[Misc] Eric Schmidt on AI

Watch: https://www.youtube.com/watch?v=UQkeRxeh34I Transcript eric schmidt is a business leader and software engineer that served as google's chief executive officer from 2001 to 2011. under his leadership google grew from an early silicon valley startup to arguably the most important technology company on the planet schmidt is currently co-founder of schmidt futures and sits on the board of many public and private institutions he is still involved with technology consults with the us department of defense also talks about ai in his latest book the age of ai and our human future written alongside former u.s secretary of state henry kissinger and computer scientist daniel huddenlocker schmidt was a guest at the milken global conference and here he anticipates some of the ai innovations that we will certainly see in five years he also predicts what we might see in 20 years here are the details recently in the last couple of years there have been extraordinary gains so for example a team at google and at the baker lab separately figured out a way to actually understand if you take dna what proteins are generated and what their structure is that's an extraordinary achievement in my opinion worth a nobel prize there are drugs being designed now that could not be possibly designed by humans in any way because of their complexity there's evidence that ai can be used in biology ai is mapped to biology the way math is to physics in other words biology is so complicated that ai will be used to interpret biology and predict its outcome over and over again ai will arrive in your life another example is the hottest area in my industry right now are large language models uh recently a set of startups have been funded between 100 and a billion 100 million and a billion dollars they have no current product or revenue plans um the the belief of the power of this technology these large language models are interesting because you suck all the information in like you read all the web which computers can do but we can't and then they discover things they appear to discover a structure of language and an example of recent google product last week can actually translate from one computer language to another and we didn't give it any examples of one to translate to the other it discovered a structure and it can predict it these are the beginning of general intelligence the the current um excitement stems from a technology called transformers that was invented three or four years ago and what transformers do is it can predict the next word after a set of words so if you give it a sentence it can predict what the word will be and it's done using a complicated mathematical technique it turns out predicting the next word is mathematically the same thing as predicting the next sound the next video the next image all of that and so you have a unification a multi multi-modal unification of video text and speech so these systems sound and look like they're intelligent a good example is gpt3 which came out last year which kicked the current revolution off you asked it do you think like a human and it says no i do not because i am a large language model and you are a i think a human who has been taught to think in this way now is that it thinking about you or is it pattern matching we can't tell and the truth is and i'm as part of philanthropic work i'm funding projects to try to understand this we don't actually understand why this works we don't mathematically understand why it works and we also don't understand its failure modes so you wouldn't want to use this as a replacement for something that's live critical because we can't say when it fails when does it just crash the current large language models for example have trouble with the notion of gravity so if you say to them i moved it i moved the object from here to here and then i put it up here and i put it down there and so forth now everyone just followed what i did the large language model gets confused because it doesn't understand gravity so the computer scientists say we're going to now add concepts right so with concepts and then with planning maybe you get to the point where it looks like a human-like intelligence which has all sorts of issues if i were 24 today this is exactly what i'd be working on this is where the hardest and most challenging computer science systems problems are with the greatest payoff now remember that the system can predict patterns and if you can predict a pattern you can also generate an artifact there's a duality in these systems where they can generate things so part of the issues that we face now is that these systems can generate speech i'll give you an example within five years the following will be true you'll be able to take a system um take one of these language models which would be infinitely expensive to make but you didn't pay for it it shows up in your doorstep and it fine tunes the technical term is literally fine-tuning it you fine-tune it to you who are you what do you care about it sort of watches you and learns from you it learns your voice right all of a sudden it can generate videos with you in it now you could think of this as a second ai right now the interesting thing is imagine five years from now i install this thing and i use it for a few years and eventually we all die unfortunately well it lives on right as a pretty good impersonation of me and what happens when i'm dead and it's still learning is that me is that an artifact of me or is it just a stupid artifact of history that you'll keep in a box and some future will say oh eric was so stupid back then but it's entertaining to watch him right because he didn't keep learning we don't know we have no way of discussing these things this stuff is incredibly powerful it will be the basis of enormous gains in human health language translation communication summary and education all the things that milken represents will be affected in an almost always positive way having said that there's terrifying consequences as well so the first question has to do with jobs does this fundamentally mean there are more jobs or less jobs i spent my whole life people saying computers will replace humans humans won't have anything to do so far that narrative has been false notice that there's a huge surplus of jobs and not people to fill it certainly in the united states the second one has to do with national security something i've worked on for almost a decade now and in our in the kissinger book we talk a lot about this what happens when the...