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David Chalmers
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- 2015-11-15
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- 2015-11-15
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“So, how do we think about the future really when it comes to artificial intelligence? And I think the only way to do it is actually to kind of set out the whole tree of possibilities that we can imagine and try to not sort of fixate on one particular way that things might go because we just don't know where we're going to go down that tree at the moment. So there's a whole tree of possibilities. Is AI going to be human-like or not? Is it going to be embodied or not? Is it going to be a whole collection of these kinds of things? Is it going to be a collective? Is it going to be conscious or not? Is it going to be self-improving in this exponential way or not? I don't think we really know, but we can lay out that huge range of possibilities and we can try to analyze each possibility and think what would steer us down in that direction and what would the implications be.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“Because it'll always be optimistic. So I think the Right, the derivative. That's the problem with a lot of technology discussion in general we visit these in a very derivative way versus viewing the original, but putting that exhortation aside, how do people make sense of this? Like what, how do they make sense of what is possible?”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“The arguments by Bostrom et al. Maybe we do, maybe we don't, but I think there's a very, very serious case to answer there. And in order to answer it, you have to read their arguments. You can't just kind of assume what you think their arguments are.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“So anything that's really, really smart is going to have a number of goals that anything is going to share. And these are going to be things like self-preservation and gathering resources. If it's sufficiently powerful, then any goal that you can think of, if it's really, really good at solving that goal, then it's going to want to preserve itself, first of all. Because how can it maximize the number of paper clips in the world, to use Nick Bostrum's argument, if it doesn't preserve itself or if it doesn't gather as many resources as it can? So that's their argument for why we have to be cautious about building something that is a very, very powerful AI, very powerful optimizer. So I think the very important thing here is that the media tends to get the wrong end of the stick here and think this as some kind of evil terminator-like thing. And so we might not think that those arguments are flawed.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“We might try and architect their minds so that they are very, very human like. But can I just come back to the Nick Bostrom kind of argument? Because he points out that although we shouldn't anthropomorphize the AI, nevertheless, if we imagine this very, very powerful machine capable of solving problems and answering questions, that there are what people who think about this refer to as convergent instrumental goals.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“You use the term anthropomorphism because it is. I've noticed you use the word creatures to refer to AI. And I think that's really telling because they are going to be more like aliens or more like animals than they are like humans. I mean, the chances of them being just like humans are very small.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“But then Bisque, just moving on a little bit from that though, it is worth pointing out some of the arguments that people like Nick Bostrom and so on have advanced and that you shouldn't anthropomorphize these creations. You shouldn't think of them as too human-like.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“If you were a person in those circumstances, you would want to get out. And in fact, very often science fiction films that portray AI, that's a fundamental premise that they use for how they work is that they assume that we're going to assume that they AI is very much like us and has the same kinds of motives and drives for good or for ill. They can be good motives or bad motives. They could be evil or they could be good. But it's not necessarily the case that AI will be like that. Depends how we build it. And if you're just going to build something that is very, very good at making decisions and solving problems and optimization.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“Okay, so we've talked a lot about some of the abstract notions of this. And, you know, this is not a concrete answer because we're talking about a fiction film. But how possible in reality is the ex-Machina scenario? And a warning to all our listeners at spoiler alerts are about to follow. So if you're really bitter about spoiler alerts, you should probably sign off now. The reality that the character, the main embodied AI, Ava, could essentially fight back to her enslavement. To me, the most fascinating part of this story, and you have no time to talk about it right now, but I do want to explore this at some point in the future, is sort of the gendering of the AI, which I think is incredibly fascinating. How real is that scenario?”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“If you walk down a British high street, Main Street today, one of the things you'll notice is a plethora of massage parlours, nail salons, and barber shops. Service businesses. Because these are the things that you can't do through Amazon.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“I read that and I thought, hang on a minute, though, because what they're looking at is they're looking at the jobs of basically well-paid information workers and saying, well, you can't automate their jobs away. But the bits you can automate are the bits that are currently, many of them are bits that are currently done for them by other people. So the typing pool, you know, we've got rid of the typing pool because we all type for our exactly. So this means that the support workers for those people are potentially put out of business by AIs.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“Well, I think look at where we are today, which is that we're quite far away from a generalized intelligence. And McKinsey just looked at this question about the automation of the workforce, and they did something very interesting. They looked at every worker's day and they broke it down into the dozens of tasks they did and figured out which ones could be automated. And their conclusion was we'll be able to automate quite a bit, but by no means the entirety of any given worker's job, which means the worker will have more time for those other bits, which were always the social, emotional, empathetic and judgment driven aspects of their job, whether you're a delivery person.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“That's right. And corporate entities aren't set up to think about that. Like Patrick Lynn studies the ethics of robotics and AI, and that entire work is funded by government contracts and distributed through universities. So, okay, so the elephant in the room, AIN jobs, what are our thoughts on that?”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“You never know. There's also this question about the kind of questions that you will look at as an academic. So the trolley problem being a good one, but there are all sorts of ethical questions that don't necessarily naturally play a part in your thinking when you think about your Wall Street.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“It's incredibly attractive, and of course, many, many people will go into industry in that way. But there's also something attractive for a certain kind of mind in staying in academia, where also you can explore maybe some larger and deeper issues that you, I mean, for example, Google aren't going to hire me to think about consciousness.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“We've just seen, for example, Uber has snaffled the entire robotics department of Carnegie Mellon. Presumably the motivation of the people there is that finally the work that they've been doing on self-driving vehicles and so on. They should get out into the world. And you can actually make a difference. And yeah, I'm sure they get much better pay. But I mean, the main thing is that rather than doing all of this in a theoretical way, here is a company that's prepared to fund you to do what you want to do. In the real world in the next decade, and that must be amazingly attractive.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“Well, I ought to put in a little pitch for academia because the one thing that you do retain by staying in academia is a great deal of freedom and the ability to disseminate your ideas to whoever you want. So you're not in any kind of silo. And some of these companies are very generous in making stuff available.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“Actually, DeepMind are another example of the same thing because if you want to apply reinforcement learning to games and that's enabled them to make some quite fundamental sort of progress, you don't need vast amounts of data either to play the game, which is a great...”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“Look at, say, Boston Dynamics, because one of the ways you train machines to walk like animals is not to use a massive internet data set of how cats walk. So in that case, not having access to that data is not an impediment. And you can develop amazing things, and they have done. That's a great example. It's been acquired by Google.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“I think you'd be hard pushed to say, look at voice interfaces between Apple, Microsoft, Google, Baidu, and Nuance. That's quite a crowded field already. So it does feel like there are a lot of AI startups who are going to run up against this problem of both data and distribution. But that said, there are particular niche applications where you can imagine a startup being able to compete because it's just not of interest to a large company now. They may then be able to take a path to becoming independent.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“But also, they are getting the Silicon Valley as the new Wall Street argument. They are getting the people who used to go into financial services, which is a good thing. I remember the head of a Chinese sovereign wealth fund saying a few years ago, you Westerners are crazy. You educate your people in these fantastic universities, and then you take the best people and you send them into investment banks where they invent things that blow up your economy. Why don't you have to do something useful? We used to say that too. And the whole of, you know, the Chinese Politburo is they're all engineers, and they really value engineering culture and engineering skills, and they can't believe that we've sort of wasted it in this way. So I think it's fantastic that now there's less money to be made at Wall Street than maybe there is a Silicon Valley and people are going west. I think that's only got to be a good thing.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“Right. And also, they have the resources to buy whoever they want. And an interesting phenomenon we're seeing in academia these days is that it used to be the case that people who had were very interested in ideas and intellectual things, they wouldn't necessarily be tempted away to the financial sector. But we'd still retain a good chunk of them in universities to do PhDs and go on. But now companies like Google and Facebook can hoover up quite a few of those people as well because they can offer intellectual satisfaction as well as a decent salary.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“You can't build a user interface without using natural language, processing and natural language understanding. So that forces the allocation of capital into these sectors because that's the only way that you can compete.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“And then the other two are, so there's this phrase, which I'm sure Andreess Norovitz is familiar with, which is software is eating the world. And as software eats the world, there are many more places where AI can actually be relevant and useful. So you can start to use AI in a food delivery service because it's now a software coordination platform, not chefs in a kitchen, and therefore more places for it to play. And this is a commercial argument. And so Murray's explained some of the technical reasons. A third commercial argument is accelerating returns. As soon as you start within a particular industry category to use AI and get benefit from it, the increased profits you get, you reinvest into more AI, which means your competitors have to follow suit. So you can't now build an Xbox video game without tons of AI.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“So I add three more to that list. One is in practical software architectures, we're starting to see the rise of microservices. What's nice about microservices are very, very cleanly defined systems. So you don't need generalized intelligence. You just need very specialized optimizations. And as our software moves from these hideous spaghetti's to these API-driven microservice architectures, you can apply machine learning or AI-based optimizations to improve those single interfaces.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, yeah. So basically, what's driving the whole machine learning revolution, if we can call it that, is, I mean, there are three things. And one is Moore's law, so the availability of a huge amount of computation, in particular the development of GPUs or the application of GPUs to this whole space has been terrifically important. So that's one. Two is big data or just the availability of very, very large quantities of data because we have found that algorithms that didn't really work terribly well on what seemed like a lot of data, you know, 10,000 examples actually work much better if you have 10 million examples. They work extremely well. The unreasonable effectiveness of data, as some Google researchers called it. And so that's two. And then the third one is some improvements in the algorithms. So there have been quite a number of little tweaks and improvements to ways of using.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“So actually, deposit her for a moment. You started off very early on talking about some of the drivers for why you're excited about this time, why this time might be different. What are some of those more specifically? Like Moore's Law, we've talked about. Because that's obviously one of the scalars that sort of helps.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“Well, without making any distinctions Still going to be boringly academic because I want to remain kind of neutral because I just don't think we just don't know. I think these arguments in terms of recursive self-improvement, the idea that if you did build human level AI, then it could self-improve. I think there's a case to be answered there. I think it's a very good argument. And certainly I do think that if we do build human-level AI, then that human level AI will be able to... To improve itself, but I kind of agree with Tom's argument that it doesn't necessarily entail.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, or we could be like, I suppose, like Babbage saying, I can't imagine how you could ever build a general purpose system using this architecture because he can't imagine a non-mechanical architecture for computing. Right”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“It's not possible is because we're actually just not seeing these physical quantities. When we touch on this idea of consciousness, there is this idea of integrated information theory, which is this theory that consciousness is actually an emergent property of the way in which systems integrate information, and it's almost a physical property that we can measure.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“There are a lot, and you know, as we start to peel apart the brain and our understanding of the neurological basis for how kind of cognition functions work, we learn more and more and we see more and more complexity as we dig into it. So in a sense, it's a case of we don't know what we don't know. But we've been here before we had understood this idea of there being a magnetic field and needing to represent physical quantities with tensors rather than with scalars or vectors. We didn't see magnetic fields, we didn't understand them, we didn't have mechanisms for manipulating them because we couldn't measure them. And therefore we could affect them. And there would have been this whole set of physical crystals and rocks that were useless because we didn't know that they had these magnetic properties and we didn't know we could use them. Silicon dioxide being a great example. Totally useless in the 17th century. Quite useful now. And so at some point we might say that the reason we think this looks very hard.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“The point is that a system that's twice as good if it's, say, an order, it might scale nonlinearly. So it might be 256 times harder to build a system that's twice as good. And so every incremental improvement is going to take longer. And it's going to take a lot longer. Improvements in other areas like Moore's law and so on are not fast enough to allow each incremental generation of better intelligence to arrive sooner than the previous one. So there's a simple scaling argument that this need not be linear.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“So, I think the takeoff argument has a sense of plausibility, it's a timing that's the issue. So I can't deny the possibility that we could build systems that could program better systems and that could start to program better systems.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“Don't sound like a believer in the kind of takeoff theory that the AI is able to develop a better AI at less time. And so you get this sort of runaway. And I think that's a very unconvincing argument. It assumes all sorts of things about how things scale.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“And this is a case where it's really important to distinguish between the short term specialist AI, the kind of tools and techniques that are becoming very, very useful and very economically significant. And general intelligence, artificial general intelligence or human level AI. And we really don't know how to make that yet. And we don't know when we're going to know how to make that.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“And I think the answer is we just don't know. But again, there's a very, very important distinction to be made. This is the trouble with academics. We just want to make distinctions. Distinctions, you know.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“So, wait, where are we then when people have expressed fears? Because one of the things I think has compelled me to invite all three of you in this discussion is none of you fall into one of these extremes of completely cheerleading, like the future is dead and, you know, we're going to be attacked and taken over, or the other extreme, which is sort of dismissive. Like, this will never happen ever. Where are we?”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“Google will expect us to do that less and less as time goes by and expect the interactions to be in more and more in natural language. But can I come? So I think that between the two of you, you've raised the two kind of opposing sides of this deeply important ethical question about the relationship between consciousness and intelligence and consciousness and artificial intelligence. Because on the one hand, there's the prospect of us failing to treat as conscious something that really is very intelligence and that raises an ethical issue for how we treat them. Then on the other side of the coin, there's the possibility of us inappropriately treating us conscious, something that is not conscious and is perhaps not as intelligent. So both of those things are possible. We can go wrong in both of those ways. And I think this is really one of the big questions we have to think about here. And the first, I think the first really important point to be made is that there's a difference.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“We'll get an Amy invite. And it does start to raise some of the issues that are very present day, right? They're very present day because right now we have these systems. I think one of the ethical considerations is that we need to think about our own attention as individuals and as people. And as we start to interface with systems that are trying to be a bit like the Turk, the chess playing device that pretended to be a human, we're giving attention to something that can't appreciate the fact that we're giving it attention. And so I'm now using a bit of computer code to impose a cost on you.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“Exactly, I didn't do that. And I was quite nice to her. And then I had a couple of people who are incredibly busy. Write very long emails to her saying I could try this, I could try this. If it's not convenient, I could do this. And I thought, this is just not right. There is a misrepresentation on my part. So I then started to create a slightly apartheid system with Amy, which is that if you're very important, and Murray, you fell into that category, you'll get an email directly from me.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“So let me give you a practical example of that. There's an AI assistant called Amy, which allows you to schedule calendar requests. And so I'll send an email to you, Murray, and say, I would like to meet you at CC Amy. And then Amy will have a natural language conversation with you, and you think you're dealing with my assistant. One of the things that I found was I started to treat her very nicely because the way she's been designed as a product, from a product manager perspective, is very thoughtful.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“Anyway, so there's the point of the extent to which a creature with a mind that we recognize is cleverer than we thought, whether it's right for us to boss it around. But we're going to get this with AIs as well, aren't we? Because the usual scenario people worry about is we are enslaved by the AIs. But I'm much more interested in the opposite scenario, which is if the AIs are smart enough to be useful, they will demand personhood and rights, at which point we will be enslaving them.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“In your space of possible minds, we have a whole bunch of minds that we could be, and some people are trying to figure out already, which are animals. And then you've got the sort of social animals, the group minds there. And this kind of brings us to another ethical question from the previous one we were talking about, which is the whole question of the evidence that octopuses are very octopodes, we should say, are extremely intelligent, has made some people change their mind about whether they want to eat octopus.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“Some of the examples that kind of approximate where we can go because the examples that come to mind, I think historically of Doug Engelbart's notion of augmented cognition, augmented intelligence. And then I'm even thinking of current examples like Stephen Hawking, Helene Mialay wrote a beautiful book called Hawking Incorporated about how he's essentially a collective because I don't agree with this turn of phrase, but describing him almost as a brain and a vat, surrounded by this collective of a group of people who are anticipating his every need. And it's not just like Obama's crew who's helping him get elected and his support team, it's actually people who understand him so well that they know exactly how to help him information.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“Instead of the spreadsheet, and you, instead of having a hundred data samples, you just look at 16 million and the Excel can handle. So we've already started to explore the space of decisions using these tools to extend human reach.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“In a sense, we already have. It's called Excel. It's not even so much that we trust whether it works. Let's assume it works. What we're doing is we're allowing, using Excel, we're allowing ourselves to manipulate much larger data sets that we could have done just with pen and paper.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“Think I'd separate out the two areas of transparency. So, one is the black box nature, right? Can we look inside the box and see why it got to the conclusion it got to? The other side that's important is to actually say this is the conclusion we were aiming for. And within policymaking, what becomes interesting then is forcing policymakers to go off and say that extra million pounds we could have put into heart research, we didn't even though it cost four lives and we put it into something else because we needed to.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“Well, I suspect that they will be, and I think that's why, in fact, this whole question that you're raising of trying to make the decision-making process more transparent, even though it's based on statistics and so on, I think that's a very important research area.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, I mean, I very much agree with that. I see machine learning as a kind of subfield of artificial intelligence, and it's a subfield that's had tremendously a tremendous amount of success in recent years and is going to go very, very far. But ultimately, the machine learning components have to be embedded in a larger architecture, as indeed they already are, you know, in some ways in things like deep minds work.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source
“So I have a model which says that AI and machine learning are really quite distinct things. AI is all about building systems that can in some way replicate human intelligence or explore the spaces of possible minds, Murray's phrase, whereas machine learning is a very specific technique about building a system that can make predictions and learn from the data itself. So there are AI efforts that have no machine learning in them. I mean, psych, CYC is a great example. You try to catalog all the knowledge in the world. And I think it's the mindset of the market to combine the two because it might give something more attention.”
2015-11-15 · a16z Podcast · a16z Podcast: Artificial Intelligence and the 'Space of Possible Minds' · IDENTIFIED FROM THE TRANSCRIPT · source