This video shows a curated list of the with a , , and . The videos include great commentary on the future of AI by many important people in the field such as Fei-Fei Li, Luis Lamb, Gary Marcus, and more. latest breakthroughs in AI by release date clear video explanation link to a more in-depth article code Enjoy the video! Chapters: Hey! Tap the Thumbs Up button and Subscribe. You'll learn a lot of cool stuff in 2021, I promise. 0:00 2020, A year in review 0:28 Where do you want AI to go? 9:06 References: Complete article: https://github.com/louisfb01/Best_AI_paper_2020 GitHub repo: https://github.com/louisfb01/Best_AI_paper_2020 Follow me for more AI content: Instagram: https://www.instagram.com/whats_ai/ LinkedIn: https://www.linkedin.com/in/whats-ai/ Twitter: https://twitter.com/Whats_AI Facebook: https://www.facebook.com/whats.artifi... Medium: https://medium.com/@whats_ai Youtube: https://www.youtube.com/channel/UCUzGQrN-lyyc0BWTYoJM_Sg/join Video Transcript 00:00 where do you want ai to go what what 00:02 would make you happy 00:03 what is the objective here the objective 00:05 function for those of us who are 00:06 building ai 00:08 um or trying to inform it from other 00:10 fields 00:11 what would count in success where do you 00:12 want to take it to 00:17 [Music] 00:50 [Music] 00:57 [Music] 01:18 [Music] 01:43 [Music] 01:54 [Music] 02:39 [Music] 03:24 [Music] 03:30 [Music] 03:51 [Music] 04:16 [Music] 04:29 [Music] 04:50 but it's a trick no no it's much more 04:52 than that uh whosoever be he were they 04:54 shall have the power 04:57 whatever man it's a trick please be my 05:00 guest 05:02 come on really yeah oh this is gonna be 05:05 beautiful clint you've had a tough week 05:07 we won't hold it against you if you 05:08 can't get it up you may have seen this 05:10 before 05:10 right yeah all right 05:39 [Music] 06:24 [Music] 06:30 [Music] 06:51 [Music] 07:16 [Music] 07:27 [Music] 08:13 [Music] 08:17 researchers and artists around the world 08:19 have been using style game 2 to do all 08:20 kinds of interesting work 08:22 at nvidia we've been pushing the 08:23 frontier of using gans to synthesize 08:25 extremely realistic images 08:28 the catch is that you need to train them 08:30 on extremely large quantities of data 08:32 so to tackle this challenge we've 08:33 invented a new approach for stylegan 2 08:35 that we call adaptive discriminator 08:37 augmentation or ada 08:38 this lets us reduce the number of 08:40 training images by a factor of 10 a 08:42 factor of 20 or more while still getting 08:44 great results 08:56 [Music] 09:06 as a scientist i want to 09:10 push the scientific knowledge and 09:12 principles of 09:13 ai further and further and the first 09:15 thing is start with 09:17 some really fundamental laws and 09:21 principles of 09:22 ai i keep saying that i still feel our 09:24 ai 09:25 era is pre-newtonian physics that we are 09:28 still studying phenomenology 09:30 and engineering but there is going to be 09:34 a moment 09:34 or a set of moments where we're starting 09:37 to understand 09:38 the principles of intelligence and that 09:41 is 09:42 the scientists in me we're in the head 09:45 of a citizen i guess 09:47 and directing stanford's human center ai 09:51 institute 09:52 i want this to be a technology that can 09:55 an idealistic way really better human 09:58 conditions 09:58 right it's so profound it's so 10:02 horizontal 10:03 it's so um it has so much human and 10:07 societal impact 10:10 it can be very very bad and can be very 10:12 very good 10:13 so there i would like to see a 10:16 framework of this technology being 10:19 developed and deployed 10:21 in the most benevolent way 10:25 what comes to mind very often so i hang 10:27 out because of the family i'm born into 10:30 with people who work at state 10:32 departments who deal with international 10:34 laws military laws etc 10:36 and there's a there's a there's a big 10:38 concern here with militarization of ai 10:40 right 10:41 danny just mentioned human decision 10:43 making humans in the loop why people are 10:45 trying to negotiate 10:46 treaties limiting should we limit should 10:49 they always be a human 10:50 in the loop when we when we build 10:52 dangerous machines 10:54 you know kill a robot as well as is 10:56 happening as we all know 10:58 in the defense world and and as will 11:01 happen so what about the growing threats 11:03 of militarization of ai which is ongoing 11:06 and what should we 11:07 uh should we do anything about it or 11:10 pessimistic can we do anything about it 11:12 or is that 11:15 genie out of the box i want the costs 11:18 and the benefits of ai to be 11:21 evenly distributed across society both 11:24 in the united states 11:26 and globally and i want the public to 11:29 trust that that's what's being done 11:31 and i think that's impossible without 11:34 changes to law 11:36 just impossible um i like one of the 11:38 sayings of michael raving 11:40 from harvard and hebrew university said 11:42 that it's great that 11:44 uh computer science has not been around 11:46 for 2000 years 11:48 and we are at a stage where very very 11:50 important results 11:51 occur in front of our eyes i also like a 11:54 saying by 11:56 alan turing in his mind paper where he 11:58 said we can only see a short distance 12:01 ahead 12:02 but we can see plenty there that needs 12:04 to be done 12:05 and as fei-fei said as scientists i want 12:08 ai to advance but since ai is having an 12:11 impact 12:12 as big as physics had in the 20th 12:15 century 12:15 engineering heading and 20th century all 12:18 the ethical issues 12:19 all the biases and all the social 12:21 implications that margaret and others 12:23 and here in francesca 12:25 have been studying they are key as 12:28 responsibility of our 12:29 ourselves as scientists and in terms of 12:32 uh 12:32 technical technically speaking what we 12:35 are trying to do 12:36 is to conciliate traditions of ai so 12:39 that we cannot see 12:41 and as you said gary before you've been 12:43 saying since the 12:44 late 90s we have to converge we have to 12:47 look for convergency 12:49 you cited the only colonial cited other 12:51 prominent scientists today 12:53 we need a way of seeing that several 12:56 techniques can contribute to this 12:57 endeavor of making ai 12:59 fairer ai less bias and ai 13:03 to make something very positive for us 13:06 as humanity we need uh as scientists to 13:09 see 13:09 our fields in a very uh human humanistic 13:13 way 13:14 so that not only the technical stuff 13:16 advances but we also have to 13:18 be guided by serious and by effective 13:20 ethical principles 13:22 laws and norms as ryan said it's hard to 13:25 do to do that at the moment we are at 13:27 the beginning of uh 13:29 an ai cambrian explosion as several 13:32 people mention here but we need to be 13:34 very aware 13:35 of the social ethical and global 13:38 implications 13:39 that ai has these days we have to be 13:41 concerned about the north south 13:44 divide about the different cultures in 13:46 order to regulate it properly 13:49 we cannot see it only from a single 13:52 cultural perspective so 13:53 that's what i want to see ai researchers 13:56 doing to be they have to be concerned 13:58 about the technical results 14:00 the outstanding results ai has been 14:02 showing but also 14:03 we have to be to care about other people 14:06 about 14:06 other people's other countries and over 14:09 and over all 14:10 for the global health of the planet 14:12 thank you very much 14:13 and merry christmas happy new year to 14:16 everyone thank you gary and vincent for 14:18 the 14:18 brilliant debate you brought today and 14:20 for the scientists 14:22 i am reminded of the old african proverb 14:24 that i'm sure you all know which is it 14:25 takes a village to raise a child 14:27 clearly it will take a village as we've 14:29 seen today 14:30 to raise an ai that is ethical robust 14:32 and trustworthy
