余天+港都夜雨+台灣的歌

修行在世間，孤獨作行囊！李商隱最好的四首詩，一字一淚，寫盡世人孤獨

修行在世間，孤獨作行囊！李商隱最好的四首詩，一字一淚，寫盡世人孤獨 雲捲花開 88K subscribers Subscribe 542 Share Download Clip Save 9,979 views Sep 7, 2023 #幸福 #雲捲花開 #獨處 • 一個人開始轉運的徵兆。看到這支影片，首先得好好恭喜你，說明你即將開始轉運了... • 低層級的人還在談能力，高層級的人都在吸收時空能量，開悟：用能量打開先天本有... • 人一生最高級的活法，是學會取悅自己，讀《簡·愛》，學到如何才能“真正取悅自... • [完結篇] 人一旦開悟，能看到什麼奇特景象 | 人生開悟#yjhk ------------------------------------------- 开悟必知空性，色即是空，究竟是什麼意思 • Video *錢就是道，赚钱即是修行，錢的靈性很高，你越懂她，她越找你 * • 錢就是道，赚钱即是修行，錢的靈性很高，你越懂她，她越找你 | Money ... 莊子：人生，最重要的東西，都是無用的！有用，可以讓我們活著；無用，能讓我們活成一個“人” • 莊子：人生，最重要的東西，都是無用的！有用，可以讓我們活著；無用，能讓我們... 後來我才知道，人只能悟，不能渡 • Video 老天要渡你，命裡會出現6件事 • Video 放下，你就贏了（句句精辟）| Letting go. • 放下，你就贏了（句句精辟）| Letting go. #雲捲花開#yjhk 鬼谷子：牢記兩條天規，從此人生順達，福報不斷 • 鬼谷子：牢記兩條天規，從此人生順達，福報不斷（已分章節）#雲捲花開 #YJHK 三個行為，影響你的好運氣！一旦戒掉，你也可以時來運轉，否极泰來！［鬼谷子］ • Video 讓別人失望，是一種極高的智慧 | 任何人都不想讓你知道的『處世秘密』！ • 讓別人失望，是一種極高的智慧 | 任何人都不想讓你知道的『處世秘密』！（... 不論和誰相處，都要學會間歇性冷漠 | 無法情緒斷聯的人，都活成了易碎品 • 不論和誰相處，都要學會間歇性冷漠 | 無法情緒斷聯的人，都活成了易碎品 #... 心軟之人皆是無福之命？ 牢記鬼谷子這3句話，福報不請自來！ • 心軟之人皆是無福之命？ 牢記鬼谷子這3句話，福報不請自來！ 有福之人有三寡，越寡福報越大！ • Video ------------------------------------------------- 歡迎點讚💗轉發💗評論💗 ☆ ┊　　┊　　┊　　┊ ┊　　┊　　┊　　★ ┊　　┊　　☆ ┊　　★ ☆ 歡迎提出您的意見和建議，我們會努力做的更好。 #雲捲花開 #讀書 #處世之道 #人際關係 #生活 #認知 #思考 #極簡 #獨處 #生活 #成長 #智慧 #女性 #理想 #reading #happy #myself #Thinking #alone #人生感悟 #心靈雞湯 #人际关系 #读书 #幸福 #修身 #渡己 雲捲花開 88K subscribers Videos About 歡迎訂閱“雲捲花開之心河渡口” 17 Comments rongmaw lin Add a comment... @原世-i1f 1 year ago 迁雨吱淋寻谦语 万江湖南京北周 诗海腾龙云霞彩 东过图字体客育 1 Reply @chancorwincof 1 year ago Thanks a lot 🧚🧚🧚✨✨✨ 3 Reply @楊志強-w1q 1 year ago 人生為孤獨點一盞燈！ 4 Reply @mingchungkwok664 1 year ago 孤獨處境!天空海闊!!😊🙏👍 3 Reply @柯新和 1 year ago 感恩 2 Reply @vivianou951 1 year ago 好夢由來最易醒，事如春夢了無痕。不以物喜，不以己悲，觀世事無常，心如虛空。 Reply @kokhaurng8566 9 months ago 我觉得出名的诗，应该每句有七个字。六个字或一下，太短；八个字以上，太长。太奥妙了。 Reply @周源通 11 months ago 感恩、妙音菩薩、漫步、,日子彷佛是野野、日子彷佛是荒荒、走出去時漫無目的、然而卻有主張、落葉一張張、山徑到處有坑、腳步一高一低、久走也成了習慣、眼中的世界己經沒有俗物、也無骯髒、這漫步的世界、在合流同汙之上、也不一定自命高尚品格、只是隨處走走、把縛緊的心靈放一放🙏 Reply @chileungcheuk3813 1 year ago 🌄獨自一人生活不等於是「孤獨」,孤字暗藏著有徧離一个共体的意思。应说真修的人喜歡撰擇一人的清淨較貼事實。 論真相,修道於實不用撰擇過一人之生活,但獨自修行確是較容易另人避開從「依他起」而來的煩惱,就是事實。 看清经「依他起」而來的一切「人事物」,均屬是無中生有的,修与無修二事根本無差別。 --「即離依他起,當下見如來」講哂了 ！--😄😄 Reply @sionghock 1 year ago 😊 2 Reply @rjgong88 1 year ago 里伤隐 1 Reply @hubenbu 1 year ago 善緣可向佛求得。 1 Reply @陈鸿亮-s2q 1 year ago 好一句孤独让人请醒,明智,👍👍👍 Reply @simonchen1223 1 year ago 阿彌陀佛 感恩慈悲分享 1 Reply @河秋 1 year ago 難怪他的詩被多數評為隱晦難解 原來是他刻意不想讓人知道他的悲苦與孤獨 Reply @楊又璇-b6x 11 months ago 清爽清醒明智 Reply @AzothTeng 1 year ago 🥹 Reply

獨處是一種能力，是人生最高的修行 | 享受孤獨，學會和自己相處，學會和內心相處。才是最好的生活姿態【愛學習】

獨處是一種能力，是人生最高的修行 | 享受孤獨，學會和自己相處，學會和內心相處。才是最好的生活姿態【愛學習】 Love to learn 134K subscribers Join Subscribe 1.7K Share Download Thanks Save 76,539 views Jan 27, 2021 #孤獨 #獨處 #愛學習 ‣‣極簡人生：多餘的東西，讓我們變成了物品的奴隸。想要生活得更輕鬆，就要學會斷舍離 | 放下了，才能把心騰出來，迎接更美好的明天【愛學習】 • 極簡人生：多餘的東西，讓我們變成了物品的奴隸。想要生活得更輕鬆，就要學會斷... ‣‣ 2020年| 20個人生道理，希望2021年過得更好！回顧2020，展望2021 【愛學習】 • 2020年| 20個人生道理，希望2021年過得更好！回顧2020，展望... ‣‣ 人這輩子最不能缺什麼？這樣東西，從來都是一個人最硬的底氣，成年人的安全感來源 【愛學習】 • 人這輩子最不能缺什麼？這樣東西，從來都是一個人最硬的底氣，成年人的安全感來... ‣‣ 極簡：聰明的人都選擇和這三樣東西斷捨離 | 只要忍受一時的不快樂，才能享受長久的歡愉 【愛學習】 • 極簡：聰明的人都選擇和這三樣東西斷捨離 | 只要忍受一時的不快樂，才能享受... ‣‣ 假如有一天，你覺得太苦太累，不想工作，就去看看這3樣東西 | 成年人的世界裡，我們別無選擇，只有繼續奮鬥【愛學習】 • 假如有一天，你覺得太苦太累，不想工作，就去看看這3樣東西 | 成年人的世界... ‣‣4大定律: 改變、完善、強化自己 ! 一個人走上坡路的法則！ 讓你變得越來越優秀！ 【愛學習】 • 4大定律: 改變、完善、強化自己 ! 一個人走上坡路的法則！ 讓你變得越來... 愛學習會員渠道啦！❤️ 【支持愛學習】 / @yt-lovestudy 聯繫:goman20200301@gmail.com #愛學習 #獨處 #人生的修行#孤獨 #和自己相處 Love to learn 134K subscribers Videos About Facebook Instagram 86 Comments rongmaw lin Add a comment... @Mia-li6tf 3 years ago 讓我告訴你:如果你遇到一個孤獨的人,不管他們告訴你什麼,都不是因為他們喜歡獨處。那是因為他們之前也嘗試過融入這個世界,而人們一直讓他們失望。 46 Reply 8 replies @ilemon0916 3 years ago 會不會是對別人寄望太多，失去了自己，所以才會對別人失望？ 5 Reply @candylam9444 3 years ago 是的! 1 Reply @YienFei 2 years ago 真正的快乐是自己给自己的 7 Reply @liyuhao-oq4vl 2 years ago @YienFei 是的，只有自己知道自己想要的是什麼，自己想要的快樂也只能自己去爭取 4 Reply @kuo7396 2 years ago 跟自己對話，獨處，增加正能量。就算人們一直讓我們失望又如何? 2 Reply @美青葉 2 years ago 同感， 經過了一個個，療愈 就清楚醒了 1 Reply @陳韋杉-j1k 5 months ago 孤獨的人，跟喜歡獨處人是不樣個性別混為一談 Reply @lunawang2776 2 weeks ago 哇 真的 Reply @微尘-o5m 3 years ago (edited) 其实生命的本性就是: 苦，空，无常。 孤独是常态。每个人都是独自来人间投胎，又独自离开人间。相伴都是暂时的，一切如过眼云烟，了不可得。 22 Reply 3 replies @camnhan9564 3 years ago 其實,自己蠻喜歡一個人獨處，做真正的自己，逍遥自在。更奇妙的是，在青年時期，睡夢中夢見自己舒服的躺在空曠地上看天上白雲悠悠，忽然天上漸漸出現 逍遥 逍遥 的字。或許暗示什么，但自己確實不喜歡被管住，被束缚自由，欣赏一個人獨來獨往。 感谢好文章分享。👍👍👍 14 Reply 愛學習 · 1 reply @BoSong 3 years ago 为人最高境界，享受孤独而非追求所谓幸福！ 17 Reply 1 reply @mhchen5 11 months ago 孤獨又沒錢，失去可依賴的人了，對未來沒有安全感。真的很可怕 3 Reply 2 replies @YT-li4wh 3 years ago 孤獨不可怕。而孤獨又沒錢才可怕 36 Reply 1 reply @陳貴女-f3g 3 years ago 孤獨是一種能力。我開始驗證。 7 Reply 愛學習 · 1 reply @Ken12467 3 years ago 從來沒學過，自出來工作，一個人住後，一向都是獨來獨往，反而不太喜歡跟人溝通。 7 Reply @jackyguo732 3 years ago (edited) 習慣了孤獨就不會再寂寞了 9 Reply @れんげいもうと 3 months ago 龜毛不重要，獨處最重要 2 Reply @vickychan6480 3 years ago 學會和自己相處 7 Reply @qazw698 2 years ago 喜歡你很多對於生命的理解，這篇最有共鳴，生命就是靈魂透過體驗昇華的過程 6 Reply @福成-d6w 3 years ago 心安平靜！一切順其自然。 13 Reply 愛學習 · 1 reply @陳主狀 3 years ago 不要執著。要學會放下。 7 Reply @a350210 3 years ago 享受孤獨！ 4 Reply @傅夢夢 9 months ago 學到不少 1 Reply @文友郭 3 years ago 孤独是优雅的，是美好的，我很享受孤独 😍 4 Reply @ongbcg6011 1 year ago 人生变化無常，到了一定的年纪，孤独是给自已最好的生活，平常心❤️去面对一切。祝安康。 2 Reply @王銘德-m4p 3 years ago 孤獨能夠內心思考，放鬆定義大利用於心中快活，冷靜靜坐著重於心放空，空間思考量大概括承受自由自在，定慧能思考生命力量解放圓滿。 6 Reply 1 reply @oliviaxue5360 2 years ago 好棒👍！特别是后面一些精句！的确，人生就是一场修行…… 5 Reply 愛學習 · 2 replies @黃麗萍-j8c 3 years ago 孤獨彷彿成為新的代 明詞昨天經過路邊看 見獨立鍋的招牌暗示 單身者的福利不禁莞 爾一笑 是啦我早就與孤獨和 平共處樂此不疲 在孤獨中會沉澱你的 心靈找回你的思緒更 能深入探討問題所在 過多人際的交流都是 空泛貧乏的只是無謂 浪費時間生命 就算是一個人呆坐思 緒卻到處飛揚怎會寂 莫 3 Reply @davidcheng6402 3 weeks ago 我以出世的心態，孤獨的活到今天！每個月都出去國外，孤獨的旅遊，看遍了許多人及事物，能夠在72歲的年紀！仍然這麼做，覺得幸福及幸運！入俗世而保持出世的心！也許有些時候，覺得孤單，但是，人生沒有完美的！自由自在的孤獨，是一個幸福的人生！我常常告訴我自己，也告訴認識我的朋友！生命的終點，必須一個人孤獨的走！所以，必須在那之前，享受幸福的孤獨！ Reply @huanxiazheng6579 3 years ago (edited) 人贵自重, 善待他人, 善待自己。 3 Reply @yangtony1319 2 years ago 內心強大的人適合孤獨，但是死在屋內無人知。 2 Reply 1 reply @liongrose1173 2 years ago 病了， 爬不起来， 怎么办呢 3 Reply 愛學習 · 1 reply @namhoyau7302 1 year ago 如果沒有性需要的前題下，我都同意 1 Reply 1 reply @johnyen1188 1 year ago 學會如何享受獨處的人才會學到如何與他人相處。 1 Reply @frankiechong9284 9 months ago (edited) 年轻为了生活而拼搏，年老了何必面对他人的问题，搞得自己那么的累。。。倒不如自己独处，活的开心，也借这机会，宠爱自己，不枉此生。。。 Reply @kuo7396 4 months ago 我身家衝五千萬，不婚不生，退休繼續在工作。早上做股票好玩，中午晚上去夜校當老師，假日自己打掃，採買做營養食物。請朋友小姪子吃飯逛街。給老母孝親費。單身50幾年，我很享受獨處，無用社交，無窮的爭吵很恐怖。 Reply @linlee5366 3 years ago 晚上好🌇感谢🙏您的分享👍👍👏🏻👏🏻🌟🌟🌟🌟🌟🌟🌟🙏🙏❤️🧡🌻🌈好的生活姿态是在孤独中成长。在磨练中成长。 3 Reply @邱慶榮-g1d 3 years ago 謝謝愛學習的分享謝謝你 5 Reply @海于-f9r 1 year ago 生活是自己的，只有自己知道，人孤心不孤 1 Reply @曾薇霓-x6p 3 years ago 我覺得獨處真是1種享受。 14 Reply 愛學習 · 1 reply @beeharong7228 3 years ago 獨处并不可怕，沉澱自已是美好，更可怕的是身边很热闹，却无知心人， 7 Reply 愛學習 · 2 replies @coolman_1087 2 years ago 生命的意義學會獨處 找出真我 另一種內心強大的境界。 1 Reply @chanstanley8802 3 years ago 喜愛清靜，不爭無為，就不會孤獨了。 2 Reply 愛學習 · 1 reply @葛瑞詩Grace 3 years ago 享受孤獨，享受寧靜之美 。 3 Reply 愛學習 · 4 replies @a350210 3 years ago 興起每獨往，勝事空自知 1 Reply @IDon-wj4ti 3 years ago Do not confuse SOLITUDE with loneliness ... One builds and another destroy! 5 Reply @3tht148 3 years ago 😊😊。。我是個異類這人世間困不住我。若未來只剩孤獨我不要活不值。。 Reply @Aaron-f6n2e 1 year ago 孤獨不存在，存在的叫慾望 Reply @呂秀惠 3 years ago 拒絕❌ 1 Reply @susan2368 1 year ago 👍 1 Reply 愛學習 · 1 reply @朱秀莲-x4z 3 years ago 👍🙏🏻🙏🏻🙏🏻 2 Reply @呂秀惠 3 years ago 久久看一次。五色鳥 1 Reply 1 reply @clairelee939 3 years ago 👍👍👍 1 Reply @帶刺的玫瑰-v7q 3 years ago 向大叔学习，真开心，享受孤独！🕶️ 2 Reply @siewthohong6618 3 years ago 👃👃 1 Reply @徐秀鶴-s3o 3 years ago 瞎扯 1 Reply

學會和自己在一起 蔣勳、林懷民在獨處的過程中得到什麼新體悟？

佛光山惠中寺２０１９「未來與希望」系列講座 講師：蔣勳

金剛般若波羅蜜經—蔣勳讀誦

心聲淚痕&南都夜曲🎶探戈演奏曲🎶經典懷舊老歌聽出好心情💕

23首 探戈 (5) 輕音樂 放鬆解壓 | Relaxing Chinese Tango Music

22首探戈 (4) 輕音樂 放鬆解壓 | Relaxing Chinese Tango Music

23首 最好聽 輕音樂 | Relaxing Music

22首探戈 (3) 輕音樂 放鬆解壓 | Relaxing Chinese Tango Music

20首 最好聽 輕音樂 | Relaxing Music

石川さゆり - 津軽海峡冬景色 / Tsugaru Kaikyo Fuyugeshiki

白冰冰 + 洪榮宏 - 女のためいき ( おんなのためいき ) 【日文演唱】

EVERY MADE JAMES HARDEN FG 19-20 SEASON

EVERY MADE JAMES HARDEN FG 19-20 SEASON STUDY THE GAME 2.78K subscribers Subscribe 418 Share Download Clip Save 32,399 views Sep 16, 2020 EVERY MADE JAMES HARDEN FIELD GOAL 19-20 SEASON Transcript Follow along using the transcript. Show transcript Transcript 0:01 yeah okay how was that last year this year but let's talk about now because i'm living the dream in the nba first field final menace of 0:08 the first half middleton now defending on hart and he 0:20 we hope it's a good one here's james harden going to us holding on to that slim lead 0:25 22-19 there's harden going through the entire pack of pelicans wow losing out there he's 0:30 got him mesmerized and he's shot it he's going to try it again yes 0:36 if at first you don't succeed good three points 0:42 hard got it arden now gets around hard for the slam 0:51 towards harden not only guarding it with one man but shading the rest of the defense now he gets to the basket they move 1:00 [Music] martin on the drive to the middle hardin lays it up and in 1:05 and he's fouled stay in front of harden normally uh roberson 1:10 has that pass but he's not playing tonight and there it is james harden i want to go that's okc is able to get 1:17 chris paul and a bunch of draft picks as james harden fast break schroeder now is trying to 1:24 guard hardin martin is fouled and goes 1:29 off the ball [Music] down the middle hardin looks comfortable 1:35 off the ball but continue to attack keep the rockets off the glass they're missing a lot of shots 1:41 there is another and one culinaries like a lot of three-point shooters they have no range because they have no 1:48 conscience martin with arch madness coming to toyota center make sure you get some tickets for that 1:54 well that's like the old days there's harden now [Music] 1:59 hardin gets around the pick by tucker and lays it up and in man so gonna go and harden lays it up 2:06 there perfect for it martin gonna dance hard gonna shoot park gonna score he had 16 points and 2:12 five five assists in 20 minutes in his season debut with the wizards 2:19 around the sepal ocean pick 2:25 [Music] 2:30 [Applause] so maybe not more veterans just a 2:36 different look [Music] and one same result again the wizards 2:41 especially without john wall hard with the cut for three 2:48 hardin gets the rebounds puts it off the glass five on four for the rocket yep feels 2:54 slow to get back good job by hachi oh second effort by heart [Applause] 3:00 capella right place right time twice in that sequence and a deep triple drops 3:08 in that good rui hachimora has no ceilings on his game 3:13 [Music] rockets back down to deuce hard stepping right 3:20 [Applause] here comes hard again oh my 3:30 god 3:43 oh hard again 3:55 [Applause] 4:01 [Applause] [Music] 4:07 [Applause] on the rookie 4:14 [Applause] 4:21 jared allen this time martin drives past him gets inside lays it up beautifully 4:26 get the match up they want they want musa on him harden for three james harden with his 4:33 hooked up by hardin harden nice move and an easy layup 4:40 the shot itself it's developing the confidence to take the shot james harden flips it up and in 4:47 [Applause] [Music] and an easy bucket for hard i'm 4:53 surprised perfect example of what the best the nba has to offer the type of man he is the type of teammate he is 4:59 as hard knocks down the three to watch how improved they are how hard they play 5:06 i just love what they're doing with their roster getting tough guys there as hard makes them 5:14 james harden gets inside makes the contact and flips it 5:19 it was in no call and then irving hit the three-pointer and it's backed [Applause] 5:27 by the net to get back pardon with the finish the rockets have 5:33 missed eight of their first nine threes butler takes the challenge defending hardman who buries the throne 5:40 first triple heat ahead by 32 and over five minutes left in the first half that was too easy for hart 5:45 he just scooted gork harten into the paint puts it in and 5:52 harden with eight seconds left in the head the step back three wow 6:00 back on the road for them i think he's gonna play him through the end of the quarter as starters and just see if he 6:06 can generate any kind of a little physical with harden and he's doing a nice job of forcing him into 6:12 some tough shots that's a tough shot i mean there's not move martin just does get to it shot lock 6:17 about to go off though uses the capella screen leans in 6:22 guterres also out there before the grizzlies has this kyle anderson aka 6:28 slo-mo hardin started 6:40 grizzlies that was just their 11th free throw attempt harden off the window hard with anderson 6:47 on his hip pocket it's his own miss goes back over him scores you see how hard he's playing his 6:52 right hand very strong because he won't come back to the left side not not a ton of lift either barney with 6:58 the left counted martin a long one good 7:06 house off his fingertips luckily harding got it back shoots the quarter three 7:11 even three-point game approaching four minutes play at the third barn on his way into 7:16 the paint floated it up and over come on the rockets trying to add to their 8-0 run 7:23 martin four three eleven it's hard again 7:30 through the lane 38 and the crowd has a little bit of 7:35 life back fires 7:40 by the rookies austin rivers quickly comes the other way hardin drives there's the euro step and 7:46 james harden the defenders in the nba 7:52 and hearts gets to the rim finishes just he knows what he's doing and a big 7:57 part of it playing four years says hardin knocks down his football well so far this year 8:05 step back again now he's got himself from the rhythm back to back three 8:13 all right now the euro step in an easy two 8:19 another step back another three james harden lighting it up here great recovery especially after the 8:26 offensive rebound hardened for three well he missed his final seconds hard drive 8:34 gets inside layup is well good loose he thought he got hit on 8:41 the arm hard meanwhile left wide open who knocks down the three-pointer presence 8:46 this is will be his 18th year in the league arden for three james harden offense uh 8:53 from last season to this season as james goes one on one against marketing [Music] 8:58 but the bull is five the bulls don't have a traditional center out there either 9:05 straight away james harden that's the rockets turnover rate be super high but 9:10 they've actually done a very good job this season gordon out there with these three hardened tucker and capela 9:17 our dances steps left shoots scores 9:23 rockets won't head to new orleans until tomorrow 9:32 hard with a pullback over the big man [Applause] you can make an argument that he's 9:39 probably been the rocket's most consistent player to start the season and kaylee kind of highlighted that in memphis the 9:45 grizzlies were three for 25. harden 9:57 what a tough shot rockets plus eight on the glass well 10:06 [Music] 10:14 he's responded with 21 in the last three yeah there's another one 22. 10:21 good health defense j.j reddick hart was taken out by house though man did you see that yeah it's tough 10:28 45-37 halfway through and nobody stopped the basketball too easy 10:33 man is that easy [Music] 10:38 hard euros good defense better off night at seven 10:46 that's now eleven fours over the last several seasons with those playoff matchups et cetera 10:52 pardon for three wow threes at a high percentage now hard they're trying to get him going 10:58 and he's gonna get the floater they got what they wanted out of the timeouts 11:05 eurostep for hardin hard walks it in 11:10 arden dances hard drives in plus the whistle [Applause] 11:21 and in a tight game too mike d'antoni all the way hard 11:26 they bracket him he'll get the runner again so harden coming through 11:32 capela had two back-to-back 20-point rebound games last season 11:39 harden looking for more he's on more he'll shoot he will score rockets 11:45 will get that fourth win in a row [Music] 11:52 and here's harden with a timer at five he'll take the first shot of the game and it's on the money he is not shot at but 11:58 [Music] here's hard in transition gets to the cup and gets the layup 12:04 [Music] [Applause] [Music] harden goes behind the back gets to the 12:09 rim and what a beautiful shot off the glass now that historic come back 12:16 hart drains another one [Applause] here's hard in transition [Applause] 12:23 step back three he's good that's third [Music] inside two to play in the first half 12:29 nobody picks up harden and you know he's gonna fire it from 30 clippers have missed 11 12:36 consecutive threes back to back but it remains in houston possession 12:43 hardin again able to fight through that double team get into the way and put it in arden with 22 points eight 12:49 in the second quarter 14 in the first gets by his defender and gets the bounce boat 12:56 and just get rid of this right now eric four minutes to go harden 13:01 drives and scores james hart now with 34. you know that they administered the rule right 13:06 i'm not on the referees he's austin rivers 13:12 [Music] hart pulls the trigger from deep buries 13:18 the 50 40 90 guy yeah and he's one of the best in the league at it that's right 13:23 are you stepping fires in here porsche and drive it down the freeway back to new york from phillip 13:30 there's harden with a runner 13:36 [Music] [Applause] 13:41 [Music] i would do it if bill does it that's 13:47 what you say and start putting some balls in the basket now with under four minutes left to play james with a step 13:52 back got it there you go now you've got hardened with the secondary offense [Music] 13:58 that secondary offense is pretty good on the step back putting the spell on it got him 14:04 mesmerized now he goes to his left lays it up in here using that pick by 14:09 mclemore so he got the switch he wanted gets by warren no problem 14:16 he hadn't heard it in a while he never got on drexler like he got on everybody else though put it up and 14:24 nice chandler looking for harden coming off that pick [Music] arden great job what did you see 14:33 hart on the drive going downhill [Music] 14:39 now he's double team who's open well i guess hardness 14:45 7 4. yeah he got it over goga barton steps back from the parking lot 14:54 these their uniforms stand out art stands out rolling to the rim and for anthony towns although 14:59 that right hand still seems to be bothering him hardcore pull back oh what a tough shot 15:06 actually we got in last night it was basically as cold here as it was back home 15:20 [Applause] in and out three wolves there couldn't get the rebound to kick out three 15:28 it doesn't for layman i'm looking forward to your first layman punt harding coast to coast 15:35 signing hard gets by coveted comes around the pick leans in for a three a two for one and it drops 15:42 great shredder from outside the arc regard for big man doesn't matter hard 15:47 from the mid-range [Applause] oh nice play yep set up harden set the 15:55 screen gave him space and he knocked it off weak side corner to help out bart pulls back 16:03 looks good it is [Applause] rockets on an 8-2 run hard pulls back 16:09 trying to make it 11-2 he's got 36. hard to get with space 16:16 [Music] takes advantage of it that's a goaltender oh one-on-one 16:24 hard drives got fouled and it counts plus one was last night and next up is gail 16:29 goodrich the hall of famer hard stepping left scoring 16:37 [Applause] [Music] [Applause] 16:47 got a piece of it doesn't matter i think cover got a p i'm getting closer to the basket 16:54 i'll pick up on harden did he come on three the heart zach collins is too so they've 17:00 really missed those two guys rockets have had their share of injuries but not for that long time 17:07 hard steps back in fire 17:12 harden picked up by rocky hood goes right by good 17:18 [Music] double team on james he dribbled right 17:24 out of it actually 17 nba players from houston that was the eighth rebound for 17:30 russell westbrook's get 14 seconds it's two blocks on white side hardened 17:36 to the basket can't stop it team rebounds for capella harden got a step harden with the 17:44 rebound martin's got five boards on the drive to 17:50 the basket lays it up and in he's up 17:56 arden steps back fires and hits 18:01 back door play to harden for two more kicks his pocket two on one right at murray basically 18:08 lets him go as milsa picks up heart 18:14 and he's trying to double but hart goes right by it and i think guys you can pass along three 18:19 and that's that's not how you're going to beat houston hart way outside and the three is good and 18:25 made three to lead the league and everything as he 18:31 gets inside beat the clock and the nuggets can't collect the rebound 18:39 left short he wanted to pass it out to the the three and kept looking at it now knocks in the 18:45 triple see that's a five points let's see if he'll see a whole lot of james harden over the next few seconds 18:50 parker shoot the three nuggets got there late is 19:05 splits the defense down the lane for an easy scoop layup george bad pass and harden's going to 19:11 have the easiest two of the night for him now he's got another star and 19:18 only his second game but he's just he's an easy guy to play with his heart gets to be popped away by paul george 19:24 but tucker dives on it gets it back out harden hits a three paul george misses that 19:30 [Applause] hardin count it and the foul check 19:39 westbrook hard wide open for three [Applause] yeah i think you're right lead cut to 19:46 two hardened for three we back up the and the clippers acquired in that chris paul 19:53 trade hard gets inside banks at home just enough neither team fouls to give 19:59 both in the penalty under two to play hard to step back puts up the three got hit shots good and one jake now so it looks 20:08 like the dallas mavericks have a wood woken from their nap and rockets have not away 20:20 [Applause] right off the inbounds pass 20:27 arden to the middle puts it up and got it [Applause] delon wright out of utah 20:35 stepped back by hardin house to pj down to capela pella had curry on him but didn't see 20:42 him and hard rockets bench has not been a high scoring bench all season long they've got to get better 20:48 hardin takes it right to the basket later on down the line here's hardin in the open court all the way to the 20:54 basket for two jack he's only 20 years old he's got moves veterans don't know about 21:00 and there's hard for 21:12 there's hardened to the basket for two that's a 21:18 [Music] 21:27 dribbles right through the double team kentucky yeah he shoots 52 on those pull-up jumpers that's his name 21:33 harden yes group and they've shown that here so far rivers gets a double team thank you 21:40 kaylee and hardin will shoot a three and he's right on the money 21:49 [Applause] 21:57 the best i've seen westbrook and hardin share the ball and the scoring duty 22:03 watch out he's unbelievable with everything intact 22:10 hardin pulls his way to the basketball heart and there it is rockets have to get into the shooter 22:16 martin has to fire it up from home he knows he can get a shot for himself 22:22 every single time deep in the corner falling away he's 22:27 waiting for help he's one on four right now [Applause] 22:33 he's inbound rockets on a 7-0 run [Applause] oh james passed it to it but they didn't 22:40 keep those players together [Music] back door to play with russell westbrook 22:46 you better run in oh from another universe he was outside 22:51 we're watching the car in action 22:57 martin's in the basket [Applause] 23:02 all the way to the bucket oh how cagey and you guys had to go to minnesota the next night houston 23:08 to minnesota at least they gained an hour last night atlanta did a friendly rim 23:15 handles that basketball like a yoyo 23:23 martin's got him mesmerized and hits the three 23:30 step back for harden got it he's got 23:37 [Music] [Applause] [Music] 23:43 their last win was like november 11. again think about all the players that 23:49 have played in the nba directs only 10 of those players have a career high 23:55 of 40. [Applause] goes to james for a ho-hum two 24:08 [Music] [Applause] [Music] 24:17 brook has really found some success in the rockets offense martin right down the baseline for his 24:23 first points [Music] 24:30 and floats [Applause] 24:38 and it goes 16 for hardin 24:45 hart drives dunks finish on the reverse but there's clint 24:51 capela there to deny and then horton trailing shoots and scores 24:56 the trip hard looks to attack turns the corner and 25:02 sees he's able to it's only a 13-point game but just over 10 to go plenty of time 25:08 and hart gives the rocks and the old school spurs rockets with seven more makes the left 25:15 hand the rolling runner i've seen the ball where it pops back up and doesn't go through 25:21 hardened trailing tough contested three over running 25:28 [Applause] 25:38 so that was a nice layup another turnover their fifth the rockets have come in six and hardens first beat us here tonight 25:49 get in there yes it took a tour susceptible to giving up a lot of three-point shots and the 25:54 rockets are trying to take advantage of that here's another one hardin has made the most 26:00 hit him on the arm and got away with it pull up three james arden rivers 26:06 penetrates [Music] 16-1 run harden oh 26:12 through some contact right to westbrook hard one-on-two to the line to the lane 26:18 in plus to reverse fakes it steps left doesn't 26:24 take it back to hard to clean look yep what a play 26:31 harden picked up outside going to his right throws it up and then 26:38 got to get harden going now let's see if he can yes two and one hardened outside trying to 26:43 work on that jab step with oobre and kelly able to lay off harden's got it 26:49 and heavy trap now that's a jump [Music] 26:54 trying to guard the beers finally by phoenix into a 10-3 run of their own 27:02 the bears to the basket for two and one one-on-one with uber 27:07 eight on the shot clock hardened to the basket lays it up and in he's playing well on 27:14 the road too they get a win here tonight they're going 2-2 on this four-game road trip hart in and out and back in again 27:21 [Music] arden will fire up the three got it 27:30 immediately get down into the block see you got a size advantage and see if you can make it work harding two-nothing rockets rest of the 27:37 kings following the defensive game plan well we saw him last night i 27:44 [Applause] mean [Music] 27:53 makes a difference when you're closer to that three-point shooter when you shoot arden goes around three players throws 27:59 it up and it goes in with the rebound outlet picked off careless turn over 28:16 [Music] 28:21 [Applause] against the team that doesn't play very good defense 28:30 there's your offense right there let's go close oh dropped it between his own five hole 28:37 and hart sticks to three winston garland one of my teammates we had a lot of fun that year and it's 28:42 very cool to see his son out here playing step back three for james harden to start this game not even 28:47 halfway through the first martin gets it back [Music] wow how about james change to a foul on 28:54 the floor the original indication by official evan scott when he put two fingers up taking the two shot foul harden slices 29:01 to the hole he is hard now with 12 points and just picked up his second assist 29:06 or harden has to be like a kid in a candy store because they're not doubling him he hasn't seen him trying to measure him up 29:12 harvard works around a capella screen hesitates leans in and scores clarkson 29:19 has upped his three-point usage to 47 this year little floater and that rolls in soft touching square pants pineapple 29:25 shoes you know what they look like that you might be right good eye 29:31 james harden his 4-3 they turn it over and harden in the open floor he's got 21 29:39 hardin and sexton stepping right tough three it goes 29:45 what the garland's accounted for three of those makes 29:52 can you get another one yes he can [Applause] 29:57 barton's swiping back and sexton drives the lane and scores plus the foul the whits get 30:03 past mclemore they reset it back to crosses james clarkson blew right by him and scored 30:09 harden guarded by porter [Music] down the lane he let him go to his left 30:16 then down three seconds two seconds pardon good 30:24 martin again oh right back at you capella grabs his 13th rebound 30:32 hardin around dellavedova to the pocket banks it in 45 five rockets 98. 30:38 dellavedova leans on hard and still fires a three still hits the shot clock 30:45 barton steps right fires scores look into the lane shock lock down to 30:51 three harden on the move the floater beats the shot clock 30:56 [Applause] [Music] barton the floater gets his own miss and 31:01 scores on the second plane for the corner threes barn one on one with terence ross their 31:07 bench scorer and he cooks him off the dribble austin was not with us 31:12 in cleveland but flew in here yesterday hardened the heaven it goes 31:21 wow [Applause] 31:27 harden step back for three 17 houstonians in the nba right now 31:34 three ball up and westbrook one on four alexa wisely to pass it back 31:40 to hard they don't close out on a bad idea that stopped the penetration and got a hand up on birch 31:46 again hard right to the rim and the lead hit four threes in the second quarter 31:52 carrying the magic offensively he checked holy obviously 31:57 according to the magic apparently not quite ready to be moved into a starting roll will pull back at the top shot oh 32:02 what a tough shot that is [Music] 32:07 pull back [Applause] get one up so they go to harden flows 32:15 right by gordon that's a good one three seconds to play in the third barn one on three 32:21 gallops throws and scores it to beat the magic of more than half that 20 point deficit we got ourselves a game again 32:28 martin go to the drive and the euro step come on the other side and gonna end the threw it away barney 32:34 has isaac on him waits for his teammates to join it oh no he does he's gonna shoot it out wide games hardshot just five of 29 from 32:40 three in the rockets two games against orlando they split and that was his ninth league in this 32:47 steal [Applause] hardin pulls back lets it go 32:53 it's a harpies who play tomorrow night keep trying to pour it on 51 for harding 33:01 on looking for more gets by mcw and there's 52 and 15 tried to use the 33:08 backboard but he used the side of it coming up behind harden can he catch him no he can't harden 33:14 i want to be a good match-up eight on the shot clock hardin with a step back he's got it move and get a shot harden 33:24 steps back and fire and hits he has no elevation once he makes his move into pain no he 33:30 doesn't does he oh the layout on an elite level nice young player canard already with four threes made in 33:37 this game harden [Music] 33:43 good play by brown but he didn't stay with it [Music] 33:50 nice move 34:02 you know that's always casey was that way when you play toronto he wanted to keep you off the line 34:13 good hearts on the basketball steps back fires and 34:32 rockets have a small lineup on the court it's all about the offense yep defense by harden coming over to cut 34:38 off that drive martin looking for his first basket there it is need to start it with 34:43 defense there's harden oh couple of europe 34:50 fast break harden harden to the basket made threes for the spurs in the first 34:56 half hardin puts it up and he hits at the 35:01 buzzer i wonder what mike d'antoni said to the to the squad at halftime 35:08 well it worked that was warped speed for russell westbrook 35:14 james for two more the rebound that's number eight for clint hardin 35:20 to the basket for two more tough defense they've held the spurs down pretty well 35:26 arden step back got it hardening murray been quite a battle 35:33 tonight hardin steps back and fires tip to harden here comes james james 35:39 with a big stop defensively just make sure he's that ankle inside the paint 35:46 part from three gets a very friendly go for the pump fake make 35:51 sure you make the player earn it and here's harden squeezing by and scores 35:56 doctor moves it back out harden played by beverly hart from deep yes 36:03 [Applause] hart on a step back and 36:11 hits over his heart on the step back george did not go for it oh what a move 36:17 there by heart that puts it down 25 points for kawhi leonard 36:24 hart [Applause] 36:34 able to hit the corner three but they keep it alive there's hart on the drive 36:41 season that was another good one out of the corner he is a houstonian after moving from new 36:48 orleans he used to he's one of the big reasons why the phoenix suns are playing so well this year he's been a big surprise 36:53 harding with the right hands martin on the rookie pulls back shoots 37:00 over the outstretched arms and sticks it in climbed the back of rivers who wanted to call no whistle 37:06 then harden right down broadway harding again on the rookie 37:11 pulls back fires this one a little no no no no no no 37:20 by the way james harden has 15 points just saying james harden has more than 15 jordan air 37:25 touch the gooch in the truck for the assist on that hard dancing on cam johnson comes 37:31 through the lane and oh hung on the rim and it fell back to eight only two games this season for deandre 37:39 eight with injury and of course the suspension as to see the amazing jacket 37:44 once again from calvin murphy nothing is sparkling and one 37:50 and i'm gonna try to chance to jinx them like the rockets did in houston two for one hard and coast to coast 37:56 94 got all that space for hard to drive 38:02 so he'll shoot the three instead number five [Applause] 38:10 still with it goes in to beat 38:17 again shot clocks winding down the heave for for a few years they're going to be 38:23 good now they're the youngest team in the league in terms of average age can it be three straight oh it can't yes 38:32 it steps back there it goes and there it goes back to take away the 38:38 alley-oop hardened through the lane a collision and they're gonna call 38:46 we'll pull back over his ex-teammate mclemore knocks it away hard will drive 38:53 gets by barnes and finishes by 29 in the league in pace right now and that does not make sense at all oh 39:01 what a conversion by 16 after one martin gets it back he's wide open 39:07 and it goes through 39:12 hard by barnes and that should be a goaltender have anybody on him he can 39:17 shot it himself he'll shoot for three and that's 11 consecutive 39:23 currently a 22-4 run for the rockets as they have this 23-point lead their 39:28 biggest of the game make it a 25-point advantage sometime last year with a knee sprain and a bone conduction 39:34 [Applause] and then james hart now has 20 the rockets have only hit two shots in 39:41 the fourth quarter harden steps left make it three like what you're seeing early on now 39:47 both teams are digging in defensively there's your trap again step back three is pure by they they 39:53 have it in them but they just can't play in spurts 39:58 harden from deep got it well he takes a lot of threes he takes 13. but he shoots solid percentages there's 40:06 another third one here in the first half he's pushing you're right very good mark 40:12 he's pushing he's pushing to get up there oh boy he is hotter than fish grease right now in there 40:18 with them so three guys are not playing here tonight hardin with a three straight away putter 40:24 for james harden now offensive rebound kicks it out rivers with the extra pass 40:31 hardin leans in for the contact and makes it westbrook in the corner again harden out 40:37 top off the pj tucker screen step back three foul and one 40:44 [Applause] [Music] hardened through traffic and the floater 40:49 good that was incredible baylor university and he was picked up in a trade by brooklyn he's had a pretty good season 40:56 too there's james going to the basket for two it wasn't atlanta came over from the hawks 41:01 james got it right back went up for two they just like yours used to be [Music] 41:09 oh great play without capella who's number two in the nba and rebounding we'll have to pick up the slack with 41:15 some other players great move looks like we that's good defense 41:22 step back heart three 41:31 arden again 41:36 run by houston and that's the man right there 41:41 his seven foot frame to make it difficult but then winning with a tough one oh from the third row check is 41:48 now he's bringing it up off the dribble three men around him in for two and one 41:57 martin in the open court attacks four next 42:07 [Applause] [Music] 42:20 [Applause] [Music] 42:29 that's not [Applause] a little bit of what we saw in golden 42:35 state too and hardy says 724 mark left in the fourth [Music] 42:42 harding into the lane flips it in he just has such uncanny next one we'll send the rockets to the 42:47 line art steps back and fires then he hits 42:53 one footer as he goes back nothing better than this one though yeah 42:59 last night [Applause] denver had a great playoffs last year in 43:06 the nba and there's harden fouled up i got to shoot it i haven't touched it for a while 43:13 arden goes to his right puts it up and in and he'll rockets bring it back one 43:18 minute left to play you better get on harden 43:23 in the post you got to play him for his right hand hardened to the basket and he earned 43:29 that one [Applause] arden fakes one man shoots a three got 43:35 it but he hesitated and pj with a rebound pj's been rebounding a lot here lately 43:42 and hardened to the basket [Applause] he's going to drive floats it up and in 43:48 man he shoots that ball the double team they're shading over the heart now 43:55 [Applause] left to play in this game 44:02 and hardin will fire up a three he's just unbelievable hardin working against a pretty good defender 44:09 and josh richardson but harden victimizes a lot of good defenders like 44:18 as horford hits another jump shot 44:23 on a minimum deal hardened from way deep got it and couldn't make them 44:30 pay but they get the offensive rebound harden all day got it 44:37 and back comes hard harden on the drive gets it 44:43 analytically one of the best low post defenders in the league and pretty good and gordon 44:50 pulls it out to harden [Music] [Applause] harden all the way to the cup with the 44:55 right hand leading by 13 on an 11 to nothing run harden mismatch on horford 45:04 [Applause] 45:14 well they need to start getting it because he keeps building it embiid still on the bench for brett 45:20 brown harding gets by richardson and got the soft finish [Music] 45:27 well defended that time by the rockets step back three on the way 45:34 seven on the clock step back three city 45:41 philadelphia at home cabela had 30 and 14 boards against the sixers 45:46 hardened from the wings nothing he's a knockdown shooter as well and again all the best to gary clark 45:52 harding down the baseline to the [Music] barn again pulls back lets it go and it 45:59 goes in oh and the all-time scoring list put up 25 000 46:04 plus points hard steps left it go shooting in the mid 40s and limited 46:10 opportunities from three this year for the hawks oh my goodness now you see him oh look they've gone two and two 46:16 but they've played very well hardy coast to coast you can't stop the guy especially for a 46:22 guy and click capella has been dealing with a heel bruise rockets turn the hawks over and it's hardened leaking out 46:27 after they had the big lead and they started to take tough shots and it came back to haunt them 46:33 here's hart good this time and that's you know trey young practices 46:38 with that line on the floor so he knows how deep that is 46:45 kept alive beautifully done by hulk and tucker very effective at taking oh 46:51 yes the charge here's heart from three marvin chris when i spoke with coach donovan he was so 46:57 adamant about not letting james harden get to the free-throw line he was critical eyes right now is on coach d'antoni he 47:04 is frustrated with the referees wondering will he get a technical just to get one in the time but harden stand coach calm 47:10 down i know they're not going to take the games away in the regular season they're just going to hold a turn 47:15 [Applause] still only a 32 3-point shooter which is not bad hardin 47:24 gets played opportunistic basketball and the rockets that's the only way they're going to get back into the game 47:30 harden with a three wiggins crossover by james hey he's coming alive 47:38 now [Music] 47:43 martin steps back and fires that's what he's done 47:48 it's always been that way harden puts it up at the buzzer [Applause] 47:54 [Music] step back by james 48:04 harden fires it up oh man watch out eric gordon has a 48:09 fixture in that six-man roll for the rock with a foul line jumper puts it in 48:14 and allows moran to take off the finish little bit of matador defense here he's hard 48:20 his step-back gun is in immediately that's where they go 48:25 step back three by harden puts it in and his ability to score the confidence that he's played with 48:31 allows him to play with anyone on this team as james harden yes he does valentine's three or four 48:37 hart crosses over got all the way to the top on milton cross him up 48:46 gonna drive gonna loop and gonna add two more points to the box grayson allen and hart 48:54 buries the three pardon against melton it's four on the shot clock hard 49:01 hangs and hits four rebounds on shooting splits of 50 49:06 40 83. they've made 30 assists a matter of 49:11 habit shot clock down to three hardness step back jaron avoiding the foul and hardening drops into tripling this winning streak 49:18 the grizzlies have been the best second half team in the league runner 33 tonight for the grizzlies this 49:26 is their fourth game of a season-long six [Applause] 49:32 [Music] 49:38 first night of a back-to-back it's the fifth time he sat one out and this game began 49:45 back door cut by harden and a good dime by looking like deshawn watson on that one 49:51 hardened driving gets the layup and one block for capela who averages just under 49:57 two per game harden step back that's good great pointer for heart 50:05 harden scoots inside floats it up and in 50:10 arden's got a one on two drives at caruso and lays it in gets the bounce not just 50:17 straight numbers and like mark said tonight huge impact 50:22 as harden gets to the again harden rushing it up hard goes right at pusma and able to 50:29 finish very up and down but frank bobo's thrilled with the way he's been playing 50:34 lately and james harden knocks down who's master slow start has had a good 50:40 game hardened to the rim count it and we know that he could put 50:46 up points there's a backdoor cut [Applause] [Music] under two minutes to go and what has 50:51 been a thunder control first quarter and it's hardened again that time rockets missed their last six shots 50:57 somebody got to step up and hit it there goes james to the basket that helps that's one way to get a 5 for 14 behind 51:04 the arc for okc hardin a couple of euro steps 51:10 they backed it up in college this year and the college numbers are down a little bit 51:16 harden to the basket for two [Applause] dork will try to stop the beard 51:23 can he make his last shot yes he can [Music] harden again playing one-on-one not 51:30 anymore it's one-on-one upset about that 51:37 [Music] [Applause] 51:42 [Music] [Applause] [Music] 51:49 harden with the step back there we go just five on monday and he's shooting 33 but he's a big time scorer 51:57 defense by houston and the pass ahead to hardin and he got it 52:04 pretty good defense by denver oh what a move by heart you can hang a wash on that shot 52:12 arden they left him 52:18 [Applause] [Music] 52:25 attacking and finishing hard and right on cue coast to coast 52:32 and if you come down houston was able to build that double-digit lead with westbrook and harding on the bench 52:37 harding able to get to the bucket high level right 216 consecutive games played as 52:44 harden gets to the rim center should be able to get daniel house's three-point shot correct we've seen that 52:50 hard right at caleb what about this gun [Laughter] 52:56 hard fourth there you go kept alive by westbrook back to hardin a 53:03 quick three great hard 53:09 to the rim and one 53:14 hardin step back three from the corner and he's on the board captain jackson [Music] 53:23 hardin drills at three that looks 53:29 james hart able to hit again so arden goes between two mavericks missed 53:35 it tipped it in and then he goes on to have that magnificent fourth quarter listen i think he's everything we 53:41 anticipated in incredible physicals with a nice play defensively gets the steal 53:47 and slams at hall he's over curry that time and rivers has the ball 53:53 drive by harden in the open floor takes it himself 54:01 right he should have rocked the cradle [Music] harden for third had lost the ball got 54:08 it back though and now westbrook has it hart from the corner and another 54:16 hardin with a step back three over ball got it first field goal for heart 54:21 but you have to obviously give up something to get somebody like anthony davis james harden to the rim counter six long 54:28 good instincts like they can be tough harden another layup and another foul is gone 54:38 picked up by ingram going one on one for three and harden hits it he's got zion playing just his sixth 54:46 nba game hardin for three another one for james harden his third 54:55 hardin drives his foul and scores with the right hand off the win but he's six of nine today from the 55:00 floor three of six from three-point land he'll try another three and get it 55:06 12 shots five seconds to go in the half defended by josh hart step back three you bet five three 55:15 you look at the remaining number of games as the hardin drills a three 55:21 he's been consistent every game and you know what's coming post up trying to get to the left hand 55:27 and you know it shows you on occasion that he can be good defensively 55:32 we know he's pretty good offensively that was a beautiful week and they did play a seven-footer for about five minutes 55:39 but they have a chance to go to three-and-oh with this small lineup as they want to run 55:45 hardy steps back and fires and hits [Applause] [Music] 55:53 big euro steps all right rockets can get a little closer right here 55:58 there's harden all the way to the bucket [Music] 56:05 get to the basket he does and scores easily eight on the shot clock james 56:13 check out that defense is glued to him and he makes it count it and martin gets a step 56:21 hardens to the middle lays it up in there harden step back fires pj's down on the 56:30 floor he takes it away what a basket 56:35 back outside to harden again shot clock at eight seconds harden crossover back up hits it 56:44 five seconds on the shot clock hardened deep oh count it in the game his speed it 56:49 doesn't matter how you play if you can't stop him going to the hole and how about that hard inventor's chest 56:55 being that you're six four [Music] [Applause] 57:01 [Music] 57:10 enough 57:17 one step at a time and there's step two after the previous basket 57:26 [Music] and scoring his first pass and the sun's 57:31 actually up to nine turnovers for the game two in a row for james hard to cool off 57:38 eventually they were one they're one of four from three in the corner and james hart i 57:45 think with the expanded teams in the league and i think the roster has been at 12 for a very long time it's hardened 57:51 now james harden to strip it rockets were down 48 to 26. 57:57 oh is he feeling it now it was a 60 to 55 game then the sun scored 58:02 the last five of the first half and then hart scores the first three of the third half of those eight 58:12 and make it five threes to go hit a lot of threes in that game and 58:18 hard flies right by also from daniel house go out there and challenge that shot oh good drive by james seems to always 58:26 be around the basketball robert james free from town to go and they go to 58:33 school four years before [Applause] 58:41 o'rourke trying to guard him can't do it o'neal i mean right on top of it 58:48 here's james going to the basket walks it right in for two [Music] [Applause] [Music] 58:55 james going through two defenders lays it up and in over him 59:02 and harden walks it in for two o'neill trying to pick up james james hooks it 59:07 up and misses got his own rebound information for him now 17 points off the bench for clarkson 59:14 here's james from the elbow trying to get in a little closer that shot was unbelievable yeah clarkson is 59:20 now 11 for 17. he's feeling it james finally hits configure that how you put that into 59:27 context is what we're dealing with right now with this oh the confidence that he exudes has gotten 59:34 him to that all-star type level step back three for hardin is true beat it is when he throws it out the double 59:40 team make a quick play either drive it or pass it you'll have the advantage against the defense or the night when he didn't have 59:46 to and he'll learn shot clock is a factor now as jane puts it up in hand 59:52 did a better job of rotating the basketball and the ball moves faster able to get that shot in the corner hard 59:58 answers for a team who's to say that it doesn't have a chance to make an impact 1:00:03 all right another step back three this time with smart automate james harden that's six seven shot clock at four 1:00:10 smart on hardin hardin fires up at three and he's got another one looks with confidence 1:00:16 [Applause] harden got another one 1:00:22 being feisty on the defensive end making it a little bit uncomfortable 1:00:28 for the celtics this evening man let's do it just what you've always wanted always want rick smith's food james 1:00:35 harden knocks the first shot reggie for the warriors now this and we talked to steve kerr before the game 27 games left because arden 1:00:42 knocks down his heart pascal gets by with the right 1:00:49 hand the awful game against phoenix two wednesdays ago prior to the all-star break 1:01:05 [Applause] 60s night here at chase center of the night from the field and a four-point lead 1:01:12 hardin puts his shoulder into bok donovich the tap for two that three now the switch between house and covington was 1:01:19 not a clean switch hardened for three and the rockets have the lead they're burning as he spent the 1:01:24 last couple of years with the pacers bart dancing on clarkson steps right shoots and scores against golden state 1:01:32 24 and a half minutes 17 points six of eight shooting at four five for three as hard but 1:01:38 i'll take your word for it hard to pull back three wow they're a minute to go 1:01:45 [Applause] harden through two defenders hoop and 1:01:50 harm [Music] it is not tied at 69. 1:02:00 pull back three wow james hard with 20. oh deal a terrific defensive player oh 1:02:07 they backed off a hard and don't do that biggest lead for either team here is at nine hard splits it drives it euro steps and 1:02:15 on the other side have you come up with a new name we have not we're still working okay 1:02:22 30. wow so close [Applause] 1:02:28 covington tips it over to hart martin give and go to the basket to the 1:02:35 lineup for houston hardin with the step back i think he's 1:02:41 the point shooter he's gonna have to work on his jumper in order to improve in the nba 1:02:47 well that was a rude awakening bobby portis put that up 1:02:54 oh what a move by [Applause] hardin back in with fresh legs huh and 1:03:02 you know he's excited to be knocking down those shots here in his hometown yeah hard little finger 1:03:11 harden side step three got it so let's see if he targets him 1:03:18 oh well he doesn't have to no more good defense who's running there's harden again going 1:03:26 to the basket for two traveling he would get a call or two every now and then on it but 1:03:33 harden a game that's ten points for bobby off the bench 1:03:40 there's just no way the defense the way they're scoring now the future looks bright harden going to 1:03:48 the basket they have this third quarter well neither team has been putting it in the hole here in the second half there's harden all the way 1:03:54 to the basket and he backs out good job by the knicks and hardin comes right back at him again 1:04:00 for two and one you look at the body types of harden and tucker westbrook 1:04:06 hardin got all the way to the bucket for the late dylan brooks often taking on the team's other leading scorer or wing 1:04:13 player and that's a big daunting houston they got a four on two covington 1:04:21 hardin was looking for the switch brooks able to stay with him brooks didn't foul but hardin got the 1:04:26 three coach you got to give me more playing time because in my country in greece i'm tracy mcgrady he hadn't gathered the 1:04:34 ball yet so it's on the floor he gathered it now i 1:04:40 at the team's uh practice facility i was an outstanding kickball player 1:04:45 there's some extra shots out here to be had he's shot the ball 23 times tonight 1:04:50 and hardy something like this there's not a lot of plays to 1:04:56 learn you can play exceptionally well as harden once again is leading the league 1:05:01 in foul shot attempts and foul shot makes over 10 a game and he gets that three to go coach 1:05:07 with two martin working against ocean nice sin right there that's the group 1:05:13 and one of potential martin with under two minutes to go here in the first half 1:05:19 over smart yes harden with under two minutes to go here in the first half 1:05:26 over smart yes not allowing the celtics to get a good look at the rim hardin for the lead 1:05:34 butter talk about tatum's offense defensively he's improved as well harden got all the 1:05:41 way to the cop cornell aquina and just checked in a few minutes ago hard blows pass throws it up shots good 1:05:48 that's that's the notch pretty good defense by knox he gets it back and still scores 1:05:55 this is a rockets team that just played a terrific game in boston the other night hardin flips it up and in that's more 1:06:02 hard like right 1:06:09 finally gets a three-pointer of the rebound [Applause] 1:06:14 ellington to reach in 1:06:24 [Applause] the past nine years the rockets have come into new york and won hard fouled shots good and won 1:06:33 westbrook up top hard left open and nails the three that's just lack of focus 1:06:39 they swing it shot clock to three hardened with the drive 1:06:46 the open they can go really really small they're also undefeated in games when everybody's helping 1:06:52 the problem with that is they're not you would love to have them on your team and coach d'antoni said tonight one of my 1:06:57 favorite players and speaking of favorite players switching everything which allows them 1:07:02 to zone up the hot offensive man it was a nice shot off balance just 1:07:09 flipped it up first back off for mcdaniel seven hornets with the strength 1:07:18 now starting three-point shot he's gonna have a really nice career he was really struggling as hard as able 1:07:24 to lay it up and then going into is on the bench it's like a blame game oh game 1:07:31 mcdory if you want to play you better bring your own gear 1:07:37 in the nba and the only reason i'm bringing up to you is those played more games in a hornet's uniform than you 1:07:44 far away from a quadruple double he's sitting on eight turnovers 1:07:50 [Music] four for rozier washington's added 22. 1:07:56 hard now with her on the floor but they just light up instantly look at ease when speaking about their daughters and their wives 1:08:03 what they mean to them it's definitely special kelvin sampson has really built a great program there at the university of 1:08:09 houston yeah houston beat memphis today and tulsa lost 1:08:16 arden now when he goes to the basket uncontested answer that question michael carter williams with an air ball 1:08:23 something he did several times in houston james four points that's an area that assistant coach 1:08:29 benning told me the team needs to focus on they have to take care of the ball they went on that six-game winning 1:08:34 streak everything seemed to be clicking for them throughout the month of february 1:08:40 contested they're not getting any easy shots there's one this has got to go down yes and the last 1:08:46 game was their worst from the three-point line oh great move by hardin and that was set up with the pick from 1:08:57 hardin great move [Applause] and he knows how to play 1:09:04 the beard gets right by his man at the three-point line 1:09:09 jeff green in the corner will wait for hart to shoot it and he hits it takes his man away from the double-team 1:09:16 possibility now harden gets a free lane to the bucket he has the tesla comes right back steals 1:09:22 it that'll give harden a layup 1:09:27 try to drive on him he'll take the three all right hardin off the bench 1:09:35 covington goes to the basket so does james and james hit the offense almost double team so covington gets out 1:09:42 of there hart with a long three and he hits it a couple to give up all the way back to heart now with six 1:09:49 on the shot clock oh james harden puts the old cap hardened on the move 1:09:56 there's that patented euro step and he gets it to go luca got ripped by tucker rockets have a 1:10:02 three on two and harden finishes at the bottom and poked or whatever it is they have to go through 1:10:09 that's not something you want to miss or sleep on as harden gets slipped on able to put it on the 1:10:14 deck james harden with another step back three caught 1:10:20 those international players jerseys oh wow and here i'm gonna do one for you are you ready 1:10:25 yes jj and hardin with 20 points already in the ball game in the first quarter 1:10:31 why not 23. he is hotter than fit 1:10:37 seven second difference between the shot clock and game clock hardin and one on his he put porzingis in the 1:10:43 friend zone on that block hardin drives gets it to full coverage 1:10:49 this time doris luca hanging around though didn't matter 1:10:56 cardboard rivers shot clock at six hardened with the floater got it as 1:11:03 right with his first three has five [Applause] hardened with the drive shank they were 1:11:11 like okay somebody make a shot wow a deep three is good harden coming back the other way 1:11:20 got all the way to the basket and finishes with the off head date doris his effort at both ends hardened fouled 1:11:27 and won over if you're the rockets that's the shot you're willing to give him 1:11:33 james harden flips it up shots good and the foul mclemore little euro step bank shot 1:11:39 won't go but tips this is a one point game i know we talk about a make or miss league it's also a 1:11:45 make a missed call hardin for three three points i'm jumping around walking the golf 1:11:51 course if i hear something in the bush hardin count it and the second field 1:11:58 goal for korver hardin for three just his third three 1:12:10 [Applause] houston doesn't panic about those things 1:12:15 because right now the blazers are not finishing with great 1:12:21 success if he can catch that thing with his feet kind of on that restricted area line 1:12:27 i think that's an automatic too hardened 1:12:34 hardin able to knife through the paint and see harden kicks it out to tucker tucker with a patented corner three 1:12:40 that's a little too long hardened with the put seven minutes left 1:12:45 in this third quarter blazers still with their starting five same thing with the rockets james harden though you can do that gotta set the defense 1:12:51 westbrook tries to push the pace hard trails though puts it on the deck nurkic tries to reach hard gets the land 1:13:00 now has davis on him with a shot clock at six and a three here comes hardin averaging 34 points a 1:13:06 game they'll dance and back up and put enough another 1:13:12 with the lakers having won three championships with uh the lakers nice to have a fan base like 1:13:18 that tucker takes the floor he plays with that desperation and it shows look at the drive by harden school 1:13:25 in the night anyone but let me tell you this at that eight spot if it ends up as 1:13:30 james harden gets all the way to the bigger heavier and times more talented players and he 1:13:36 gets the jump jump wow three to play in the second quarter 1:13:41 this is dude 1:13:46 here comes harden green is there meets dudley to pump the drive and glides for a nice fake by james 1:13:56 lakers trying to swarm defensively three 1:14:02 and there's smith right there jr's on him harden goes by him and got it to go 1:14:08 pretty pockets turnover right there by the lakers hardin will take it step back triple 1:14:13 morris defends bullseye nine unanswered points after giving up the first triple 1:14:19 the rockets oh nice push great roller they found a real rhythm with him but 1:14:25 now you set up everybody oh block knocked out of the hands of harrison barnes king's turn it 1:14:31 over give covington credit there for poking that away there's harden on the wing and he drains the earlier the only one that's 1:14:37 able to get inside and break down and get in the paint of houston to the move by heart 1:14:43 and the finish around and down seven of 21 on distance 1:14:51 oh there's the strength again point quarter number three game number five of eight for the kings arden with a familiar 1:15:00 step back on the familiar and covington pokes it away and he ends up with a sloppy basketball hardened with a 1:15:06 two-hand flush 1:15:13 [Applause] move on the defensive end field now four of eight from downtown there's harden going to 1:15:20 answer back and he does 1:15:25 oh boy oh boy hesitation move 1:15:31 aaron and justin on the team for indiana there's james he just continued [Applause] 1:15:37 all right what's the defense going to be on harden this time as he steps back and fires and he hits bad shot if you're a houston rocket 1:15:43 although the indiana pacers still want their guys to take those james with his eighth rebound of the game floats it 1:15:49 up look at the touch side good job by eric [Applause] 1:15:54 james sets and fires and hits cast on a three turns it inside for the drive now passes 1:16:01 outside which gives james a wide open look now that's 1:16:07 i knew you'd get that in and there's james and that's his first three of the game 1:16:13 he's one for eight james hits a three got that good first 1:16:18 step and he gets you in that rocking chair move and rocks you back and then he can get that easy 15-footer there's 1:16:24 james what an acro and he won 85 indiana look at that space for james to drive 1:16:29 and he does lays it up and in great maybe he just wants to get back and fish 1:16:36 gene oh apparently so does he end smoking no it's been great james still 1:16:43 in the game and he hits a three he has more 40-point games then he has games with less than 20. and he's got another 1:16:51 three simmons has got it to green again out to harden hardened on the drive 1:16:58 puts it up and in and it's a takes on all comers on the defensive end of the floor 1:17:05 harris trying to stay with harden he does whistle val to the free-throw line quite 1:17:10 a bit too harden quick trigger three man this is 1:17:16 almost without russell he can take it up to do it yourself as he does here pardon with that steel 1:17:22 going under five minutes to go nice back door cut by harden and a sweet 1:17:28 per game hardin squeezes off a bunch 1:17:34 and he makes a book the rockets have really been priding themselves on their defense in these seating games their 1:17:39 defensive efficiency had ranked them in the top five here that's egregious 1:17:46 you get it then james harden gets it left it short on the run out james harden against 1:17:52 embiid and then he just let him go steal jeff green on the move 1:17:58 kicks it back out for three and that's the way the rockets play backwards 1:18:03 kalinari is there shot clock down to three hard and pulls the trigger and hits 1:18:08 it's in the paint at 15 again so he's their pace and their attack on 1:18:14 the rim harden and loading up their defense ready to come to help harden again breaking him down and 1:18:22 they've cut it to 13. thunder out of fouls harden goes right around schroeder 1:18:29 oklahoma city's offense back in gear here comes hardin gets his defender on his heels again 1:18:35 points in the second half so he'll get a much deserved breather here harden quick trigger three 1:18:41 tonight stand shooting 79 percent from the field harden got it your team is shea gilders 1:18:48 alexander is one of 13 guys in the league who scores 10 points a gamer 1:18:54 team with seven minutes to go 29 points for galinari that was his second three of the night 1:19:00 but harden had one player movement can do to get you better shots and we haven't seen much of that out of the oklahoma 1:19:06 city thunder tonight the rare chance that we stand in our country and of course cp3 right at the forefront of 1:19:12 that group no questions harden pretty driving off performance by this team 1:19:19 you're 12 for green his heart goes right down no call on that pass and crash that was 1:19:24 not a foul and i'm glad the officials didn't whistle james harden puts down his foot 1:19:30 schroeder comes back out on james james going to his left can't stop it 1:19:37 and he does [Applause] james takes it to the basket for two 1:19:43 he's so strong he just look at adams try to cheat i like this shot right here you're right on top of 1:19:49 it in your living room went for a flop that's 57 235 left to play james over schroeder 1:19:57 yes oh and the money five out that the rockets play offensively harden 1:20:03 it's switched on to shake hill just alexander the drive-by and late consistently great defense by 1:20:09 the rockets harden with the euro step and reverse come on that's to utah for 1:20:15 more on these games go to nba.com or visit the nba app hardened inside off glass 1:20:21 the thunder really off to a poor start two of 14. hardin put harden has a mismatch against 1:20:30 adams little euro step wow james harden 1:20:36 against oklahoma city [Applause] oh harden loves his defender shaken 1:20:43 playing off your defense playing with pace exactly what billy was exhorting you to do 1:20:49 harden ducks into the layup for the rockets 1:20:55 harden with the three and that's his first one of the night stay with chris paul lost the control 1:21:01 harden on the break count it and harden trying to find his rhythm 1:21:09 step back three just the way he drew it up right they are cheating and helping off of him 1:21:15 with good reason hardened with the three got it [Applause] 1:21:25 hardened pulling his way to the pub doesn't work you got to kind of get him on the move dump it down to him and then use his 1:21:31 height to an mba and you can take advantage if you can play size 1:21:36 and harden is open with a couple triple back then jacksonville orlando ontario arizona state g-league and 1:21:43 playoffs now and jeff green 1:21:49 and that toss back to hardin he's not going to miss those hard door tucker banging and bumping 1:21:57 harding down the lane oh what a finish martin went for the reach hardin with the take harden with a 1:22:02 breakout and finish unfortunately that big body of adams is 1:22:07 right inside to tap it in james harden lasering in at three and feron 1:22:13 you know he's on the rockets battling in the third so the rockets 1:22:20 that incredible beginning to the half from three-point land and harden to your point getting to the 1:22:26 door who's been tasked with guarding him all night and hard right to the rim and houston's got 1:22:32 the lead again try to get it in the hands of james harden eventually there is harden quickly turns 1:22:38 around puts up the three and it is jazz in oklahoma city lost his footing they get it out to covington 1:22:43 now to harden with tend to shoot harden goes right down the paint covington can get out on him and knocks 1:22:49 down the three hard in the attack and a tough floater bowl competing for 1:22:56 that championship once again but now there's just a new resolve to keep social justice in the forefront 1:23:02 of their minds as well guys this has been the story so far poor shooting by the thunder three of 1:23:07 18. harden right down broadway right into his chest offensive rebound tucker 1:23:16 harden left got it lou dort rolling to the rim on pick and rolls 1:23:22 since then we heard rebecca tell us his hardened squares up on a three and hits badly needed check a presence that is 1:23:29 unmatched that he has so much energy that you really miss him when he's gone right now he's certainly showing that 1:23:36 presence happy with their spacing on several possessions in the first half 1:23:41 hardin was highly efficient in the first half and that continues as much as they like lou dort 1:23:47 defensively they just could not function offensively with him on the 1:23:52 floor and they're having a hard time going offensively for them no and for shea gill just alexander it's 1:23:59 been a nightmare of a night they're attacking him half this team getting closer to a win 1:24:06 yeah they've just exploited matchups at both ends and but right now he's even going it's been a 1:24:11 remarkable to watch him operate both on and off the court here such meaningful moments as harden puts 1:24:17 one off the backboard and then and one [Applause] harden crafty all the way in easy for 1:24:25 james harden nice harden taking it all the way baisley 1:24:31 autumn no contest james harden every night when you match up against the houston rockets 1:24:36 so far so good here's hardin for three that's his first hit of that russell westbrook 1:24:42 [Applause] here's harden now across the lane scores at the rim 1:24:47 you know you have to love that to be able to trust the the best skill is availability all tied at 46 and 1:24:54 harden with the spin westbrook crosses over kicks it ball movement for houston now it's 1:25:00 hardened all the way in untouched james schroeder picking up hardin 1:25:05 nearly at the half court line working on adam's easy for james harden 1:25:11 they only make 11. they have six now so this is right on schedule for them 1:25:17 harden for three he's got it just crept over the front of the rim it's changed the game and who'd have 1:25:23 thought as harden goes to the hole to score it who'd have thought it would have rendered 1:25:28 up their closing lineup the three-point guards with galindari and adams 1:25:34 step back for harden three-point hit for james harden that's a big one i lou dort dorada's done a nice job on him 1:25:41 and he got the stop but harden got the put back to go on the offensive board would have 18 1:25:46 points with a little under five minutes to go and i mean that respectfully you're right you're right i 1:25:52 don't even think now westbrook taking exception on the floater bounced a couple of times and 1:25:58 went in harden working against dort got into the 1:26:05 pain and finished [Applause] 1:26:15 and a tough shot over javale mcgee blocks the three-point potential game winning shot 1:26:21 in traffic that time over action since march uh mark and frank vogel said he was ready to return 1:26:27 versus the blazers but his back just locked up so it's been over a week since he was a lady 1:26:33 very talkative very demonstrative like another coach on the floor and james hart they've had a long time off mark they've 1:26:39 played since last saturday whistle foul and one full team james harden just 1:26:45 randomly this time danny green trying to do it caruso blocking 1:26:52 guzma going to have his hands full here harden with the three 1:26:58 no double team shot clock down to two just got it off in time and justin's up 1:27:04 to 15 points on six of nine and another block but 1:27:09 this one's gonna be great anticipation by hardin 1:27:14 and he had to punch that in or else [Applause] 1:27:22 harden floater in the paint contact block and one had to leave the bubble 1:27:29 earlier in july when they first got here because of the passengers grandma 1:27:35 draymond green recently tweeted if houston takes this series it's going to hurt the value of the big man even more davis prefers to play 1:27:44 the power forward as hardin draws the foul shots good and one there's the strength of harden one on 1:27:50 one with anthony davis little step back three got it james harden from downtown 1:27:56 [Applause] 74-68 kuzma's got six points james 1:28:01 harden drills another three-pointer [Applause] harden step back three that's good frank 1:28:09 vogel various to eight with a minute to play ten points nine assists for rondo 1:28:16 harden using the off hand banks at him turnover los angeles harden all the way 1:28:22 in too easy sent from three on the year making a couple a game he shot over 38 percent 1:28:28 from three here in the playoffs james he's caught it deep in the post as we 1:28:34 saw in transition he's hit threes and now he's hit a mid range boy hardin goes 1:28:39 right by jay seven los angeles turnovers at this point finally an escape and harden with the 1:28:46 floater caruso on him and he finds hard wide open boy how do you leave james harden 1:28:52 that open a couple of injured players on the other end westbrook gets it to harden hardened all the way in for the layout 1:28:59 all up high you've got to wait until the ball gets to the wing to be fronting too easy james harden all 1:29:06 game harden goes to the rack hardin throws it off the backboard gets his own puts it 1:29:12 back by does he's got 31 first points of the third quarter for lebron 1:29:17 hardin for an answer yes turnover like that here's hard now on the drive hardened 1:29:24 all the way in shooting the fact that they only have 12 attempts 1:29:30 is a mark of great laker defense also points per game in the three games of 1:29:35 this series scored 25 plus during the regular year as 1:29:40 hard and 15 to nothing on second chance points you got to run back and block 1:29:46 somebody out there's a three-pointer covington 1:29:51 but that's two times harden is driven without shooting that's a third drive 1:29:56 and he shot ones they'll sit and either one of them played a second in game four hardened drives good move a good 1:30:02 aggressive move from covington 1:30:07 hardin tries again this time cadets that's his first defensive player to deflection green throws it up shot blocked by kuzma 1:30:14 but right there on the follow was hardened harden 1:30:20 step back three that's good rattles home that's his second that's on the floor but from the bench 1:30:26 yeah i i i agree with marcus harden with uh a gravy 1:30:34 goes right that james lay-up is good james already with two fouls [Applause] 1:30:41 on the drive hardin with the finish he's got 21. 1:30:48 the floaters up and good james harden rivers drives blocked by davis harden 1:30:53 right there on the follow 867th lakers in control once again hardin 1:30:58 looking to post up danny green james conversation that's going on 1:31:06 nice move from james 29 STUDY THE GAME 2.78K subscribers Videos About 23 Comments rongmaw lin Add a comment... @marcopadovano3427 4 years ago 27:36 just Wow 14 Reply STUDY THE GAME · 1 reply @jpba 4 years ago Who else watched the whole video? 10 Reply @monkeymoo87 1 year ago He is the GOAT 7 Reply @liamm6208 2 years ago Look Harden man 4 Reply @studythegame9203 4 years ago 1:09:52 is when bubble highlights start 5 Reply @TAJYPOOHPOOHBLISS 3 months ago Stopped at 30:10 for when I return Reply @TAJYPOOHPOOHBLISS 3 months ago Watched the full video 1:31:08😁😅 Reply @chrishosey7535 3 years ago Can you do Damian Lillard 2021 all threes??? 1 Reply @StevenEvens7125 3 years ago Who else loves this channel and knows that @StudyTheGame is way underrated? Can't just be me. #Knicks4Life 5 Reply @christopherabellera3981 1 year ago kinakalabaw lng si irving😂😂😂 Reply @TAJYPOOHPOOHBLISS 3 months ago 1:00:15 Reply @Victor-oy8bj 1 year ago you should do this but for 18-19. he avged the more and had more isos Reply @yellowcoyote9640 4 years ago Are you gonna do all kawhi Leonard fgs 3 Reply STUDY THE GAME · 1 reply @bignardo95 2 years ago Amazing how demonized harden was for playing this masterfully by the sports news talking heads. He will NEVER win. He's arrogant. Not a champion etc etc. Now we're seeing luka doncic play the exact identical same way but he is a media darling, he has an amazing future, will win championships, blah blah blah. I wonder why! Hmmmm....anyone? 4 Reply 3 replies @ultradoesthings2182 4 years ago Thumbs up! 2 Reply @TAJYPOOHPOOHBLISS 3 months ago (edited) 57:10 "Give that to Taj" ✝️🫰😬😁 Reply

CHM Live | Fei-Fei Li's AI Journey

CHM Live | Fei-Fei Li's AI Journey Computer History Museum 150K subscribers Subscribe 226 Share Download Clip Save 6,320 views Sep 19, 2024 [Recorded September 17, 2024] Artificial intelligence has been dominating the headlines recently, but Stanford Professor Fei-Fei Li has spent more than two decades at the forefront of the field. Li shares her inspiring journey—chronicled in her new book, The Worlds I See—from her early struggles as a Chinese immigrant in the US to one of the leading figures shaping the future of technology. Here's what you'll experience: -Learn how Li, the creator of ImageNet, sees a path for technology to improve the human condition. -Hear how her curiosity and determination led her to become an AI expert. Speaker Fei-Fei Li Sequoia Professor of Computer Science, Stanford University Denning Family Co-Director, Stanford Institute for Human-Centered AI (HAI), Stanford University Fei-Fei Li is the Sequoia Professor of Computer Science at Stanford University and Denning Co-Director of the Stanford Institute for Human-Centered AI (HAI). Before founding HAI in 2019, she served as the director of Stanford’s AI Lab. She was a VP at Google and chief scientist of AI/ML at Google Cloud during her Stanford sabbatical in 2017–2018. Dr. Li serves on the National AI Research Resource Task Force commissioned by the Congress and White House, and is an elected Member of the National Academy of Engineering, the National Academy of Medicine, and the American Academy of Arts and Sciences. Moderator Tom Kalil CEO, Renaissance Philanthropy Tom Kalil is the CEO of Renaissance Philanthropy. He served presidents Obama and Clinton and designed and launched dozens of White House science and technology initiatives, including the $40 billion National Nanotechnology Initiative, The BRAIN Initiative, The Next Generation Internet initiative, and initiatives in advanced materials, robotics, smallsats, data science, and educational technology. Catalog Number: 102809038 Acquisition Number: 2024.0149 Transcript Follow along using the transcript. Show transcript Transcript Search in video 0:01 [Music] 0:10 well well well well welcome everyone here we go 0:18 um save that for the good stuff it's coming up welcome uh for those of you 0:23 that I don't know my name is Dan Le and I'm the CEO of the museum been here for about 6 and a half years particularly 0:30 excited uh about this program tonight it lines up wonderfully with our new Mission which I'll mention in a moment 0:36 but I wanted to start off by thanking all the members the trustees the supporters the volunteers the crew that 0:43 puts the programs together uh we couldn't do it without your support and help so thanks to 0:52 everyone we got a pretty much a full house here today and we're streaming online so welcome to the audience who's 0:58 looking from afar um and you'll know if you're not aware 1:04 that the museum evolved its Mission about 6 years ago we will continue to collect and preserve like all 1:10 collections institutions do and we will do it for posterity but we also care a lot about people uh CU in the beginning 1:17 people were computers and then we invented these things called computers and now life doesn't exist without them 1:24 so the mission of the institution has evolved uh to decode technology the 1:29 Computing path where we get agency because we have the collection the digital present which is a moving Target 1:35 and it's ever changing and the future implications on The Human Condition and uh the program tonight is going to speak 1:42 deeply to that from a personal perspective and I'm very excited to 1:47 welcome Fe Lee Dr Lee to the program tonight her story uh from this book the 1:53 world I see is really one that speaks very deeply at a personal level but also 1:58 at a world class and definitive professional level about the implications of computing on The Human 2:04 Condition so we do believe that all these Technologies can be used for the greater good um and that is our goal at 2:11 the institution is to help people realize uh and consider the best use of 2:16 these Technologies for the greater good I'd also like to thank tonight's sponsor the Patrick J McGovern Foundation I 2:23 think we'll put that up on stage we couldn't do these kinds of programs at scale uh and the McGovern Foundation has 2:30 been a terrific supporter Pat McGovern uh senior uh passed some time ago was 2:35 one of the founding Trustees of this Museum going away way back to Boston where it was initially instanced and and 2:41 obviously moved to the Bay Area some 20 plus years ago so we want to thank them for their support in an ongoing series 2:48 about Ai and The Human Condition so uh without further Ado uh you have um I 2:55 think you're here because you know uh a lot about or you're interest Ed in 3:00 learning more about what's going on uh with AI and The Human Condition and let 3:05 me introduce Fe with a little bit of her background she's the Sequoia professor of computer science at Stanford and the 3:12 Denning co-director of the Stanford Institute for human centered AI uh she 3:17 was the director of Stanford's AI lab and during sabatical was the VP of of um 3:23 Chief scientist of AI and ml uh artificial intelligence machine learning at Google uh and did an immense amount 3:29 of research and that uh stay as well she's also serving on the national AI 3:35 research resource task force which was commissioned by Congress and the white house so please I'd like to welcome uh 3:42 Dr Lee to the 3:48 stage thanks thank you and Tom khil is here to moderate the conversation I had 3:55 the Good Fortune of meeting Tom some long time ago when he was working in the White House of office science technology 4:02 and policy in the Obama Administration he worked with both the Clinton and the Obama Administration has a lot of 4:08 experience in the policy Arena as well as um working very aggressively in the 4:13 national uh nanotechnology initiative and the Brain initiative he's now currently the CEO of Renaissance 4:19 philanthropy which is a new organization focused on the consideration of this new Renaissance which we're living through 4:26 and in many cases creating in the neighborhood so I want to want to thank Tom and F for the program and uh join me 4:33 and welcome them to the stage thank you let me leave you with 4:39 [Applause] your okay everyone has to rush out and 4:45 buy this book get some for your friends and relatives as well it's it's a great 4:50 read um so uh fa we we've got to see how nerdy this audience is um so how many of 4:59 you could explain to someone else how stochastic grading descent and back propagation work ra raise your hand okay 5:06 all right okay great um so uh fa one of the things that you talk about in your 5:12 book is uh a little bit about the history of of AI so I'm wondering if you 5:17 could start with what was going on in 1956 and how long did it take the researchers then to to to figure that 5:24 they'd be able to solve artificial intelligence okay well first of all 5:29 thank you thank you uh Computer History Museum thank you Daniel and uh Tom for 5:34 inviting me I do want to say that happy for those of you who are celebrating lunar uh calendars happy mid-autumn 5:42 festival [Applause] 5:47 today um okay now let's go back to 1956 that's not the dmouth uh Workshop 5:55 was it yes okay I thought that was 1959 okay my memory has faded so um there are 6:02 real historians in this audience I know that so 1956 a steamy summer in uh Dartmouth 6:10 College uh the founding fathers of AI John McCarthy Marvin Minsky Claus 6:17 Shannon who's the fourth person um there's one more person sorry we 6:23 remember this um and uh also u convened a group of computer science scientist 6:30 under I think a uh a small Grant from DARPA right uh to discuss the future uh 6:37 the Computing and that time I think John McCarthy um just newly minted this uh 6:44 field calleded uh artificial intelligence and and they spend the 6:50 workshop in that summer try writing this white paper 6:56 on what artificial intelligence is what would it do how would we solve this 7:01 problem focusing really on reasoning deduct deductive reasoning and and uh 7:08 trying to make machines think like humans answer questions make decisions 7:15 and uh it's been uh quite a journey you know 70ish plus years and uh I we have seen 7:25 ups and downs we have seen real you know you think we're in a hype cycle 7:31 now we had hype Cycles uh in the in the' 70s about expert systems uh really 7:38 starting to see real applications of using first order logic and expert 7:44 systems to to um in in AI that time but 7:49 then that bubble crashed pretty badly because um it didn't deliver at that 7:55 time I think there were magazine covers that talking about robots taking over 8:01 the society 1970s and uh that didn't deliver um the 8:08 funding really drained funding at both uh in Academia as well as in Industry 8:13 drained I think uh um military funding or defense funding was still there but 8:20 some researchers actually shied away from those uh from those funding sources 8:26 so by and large the whole field shrunk and then comes 1990s I would say that there is a quiet 8:35 um Revolution that started to happen in the field of AI the whole public world 8:40 still sees that period as the winter AI winter but I personally think that was 8:46 the that was the early spring where the green shoots exactly the snow hasn't 8:51 totally melted but I think that was driven by first um it really was driven 8:58 in my opinion by statistical modeling which combined with computer programming 9:05 we start calling it machine learning um the field of AI and machine learning found its language and and that language 9:13 through statistics through machine learning start to crack open individual 9:19 Fields like uh uh natural language programming computer vision speech 9:25 recognition and uh and and research start working these uh fields in pretty 9:33 deep ways um personally I entered AI as 9:38 a PhD student at CCH in the year of 2000 so a lot of the public still thinks that 9:45 was the that was the uh winter time but for me two things happened during my PhD 9:52 I think that was defining of my generation of AI researchers one is 9:58 statistical machine learning and that's when a lot of you know um I my first 10:06 class in graduate school literally the first class I walked into was called neuron Network and pattern recognition 10:14 um we read back propagation papers and but we also did support Vector machines 10:20 basion net you know boosting methods and kernel methods and all that that's one 10:25 thing that's happening to us we use these tools to start to look at AI problems like computer vision but 10:32 another thing I think that happened um outside of our Labs outside of Academia 10:39 that came to have a defining role in AI is the internet because uh I think 10:46 Google was founded in 1999 uh or 2000 um the internet start to 10:54 give us data and uh and as 10:59 just to finish as you know and of course there's gpus starting to come in the 11:06 about 10 years later so so things are star to quietly converge and I think by 11:13 um around 2010 to 2012 the the public moment of AI start 11:21 to really happen it's at least in Silicon Valley the public moment started 11:26 to happen when right Google and uh other companies were trying to acquire this 11:33 little startup that probably doesn't even have a name coming out of University of Toronto that won the image 11:40 net Challenge and uh and then since then we we are in the in 11:46 the modern AI the the era of modern AI Rebirth of AI right so a project that 11:54 that you worked on played a very important role in changing people's views about about what was possible uh 12:01 and that was the image net so you you worked with your colleagues to create a 12:06 data set of 50 million photos and labeled them so why did that play such 12:12 an important role um in help thing to jumpstart This Modern Wave of of AI 12:19 right so for those of you who don't know imag that was a a data set project a data set project that was started in 12:25 back in 2006 and took a few years and uh a published in 2009 at the end it in 12:32 2009 it became the biggest data set in AI field it is consisted of 15 million 12:41 um internet images uh human sorted curated and and organized and cataloged 12:48 across 22,000 uh um natural object categories 12:54 and uh image net project um three at immediately after we published image 13:01 that as a open-source data set we engag the research community in this annual 13:07 image net challenge to ask machine learning researchers and computer vision researchers across the globe to 13:15 participate in this annual challenge of what we call object recognition and that 13:21 annual challenge uh began in 2010 and led to the moment in 2012 which 13:29 was a uh the first place winner of that Year's challenge is what now everybody 13:36 knows called Alex net was a work done by University of Toronto researchers 13:41 including Jeff Hinton elas saser um Alex Kushi and uh and that moment is pretty 13:49 symbolic to the world of AI because three fundamental elements of modern AI 13:55 converge for the first time and that was namely new network this is why Tom was 14:02 quizzing you on back propagation that was the that was the mathematical underlying mathematics of neuron network 14:08 uh so so first element is Neuron network uh second element is um um big data 14:16 using image net and the third element is G GPU Computing and at that time it was 14:22 two gpus um you know um and uh the significance of image net 14:29 is um it's kind of trivial today everybody knows AI is driven by data but 14:36 pre-image net people did not believe in data everybody was working on completely 14:41 different paradigms in Ai and with tiny bit of data uh sometimes not even you 14:47 know like handcrafted feature engineering exactly exactly so this very radical idea is I we had was scratch all 14:56 that in the data models with data drop drive high capacity models with 15:01 datadriven uh methods and to drive generalization in AI that was that was 15:10 deeply uh suspicious by many people right and so um so there wasn't this 15:16 view that hey one way to think about these neuron Nets is that they're Universal function approximator and if you give them enough examples they can 15:23 map between the input they can learn a function that will map between the input and the output so that that wasn't of 15:29 the mainstream view no it wasn't I see okay now I thought it was interesting in your book that a lot of your more senior 15:35 colleagues uh were wondering why you were doing this uh so uh so I think this 15:41 is a good good example of if you believe in something you know sometimes you should keep doing it because obviously 15:47 it had a huge impact even if you're not getting the love from your colleagues that that you would like at the time 15:54 yeah but you know look I don't I did write it from a negative point of view I think this is scientific progress is 16:01 that being challenged whether it's your senior colleague Junior colleague your student I'm constantly challenged by my 16:06 students and I probably have 99 stupid ideas um every day maybe once in a while 16:13 one good idea so it was fine I was challenged it was fine because it was a 16:20 untested idea but I guess the flip side of the story is for for especially the 16:25 younger people is just because you're challenged does doesn't mean you should give up so that's the important lesson 16:32 here yeah yeah um so you know now going from 2012 to 16:38 2024 uh what are some of the most important advances that you think we've 16:44 made in the interum in AI right believe or not 2012 is also the 16:51 same year Jennifer daa and her colleagues discover crisper she and I had a conversation that 2012 um it 17:00 turned out you know um two major scientific technological breakthrough came in a so okay so 2012 since then 17:10 it's been 12 years and uh what has happened well several things has 17:16 happened right um so in the field in the in the more research field I think Alex 17:22 net plus image that was a major moment it it really um opened the door to the 17:29 Pioneers including the the technology companies like Google start to doubling 17:34 down on uh on deep learning it was the beginning of deep learning era then I think a public moment came in uh January 17:42 2016 when Alpha go um played the gold Master Lisa do and won um won the 17:51 matches and I think that was the first time that um there was the first time 17:58 public was aware that machines are powerful enough to challenge humans in tasks that 18:06 humans tend to think is deeply um unique to our ability right and uh and also it 18:14 introduced the a new class of algorithm called reinforcement learning you know 18:20 that that in in on top of uh deep learning so that was uh that was a 18:25 moment and and there as this point between 2016 to 18:33 2022 I think it was a gradual increase of just more investments in AI in big 18:41 Tech in um in entrepreneurship there is also we're 18:46 starting to it also coincides with the first glimpse of tech lash um I would 18:53 say Tech Clash for a lot of us happened after kambridge Analytics 18:59 you know 2016 election but it was around the time machine learning bias was being 19:05 called out around the time self-driving car fatality happened the earliest I 19:11 think it's around 2017 MH so we start to have a societal conversation um and and 19:19 tension between excitement of tech but also concerns of tech all this I think 19:26 accumulated in um end of October 2022 when Chad happened 19:34 Chad you know for those of us who are researchers we kind of saw that was 19:41 happening you might be thinking oh she's just bluffing but I'll tell you I'll tell you why because we're in the Hat of 19:48 the co-director of Stanford human Center uh Institute in 2021 we actually founded the world's 19:56 first center for research of foundation models because we saw gpt2 results and 20:03 at that time the public was not aware but the researchers like us realized my 20:08 colleagues percil Leon Chris Bing they realized oh my God this is going to change so we immediately put resources 20:15 to form this Center so when chat GPT happened we were kind of grateful we 20:21 started this but we also were shocked by the medior mediatic rise 20:29 of the attention I think the difference between alphao moment and Chad GPT uh 20:36 moment in terms of public awareness it's not just the number of people is the 20:42 first time AI is that intimately in the hands of individual users Alpha go is 20:50 not in the hands of any user other than you know the The Go Master but Chad GPT 20:56 is at your fingertip and that was an Awakening moment not only 21:03 for every single individual it's also Awakening moment for governments right 21:08 the kind of you know before chpt our Institute had part of our mission is to 21:15 bridge the gap between Tech world and policy world so you being in Washington I I would not 21:22 naturally fly to Washington all the time but I was going to Washington just to to continue the conversation but after chbt 21:30 it was like Washington was just calling us you know um so I think like what's going on exactly so I think really these 21:39 10 years has been the public sees this in 21:44 discrete dots of events we see this as a continuous just just more and more just 21:52 log log plot right right exactly more and more Investments and uh movements yeah yeah so is there still a debate 21:59 within the research Community about whether these large language models are stochastic uh parrots or whether they're 22:07 still or there's actual reasoning going on so what what do you is what do you 22:13 think of that debate I understand why you use the word stochastic C parot because it's specifically coming from a 22:19 paper that is critical of a large language models and I think it's important to recognize we do need to 22:26 criticize these models from different angles both in terms of its ability 22:31 energy consumption its limitations the bias and all this but I would have call 22:37 from a scientific point of view I would use a more neutral tone rather than calling it you know either God or 22:45 parrot it it really is a large model that has so much ability to not only 22:54 pattern match pattern learn but to also do prediction and also to predictions 23:02 with very capable um demonstration of even some 23:09 level of reasoning right because it's able to explain to you what things are 23:15 right um I know that there's just a new release a few days ago 01 I personally 23:21 haven't had time to to test it there it took reasoning to even another step 23:27 further in inference time so I think it is fair to say it does have the pattern 23:34 recognition which some people might call parenting right parting uh ability but 23:40 it also has uh some level of reasoning MH but I'm always so careful especially 23:47 being an educator my responsibility is to be an honest Communicator with the 23:52 public I'm always so careful from hyper hyping up what this reasoning 24:00 is includ including some more hyperbolic extrapolation of you 24:07 know um sension or or Consciousness um so you know what do you 24:14 think is likely to happen over say the next 3 to five years so what what do you think are some of the biggest 24:20 limitations of the systems as they currently exist and what are some of the areas uh that you think we can make real 24:27 progress in in terms of improving their performance right Tom I don't know if 24:32 you're asking narrowly about language models or you're asking about ai ai in 24:38 general yeah so for example there's some people who believe that uh you know we 24:43 can just make an incredible amount of progress by buying more gpus so buying 24:48 two million gpus rather than two gpus uh and you know more data more 24:54 synthetic data right so we you know Transformers attention is all you need we you know so so there are some people 25:01 who believe that that we can just make an incredible amount of improvement by scaling up the technology as it exists 25:07 today and there are other people who say well today's version of AI has these 25:12 fundamental limits and we're going to have to explore new approaches like you know neuros symbolic approaches or 25:18 something like that so where do you do you have like a strong view on on that debate well so first of all all good 25:26 points the truth is I do think we're in a real AI digital Revolution so so the 25:34 next 3 to five years will continue to be very exciting for technology but also 25:40 tension filled for our society including policy uh everything you've asked is 25:46 more on the technology side so first of all I fundamentally believe every point 25:52 in human history the technology and science are limited you know it it we 25:59 can always push the frontier forward for uh personally speaking I'm so super 26:05 excited by spatial intelligence that's Way Beyond language if you look at human and animal intelligence language is only 26:12 one piece of intelligence even if we're looking at advanced intelligence humans have built civilization based on so much 26:20 that's beyond language from you know the construction of the pyramid to the to the um intricate design of machine for 26:28 the first Industrial Revolution the discovery of DNA structures the the the 26:33 creation of C cinematography and and all this a lot of this is built upon spatial 26:40 intelligence that goes beyond language so there are definitely new doors open 26:45 uh other than language um technically speaking um scaling laws for data we're 26:52 still seeing a very healthy evidence of scaling law for dat data but it's also 27:00 very intriguing that we're hearing more and more about um where are we running 27:05 to the limit of data MH especially text based data on the Internet it's very 27:11 likely we're we're possibly running in the limit but where I sit in in uh um 27:17 higher education I also see that there's so many pockets of scientific discovery 27:23 where data haven't even been properly harvested you know from digitization of 27:30 some of these data to modeling of these data so I actually think the next 3 to 27:37 five years we're going to see blossoming of scientific discovery in different fields because of AI ml not just the 27:45 commercialization of large Foundation models uh we're going to see more 27:51 spatial intelligence I'm personally involved in that I'm excited by that uh 27:56 we are also going to see the next 3 to 5 years is not just the years of 28:03 Technology it is also the years of how we deploy these models how we govern these models now that you know here in 28:11 our home state California there is AI bills being discussed right and uh 28:18 personally I'm both supportive of safety measures and policy measures but also 28:25 I'm concerned about you know even while intended um bills that might have 28:32 unintended negative consequence to the to the you know scientific and uh open- 28:38 Source community so all this will play out in the next 3 to five years for sure 28:44 yeah so I definitely want to come back to the policy issues but I I want to maybe have you describe for the audience 28:50 a little more about what you mean by spatial intelligence so what does it 28:55 mean for a computer to be able to see do and learn um and what are how would we know 29:01 whether we were making progress uh in spatial intelligence so you know one of your uh colleagues at Stanford uh 29:08 Chelsea Finn said you know we're still very far away from being able to have a robot show up at a house uh that it's 29:15 never seen before and make breakfast for example very far I I can't wait but it's 29:20 very far so I was just um this audience is so 29:26 dark Tom and I cannot see show of hand so I won't ask questions but 29:32 uh if you CH Trace back the development of human language of course this is 29:39 still a scientific study area but roughly the earliest protol language 29:46 moment happened in the very early ancestor of humans about one to two 29:52 million years ago that's the earliest you can trace Trace back a lot of people say language is developed within the the 30:00 the language we use today is within the the last 300,000 years but if you trace 30:08 back the ability to see space the 3D 30:13 World to understand what's going on to see obstacles to see food to see how you 30:19 navigate to reason about this it traces back to 540 million years ago that's 30:26 when the animal world underwater first developed light sensors and with that 30:32 ability perception began with that when perception began animals start to move 30:39 in an intentive way before that they're just floating around they can't they can they were probably touching a few things 30:47 because there was early tactile sensors but it was very very chill but once you 30:53 can literally speaking once you can see did get that from your 30:59 kids yes once you can well I work with young students they um once you can see 31:07 you you start to develop spatial intelligence you start to plan your life you start to see food you start to hide 31:15 away from being someone else's food and that evolutionary process of intelligence just began so spatial 31:23 intelligence summarizes all this ability in today's language I would say is the 31:29 ability to understand reason generate and interact with 3D worlds now we 31:37 liveing simultaneously physical world as well as digital worlds so this spatial 31:43 intelligence applies to both physical and digital worlds so which ties back to 31:49 if you ever want a robot that can come to your house to make breakfast one of 31:55 the most important thing the robot needs to have is icial intelligence because the robot needs to know where's your 32:00 fridge where's your stove where's the egg how do you you know crack open an egg and the and put it in the pen and 32:07 and all this all this is part of spatial intelligence mhm got it 32:17 um why is that so [Laughter] 32:23 funny so uh so there's a lot lot of discussion about this concept called artificial 32:30 general intelligence and I'm wondering whether you think that is a useful concept or not so what people usually 32:36 mean by that is that it will be possible to do maybe let's side the set aside 32:43 robots for a while because that's a little farther off but that in a if you 32:48 imagined a sort of a remote worker uh that you would be able to have an AI that does sort of every useful economic 32:56 economically useful thing that a human does uh we would be able to do with uh some AGI first of all do you think 33:04 that's a useful concept uh uh number one and and number two do you think uh you know some people 33:11 are saying oh that's going to happen in three years do you think that's sort of wildly optimistic right that's a good question 33:17 it's also you know I have to admit that uh it's such a Silicon Valley question 33:23 MH um that's where we are f f i know 33:29 um you know sometimes in my head I have dialogues with the pioneers of AI John 33:36 McCarthy you know Marvin Minsky Ramen Raman har also you know Alan touring he 33:44 probably would not have called himself the pioneer of AI cuz when he was daring 33:50 Humanity with the question of thinking machines eventually translated to touring test he wasn't thinking about 33:56 the words a I yet it wasn't invented but when I was having dialogue with these 34:02 Giants I think that their definition of AI would be very similar is that General 34:09 capability of intelligence so if they C 34:15 AI having that in mind it is hard for me as a scholar to differentiate the word 34:21 AI from AI mhm because I think they're deeply overlapping right and if you look 34:27 at when AGI as a term came about it was 34:32 probably not even 10 years ago it came out of more the industry marketing World 34:40 MH I there's nothing bad about it but from a academic scientific technological 34:46 researcher educator point of view the the the some of you who read my book 34:51 knows I I I use this word North Star a lot as a scientist we chase the hardest 34:58 problem that we might never solve in our lifes time but they Inspire us and I think the Northstar of AI as a field is 35:06 always that General capability so what do I think about the word 35:11 AGI nobody asked me when they invented that word I it's fine but I the AI that 35:19 as a field that we we love we we still believe in is largely overlapping with 35:27 the this definition now 3 years are we going to achieve that um if I mean in 35:35 front of a venture capitalist I'll say yes of course but you're not and you're not so 35:44 I I think I think we need to be responsible you know what does that mean 35:51 would machine surpass human in important tasks we have already done some some of 35:58 that right you know like 20 the DARPA Grand Challenge of self 36:05 driving car was 2006 right 2006 my colleagues abasan thr 36:14 and his team drove let a car drive 138 miles in the desert of Nevada right and 36:22 that was that was a incredible capability and then we have ma that can 36:28 translate tens of languages that's just superum we have we have so many tasks 36:35 that already surpassed Alpha fold is it yeah Alpha fold Alpha go you know even 36:40 image that that's 1,000 Arcane classes of objects like 36:47 Star nose mole or you know so many species of dogs and these 36:54 are all superhuman capabilities um so so I think we have achieved some we will 37:00 continue to achieve some but that I I think without a clear definition if 37:09 you're if the holistic of Being Human and being as intelligent as human as 37:15 being as intricately and and complex as human in three years I do not believe 37:23 mhm okay um so let's talk a little bit about what you're doing at Stanford uh with 37:30 this initiative on human centered AI first of all what what do you mean by human centered AI yeah that's a great question I think 37:37 human Center AI at this point for me is a frame framework to think 37:42 about my yours AI work because AI is 37:47 made by people is used by people will impact people's lives and what is a 37:54 guiding framework to think about this technology I I came out I I think in March 2018 I was 38:02 still a chief scientist at Google I wrote a New York Times article call 38:07 putting the stick on the ground and calling this framework human Center AI precisely because I was so inspired by 38:14 my work at Google I had the chance to interface with so many businesses from 38:21 Individual developers in Japan cucumber Farmers using AI all the way to 4 50 38:28 companies hoping to use AI to revolutionize their their entire business model I realized this 38:36 technology is bigger than anything I had imagined it's going to impact our lives 38:42 and businesses and and World in such profound way and that realization 38:47 actually send a chill down my spine it is scary to think that way it is scary 38:53 to realize a tool can be that powerful and we better think about the 38:58 implication and to me that deep implication has to be grounded in the 39:04 human implication and once I thought about that my colleagues and I at 39:09 Stanford put that stick on the ground and say we need to approach AI with the human Center framework now at Stanford a 39:17 uh hii we think about the human impact of AI in three concentric Rings individual 39:26 community and Society I'll give you an example individual really has to do with 39:31 every single individual matters how does this technology um you know impact you 39:38 or benefit you you know if you're artist how are you using that to augment it or 39:44 is it taking away your intellectual property if you're a patient is this technology making you um heal better 39:52 without taking away your human dignity if you're a student how are you learning 39:58 you know uh this uh anything you're interested through this of through the help of this technology so there's 40:04 individual impact then there's Community impact right how is AI how can AI be 40:11 used as a tool to help communities that are underresourced for example AI plus 40:17 tele medicine is a deeply deeply um good use case for communities 40:25 that don't have access to hospitals and and enough doctors in the meantime can 40:31 biasing AI impact one Community more than the other we're seeing that already 40:37 so that's the the the the community uh uh aspect then we have Society right 40:44 today we cannot stop talking about ai's impact in November our Democratic 40:51 process how is AI and deep fake and and information war or going to change all 40:57 this we cannot stop talking about jobs MH you know from software engineering to 41:02 to um truck drivers to Radiologists in in AI is impacting the whole society so 41:12 all these are are human issues so math is clean but human world is messy and AI 41:20 has exited from only that clean math clean programming world to a messy human 41:28 world yeah somebody once said technology is easy humans are hard yes especially 41:33 little ones yeah what are some of the potential 41:39 benefits and applications of AI like ambient Health that that you're most excited about right thank you for 41:45 queuing that because it's chapter 10 of my book but there really it 41:52 is um really it is um boundless I personally I got very inspired by just 42:00 spending endless hours sitting in Primary Care in EM mergency Department 42:06 outside of uh uh surgery rooms in Ambulatory Care settings because I have 42:12 a alien parent who is deeply deeply ill for so many decades I take care of my 42:17 mom and I realized our our our Health Care system 42:24 is full of humans taking care of hum humans but all these humans health care 42:30 workers from nurses to doctors to to um 42:35 caretakers they don't have enough time and they don't have enough help and so 42:40 am ambient intelligence in health care setting really uh came from a 42:46 collaboration between me and my collaborators in Stanford Medical School wanting to use technology to provide an 42:54 extra pair of eyes and ears to help doctors and nurses and caretakers to to 43:01 make sure our patients are safe or their their situation is not deteriorating 43:06 rapidly for example I I don't even want to see a show off hand it would just 43:11 make you make me sad but so many of you have personal family members and friends 43:17 who have fell and that's a deeply deeply painful and costly injury especially for 43:24 elderly but how do you predict that how do you alert that how do you help them 43:29 how do you help our elders or or patients that you it's hard to have a 43:36 human to be watching 24 hours but computers and cameras can help um or you 43:44 know um ambul uh ambient intelligence can can help uh monitor the the the the 43:51 a a COPD patient in terms of the way their their conditions are 43:57 and alert um doctors when the oxygen has changed rapidly or some situation has 44:04 changed so that's just one example of AI being almost a guardian angel to be 44:12 augmenting our caretakers to take care of people but we're see exciting use 44:18 cases in education personalized the learning right is so obvious that AI can 44:26 um can be a a tutor can be a TA can be a a teach assistant to our teachers in 44:33 different learning environments I think one of your former grad graduate students Andre is is working on that yes 44:39 I exactly yeah I just saw him a few days ago yes but there are a lot of use cases 44:45 in agriculture believe or not I had a former student years ago before deep learning 44:52 re uh Revolution started uh or co-founded a startup using computer 44:58 vision technology to detect weeds in fields so that it can um you know um it 45:05 can keep the crops healthier you know I've heard salmon Farmers using AI to 45:13 help farming Salmons you know the the use cases of positive uh uses of AI is 45:19 just countless right and so how how can we prepare more people to have both a 45:25 computational back background but also be a domain expert for example in the same way that your colleague Daphne 45:32 Culler has a machine learning background but she's also learned a lot about Healthcare and and Drug Discovery 45:38 because it seems to me that the people who have a foot in both worlds both the computational expertise and domain 45:45 expertise are going to be in a position to help identify some more of these compelling use cases that's a great 45:51 Point Tom um I deeply deeply believe in interdisciplinary and multi disciplin 45:58 disciplinary approach you know even even if you don't want to get a PhD at the 46:04 intersection of I personally got it at the intersection of AI and computational 46:09 Neuroscience or or intersection of AI and com computational biology or 46:14 intersection of AI and political science even if you don't go as deep as a PhD in 46:22 all your journey as a student there is a lot of value to embrace both the 46:28 Computing the stem Fields as well as your areas of passion um whether it's 46:34 biology or art or or uh policy or you know chemistry and so on so for students 46:43 out there if you're in school if you're thinking about college if you're in college I do think what Tom said is 46:49 really valuable is to embrace that interdisciplinarity I think zooming out 46:55 a little bit um you know AI is the new language for computing I I have been uh 47:02 quoted in saying that anywhere there's a chip there is or will be AI as small as 47:09 a light bulb which has a chip in it there will be AI as big as robots and 47:15 cars and and whatever so given how important this technology is I do 47:22 believe in um in um educating our our kids young educating our students from 47:30 all background all walks of life educate our public with this uh with this 47:37 technology at least if you if not coding at least know what this is but last but 47:42 not the least I also think even if your passion is not in Computing computer 47:48 programming or in in the technical details of AI if your passion is in arts 47:54 if your passion is in political science in law in medicine there is a place for 48:00 you because because it's the domain experts who will be using AI to make a 48:07 difference in your domain so don't be afraid of embracing it from your you 48:14 know perspective and use it to make a positive difference yeah um which of the 48:22 you know there's people list a lot of potential risks so you've already talked about some of them you know people are 48:29 going to lose their jobs uh you people will use deep fakes to disrupt 48:34 elections they'll be we'll be reinforcing existing biases um you know some people have more 48:42 speculative concerns uh like uh this idea of instrumental convergence you 48:48 know so if if a if we give an AI system a a uh an objective function of trying 48:55 to achieve some goal then it's going to have a sub goals wanting to make copies of itself and have access to more 49:02 computational power wh which of the uh the risks that people talk about do you 49:07 take the most seriously yeah look there are many risks 49:13 every technology every powerful technology has created harm has been 49:19 used for harm and even well intended has had unintended consequences and we have 49:26 to face that but if you are forcing me to pick a risk as an educator I would 49:33 say the biggest risk of embracing the new era of AI is 49:39 ignorance is it's not just the the basic ignorance of I don't know how to spell 49:45 the word AI it's not it's even some deeply learned knowledgeable people when 49:52 they are ignoring details nuances and 49:58 are communicating AI in hyperbolic ways 50:03 that is a risk to the society but 50:09 ignorance you know we know if if we're too ignorant of this technology we miss 50:15 the opportunity of using it to our benefit if we're ignorant of this 50:20 technology we cannot call out or recognize the actual risks if we are 50:27 spreading the ignorant um message we also are misleading the public or 50:33 policymaking so the the a lot of these um a lot of the root of these these 50:41 issues are actually stemmed in the lack of understanding so that we're not 50:47 assessing risks right or we're hyperbolically communicating it or we 50:53 just completely just missed it so so so that's how I would put it and and what 50:58 are some examples of that that you see now where people are are saying things that you think are to are totally off 51:04 base well okay so I think anybody who 51:10 says AI is all good as if you know you can swap in this word technology is all 51:17 good it's only good it can never do bad I think that's that's a ignorant 51:22 ignorance of the past right we look at humans history with tools every tool has 51:29 been used in harmful ways you know so we have to recognize if your data set is 51:35 biased you're going to have really bad Downstream um uh impact in terms of 51:41 fairness if you uh if you are making you know um if you don't know where how the 51:49 the the the AI is made you might actually be so ignorant and be working 51:55 with deep fakes without your knowledge so these are all not good but there's also another 52:02 swing which is this is such a demon that 52:08 it's existential crisis it is going to proliferate itself replicates itself 52:15 turn off I don't know uh Power grids and and all that also I think that is 52:22 hyperbolic and it ignores that AI is not an AB ract concept it's actually lives 52:29 in physical systems even if it's virtual software digital programs it lives in 52:35 physical system it lives in data centers it lives in electric grids it lives in a 52:42 human society and there are so many things that is Tethered and and and um 52:49 and contextualized that uh um that it's you know that hyperbolic assumption 52:56 right is but you know some of the people raising some of these more speculative concerns are people like Jeffrey Hinton who you 53:04 know presumably understand the technology so so why do you think that there are so why why do you think that 53:10 there are people who have been deeply involved in the technology who've gotten more concerned over the last couple 53:16 years so first Jeff I'm really really respect je I knew Jeff since I was a graduate student um actually last year I 53:24 was in Toronto I had a public uh discussion with Jeff Hinton um on this 53:29 very issue and it's on YouTube I I think it's one of the very few times that Jeff 53:34 and I uh or Jeff and anybody had a public discourse about this if you 53:40 listen to him carefully he is concerned he's also 53:46 calling out the potential um risks 53:51 right but you know there is also a layer of 53:57 amplification of his concern and and we have to dissociate I I totally respect 54:04 that discussion with Jeff and I agree with him irresponsible use of this 54:09 technology would lead to really dire consequences and he has his version of 54:16 irresponsible use I have my own version of irresponsible use yeah I think also 54:21 you know I respect every individual for calling out these risks in their own 54:27 ways but I also want to be a responsible communicator and educator I want to let 54:34 the public know that it is still our human Collective individual 54:41 responsibility to harness and govern this uh technology and there is 54:47 absolutely it's not only there is time it's absolutely there's time there's also you know there's just everything we 54:56 we it's in our hands and we shouldn't give that up right so you talked about 55:02 governance um and you've played a very important role in getting this idea of a national research Cloud on the political 55:09 agenda um if you did have an opportunity to uh brief the next president and they 55:16 said uh fay F what should I do uh you know what what advice would you give the 55:21 next president about the most important things that the uh that the US government could do to try to promote 55:27 the benefits but also understand and manage the risks right um I probably will say the 55:34 same thing as I said to President Biden last June and also earlier this year I 55:39 met him at the State of the Union uh Speech is that I believe that our nation 55:45 needs a very healthy AI ecosystem and when I say it's a ecosystem it includes 55:53 um um public sector Academia uh entrepreneurship We Now call Little 55:59 techs as well as big tech technology and uh our 56:04 country is a very strong democracy and we believe in the value of this 56:10 democracy and I believe that having a healthy AI ecosystem plays to our 56:17 strength and can have a very positive role and but what's what's something we 56:22 could do to try to public investment yeah Public public investment is really really important now that I am partially 56:29 in the private sector it makes me even more uh convinced that the discrepancy 56:36 between private sector investment and public sector investment of AI is just 56:41 so huge right like my Stanford a my Stanford computer vision lab shared with 56:49 a couple of other faculty has zero h100 mhm it also has zero A1 100 we're 56:57 still using a6000 and other older chips MH and uh and yet the the the the big 57:05 Tech has you know like you said hundreds of thousands and millions of chips and I think that public sector investment is 57:14 where The Gardens of ideas the flowers Blossom we wouldn't be here today and I 57:21 wouldn't be here if it were not to public sector and also I mean when did Jeffrey Hinton start working on 57:28 artificial neural that's how many decades ago yeah when he was in CMU or maybe even earlier Right image that was 57:35 from uh from uh public sector you know and the next three to five years we talk 57:40 about the scientific discovery we're going to see exciting things coming out a lot of them will come out of public 57:47 sector and also the best thing that come out of public sector Academia guess what 57:52 are people exactly so we need to invest public sector yeah great well uh we have 58:00 a very smart audience so I'm sure you've come up with lots of really good questions 58:06 um let's see uh one was for your new company uh how will you 58:14 collect enough data to build a spatial map of the world to support real-time localization so you you might want to 58:21 address the premise of that question but clearly you know data is going to be you're not going to be able to make 58:27 progress on spatial intelligence in the absence of data so maybe you could address that right we are not publicly 58:34 discussing the details yet because we're not ready when we're ready we will I'm a 58:39 little amused that this person already knows where we're building uh that's their version of story I'm not 58:46 commenting on that but you're right um AI is driven by data it's important our 58:51 company spatial intelligence is absolutely pixel based right so a lot of 58:56 pixel data is will be driving this technology right here's a great question 59:02 um from Amy uh and this relates to something that you worked on uh a AI for 59:09 all but she says um I'm a 12-year-old Middle School 59:15 student what can we do to encourage more girls to study Ai and better prepare for the AI 59:21 era great question um I I think every 12 59:28 year-old should be encouraged to embrace this no matter if you're a girl a boy you live 59:36 in rural world you live in Silicon Valley this is this is if you love it 59:43 embrace it and for you know for for Amy as well as just thinking about when I 59:49 was 12y old um there was no AI well at least I didn't know there was AI um I 59:57 loved math I loved physics the one thing that I'm grateful today that my parents 1:00:05 and my teachers did to me and I will say it to Amy and all the students out there 1:00:11 is Follow Your Passion follow your curiosity and uh be resilient do not if 1:00:19 there are negative voices just tune it out there are plenty of people from your 1:00:24 parents to your teacher to your friends to to your role models are out there to 1:00:30 support you and uh just keep doing it keep 1:00:35 going uh what's the most important human problem to solve with spatial intelligence Beyond making 1:00:41 breakfast lunch no just Kidd um spatial intelligence really can 1:00:51 power many things from creating to design how many of you want to just have 1:00:59 a app that you can just imagine all the furniture you know rearrangement um to robotics to 1:01:07 arvr to you know um specific areas whether it's teaching learning Health 1:01:15 Care you know Factory manufacturing and all that so so it really is um a deeply 1:01:25 prevailing horizontal technology that can impact all all of these 1:01:30 areas so we have a question about the combination of small models and AR 1:01:37 glasses so is is that something that uh that You' thought about I'm definitely 1:01:42 excited by the New Media I know this is early right like again we're in Silicon 1:01:48 Valley I'm sure many of you have stayed up late to buy the The Vision Pro so I 1:01:54 was very excited actually apple called it spatial Computing cuz at that time I 1:01:59 was already thinking about spatial intelligence for many years and and I was like yes because spatial Computing 1:02:06 needs spatial intelligence so but just this form factor of um glasses or I I 1:02:15 really believe in glass possibly headsets but glass are very exciting to me um and uh the edge compute uh or or 1:02:24 small models it's very exciting but um small models can can be useful not just 1:02:31 for glasses and and headsets it really is very powerful for uh Edge compute 1:02:38 whether it's smart devices robots especially home robots you cannot carry 1:02:43 a server in the back trunk right so uh so there's a lot of use for small models 1:02:49 yeah I'm very interested in the role that uh multimodal models and smart 1:02:54 glasses could play uh in terms of Workforce Development yes so there are a lot of you know we don't 1:03:00 have enough electricians so you could imagine that sort of earbuds Ai and 1:03:07 smart glasses abut providing sort of just in time just enough training as part of a you know an apprenticeship 1:03:14 program um uh what do you what can we do what 1:03:20 can the research Community do what can companies do to address the fact that uh other languages are other than English 1:03:27 are underrepresented right so this is a great question this goes to data bias 1:03:34 and all this first of all I do think when I say public sector investment in 1:03:39 AI I think every country should have public sector investment that itself is 1:03:46 related to the local culture local language you know so so from that point 1:03:52 of view it is individual researchers it's important individual researchers pay attention but it's also 1:03:58 important that governments and uh and big organizations that can deploy large 1:04:05 amount of Resources pay attention to this it it's absolutely true that uh 1:04:10 English is dominating and we should be aware of that and uh 1:04:16 um this goes back to my point of public sector investment even in this country 1:04:23 right is that I'm sure we have incredible researchers students out 1:04:28 there thinking about other languages but right now they're lacking data sets 1:04:34 they're lacking compute resources and uh we need to fix 1:04:39 that um so there were some kind of philosophical questions uh from the 1:04:46 audience um and I'm I'm wondering uh you know if you if you can 1:04:51 talk about what sort of effort you've made to engage people in the humanities and the and the social sciences yeah at 1:05:00 at at Stanford and what are what are some examples of insights that that they've been able to provide that have been sort of interesting to you as as a 1:05:07 computer scientist actually this is the most fun part of my last five years 1:05:13 establishing and co-running this institute is really Reaching Across the 1:05:19 campus Stanford particularly has about I think eight schools from school of 1:05:26 the law school the business school the medical school the the now the sustainability School the the humanities 1:05:33 and uh Natural Sciences School uh the engineering school just just talking to 1:05:39 colleagues and reaching out to students and researchers and Scholars across the campus is extremely fun and Illuminating 1:05:48 what what have I learned for example I um you know um talking to my 1:05:56 um talking to my Humanities colleagues really opened up my understanding of 1:06:02 human expression and creativity and what does it mean how do we think about ai's 1:06:08 relationship with people who are deeply creators you know especially when Chad 1:06:14 GPT and Sora came out you know from Hollywood's uh writer strike all the way 1:06:20 to the the concern about the voices the the the the the artist the the um 1:06:28 individual um copyrights uh all the way to artists were at the avagard of 1:06:35 embracing this tool it's just so complex it it really I I didn't have a formal um 1:06:43 education to even wrap this around my head and they teach me in thinking about that one thing I did learn again talking 1:06:50 to this audience probably deeply te technical I think it's really important 1:06:57 technologists listen and reach out to humanist and and social scientists and and also in your own work 1:07:04 setting it could be you know legal it could be you know um product it could be 1:07:11 marketing it could be many different functions uh because technology doesn't 1:07:18 live in a vacuum Tech you know it takes a complex human effort to make 1:07:25 technology Bel benevolent and good and just going in with that humility and 1:07:32 respect and and giving the other side the dignity they deserve is really the 1:07:38 the the most fundamental thing we could do to form these 1:07:43 Bridges um how important is it that you think we make uh progress in areas like 1:07:49 explainable and interpretable AI That's a great question I think by in 1:07:56 large it is important but again I think it's important we we go a little nuanced 1:08:01 for example even explainability has different layers um for example 1:08:08 everybody knows Tylenol is good for fever and headache explain to me the molecular pathway of 1:08:15 Tylenol in fact even today even scientists don't know all the details 1:08:21 yet you will never say Tylenol is a inex explainable drug is because there is a 1:08:29 whole system around drug development around regulatory measures around the 1:08:34 the approval process of a drug that has enough of the the the the the 1:08:41 explanation that that made you or most of the public convinced and and feel 1:08:47 trust feel trusting so that's one way of explainability another way of 1:08:53 explainability is um uh for example you know especially you Tom drove from 1:08:58 Lafayette over here Google if you put in Google map it'll give you choices right 1:09:05 you know this route you pay but it's 4 minutes faster this route is syic I 1:09:11 don't know if there's any syic route from LA to Mountain View right now but 1:09:18 honestly that doesn't explain to you the algorithm of point A to point B but as a 1:09:24 human user you feel there is enough explainability in terms of in terms of 1:09:31 your choices and again back to Medicine we we hardly any of us were not doctors 1:09:37 understand treatment yet your doctor used certain kind of human language to explain to you what this treatment is 1:09:46 I'm using this example I'm spending time to use this example to to to kind of 1:09:52 share with you that it's important to think about the case use case it's also 1:09:59 important to think about the definition of explainability and and that definition the particular definition and 1:10:05 particular use case really need to match sometimes we don't need the mechanistic 1:10:12 molecular pathway level explainability sometimes we need a different 1:10:18 explainability and we so so to answer your question it is important but it depends on the use case it's important 1:10:25 in different ways uh well we have a lot of people in the audience who would like to know more 1:10:32 details about your business plan for World Labs but we'll we'll skip those questions um so they're the VCS in the 1:10:39 audience yeah um so there's question you know you 1:10:46 you mentioned that in addition to studying AI you also studied Neuroscience um and so there have been 1:10:54 some people who are interested the question uh you know what can AI learn from Neuroscience so the you know 1:11:01 convolutional neural networks were at least sort of loosely inspired by how 1:11:06 the you know the human visual system works uh you know people have looked at 1:11:12 the uh dopamine reward circuit and that's been a source of inspiration for 1:11:17 reinforcement learning right um are there other areas where you see you know 1:11:23 potential collaboration between uh neuroscience and and AI clearly Mother Nature has figured out something about 1:11:30 low power Computing because our brain only uses 20 watts right exactly dimer the any light bulb in this room so you 1:11:38 know when we founded Stanford Hai one of the three major research 1:11:44 pillars is neuroscience the in the cross disciplinary collaboration between 1:11:51 neuroscience and AI to me is foundational to the advance of our field 1:11:57 and also to the advance of both Fields going forward and I've got I'm very very 1:12:03 uh lucky to work with colleagues like Seria gangully and Mike Frank and Noah 1:12:10 Goodman a lot of colleagues at um at Stanford are at the Forefront of this 1:12:17 interdisciplinary research right for example um um young children's 1:12:24 development you know early days kids uh very young children do a lot of 1:12:30 curiosity driven um uh learning how does that translate to um AI you know AI 1:12:38 systems right that's one in Inspiration we also know that um that backprop is a 1:12:45 very very simplistic translation of what's going on between the two neurons 1:12:51 in our brain in addition to synaptic connections there's a lot of dendritic 1:12:57 connections that are actually deeply electrical chemical and very nuanced no 1:13:03 machine learning algorithm today has incorporated any of these Complicated 1:13:08 new uh you know interesting uh uh synaptic and uh neuronal communication 1:13:15 channels and the flip side is totally true our neuroscientist colleagues 1:13:21 whether they're using animal models or cellular models are collecting a massive 1:13:26 amount of data and using machine learning is or AI is a fascinating way 1:13:33 of helping them to discover their their science and last but not least um even 1:13:40 my lab I I find it fascinating that now we're collaborating with psychologists 1:13:46 and using um non-invasive electrical um 1:13:51 electrical um uh EG waves from humans to Drive robots you know that's completely 1:13:58 non-invasive ways so so the point is these two Fields have a lot of uh uh 1:14:04 cross pollination and to me is one of the most exciting area of interdisciplinary research right right 1:14:12 well fa we have enough questions to keep you here until 10 uh but uh uh please 1:14:18 join me and and thanking fa for a terrific interview thank you 1:14:30 and remember the world's I see yeah that's for sure so thank you both very 1:14:36 very much again this is a terrific there's so many takeaways um 1:14:42 that I have personally um the public support uh is really one that's so so 1:14:49 fundamental I think and Tom you had a lot to do with some of those things in in in government and um 1:14:55 I think without it we're we're going to be at a loss you know at at this stage because so much of this is tied to the 1:15:02 societal implications the person that you were looking for the fourth person oh yes at 1:15:08 the Dartmouth conference was Nathaniel Rochester yes who who was working at IBM 1:15:15 at the time and I wanted to tell all of you who haven't been in the exhibits 1:15:20 lately there's a holth machine downstairs which is a machine that Herman holth built as a result of a 1:15:27 public call to solve a problem that the US government had which was to codify 1:15:34 the census from the 1890 era because the techniques by which the the addition was 1:15:41 done um would not allow for the census to be counted in due time as a result of 1:15:49 the population growth and through the combination of public call 1:15:55 and private initiatives um he came up with a machine that was based upon a punch card which 1:16:01 was designed and built for the jacard Looms in the industrial revolution to store the patterns by which all these 1:16:08 fabrics and and drapes were considered so we we just go back to whether it's 1:16:13 DARPA funding or whatever there there's there needs to be a societal call for this and if not now I don't know when so 1:16:19 you laid out some wonderful thoughts for everyone on stage i' like to thank you both again and please Jo join me one 1:16:25 more time and then don't go away thank you Computer History Museum 150K subscribers Videos About Facebook Twitter Instagram 5 Comments rongmaw lin Add a comment... @harshavardhanvenkatasaikot6861 8 days ago All the best god mother 4 Reply @rodolfo1110 7 days ago Frankly, it is unusual the capacity of a cientist to explain processes, concepts and projects with such clarity and sobriety. Something to learn and to enjoy. 2 Reply @EquipteHarry 2 days ago Wilson Joseph Young Susan Smith Timothy Reply @soundodyssey3914 6 days ago Very interesting. Thanks for sharing. With all the media attention around AI, it is incomprehensible that this interview only has 1,657 views... 1 Reply @williamjmccartan8879 6 days ago Thank you very much for sharing this conversation with us, Fei-Fei rocks 2 Reply