The Ledger, every show

“Well, I don't think we're that close to a system that's going to be able to, you know, if I have an hour with it, let's say just to be conservative. I don't think we're that close to a victory there.”

“The bottom line is what's driving it, and it's not that likely, unless Congress steps in, that there will be a pause.”

“And what these systems are doing is kind of like amazing enhanced version of sampling where you don't even recognize what the samples are anymore. It's all derivative.”

“Lambda actually has fewer sensors than my watch. My watch has a lot of sensors and lamb doesn't really have anything sensing the real world, except for its linguistic input.”

“I am in no way arguing that it is not possible to build a sentient machine. I don't think we know how to do it, and I don't think we're clear enough on what it would consist of, but I'm not making the argument that it's impossible.”

“So I'm pretty confident that we'll have models of the world, internal ideas about how the world works. I don't see how to build an AI without it.”

“If what you want to do is to put out like 10,000 versions of something on Twitter, something untrue and find one that sticks, then misinformation as a service, which is how they might call it in the tech industry is a pretty damn powerful technique. And if it …”

“So yeah, there's a ton of companies that are trying to use GPT's technology. I don't know any of them that are You know, breakout successes.”

“The issue there is the software itself is relatively easy to copy.”

“These successes are examples of one thing. They're all examples of what a cognitive psychologist would call perceptual classification, and that's part of what we do as intelligent human beings, but it's not all that we do.”

“Deep learning, it mostly cares about texture.”

“If we want to build machines that are as smart as people, we should start by studying small people.”

“50 years from now, we will know how to build really deeply neurally inspired models, but right now we have to settle for cognitive science, for psychology, linguistics, fields like that, where we can actually get some insight now before we unravel the brain.”

“In fact, they can drive in Palo Alto, but they can't drive in Manhattan.”

“There's still been very little progress in building a general game player that can play games that require strategy or insight, complex three-dimensional graphics.”

“But we're not there yet. We're not even close.”

“I asked Peter Norvik, who at the time was director of research at Google I said, you know, how much money would it really be worth if you could have strong AI? And he wrote back about five minutes later, I'm suddenly a much louder, I think. And estimated somet…”

“People get very excited every time there's a new deep learning result. But it's always the case of doing better on the high frequency data than the low frequency data.”

“So, where I think we should start looking for clues, in a nutshell, is children.”

“If you have human-level intelligence, you can make sense of that, but if you just memorize stuff off the web and do information retrieval, you could actually get stuck there.”

“And so, as a result, there is no great machine learning technique in natural language.”

“Facebook's new M service, which they have not rolled out at scale has humans on the back end. There's a little bit of AI in there, but it's mostly, ah, human beings, which is why they haven't rolled it out for a billion customers. They don't have enough human …”

“Where they looked at things like, can you pull out a chart based on a series of financial statements, SEC statements from a bunch of companies and these systems all claimed to do it, but accuracy was under 10%. And overall on this new benchmark, accuracy was a…”

“If you talk about another domain, like language synthesis, it turns out that current systems can make very convincing language, but it's often bullshit. That doesn't matter in the same way in art. So in, if you have a system make up a news story, even if it's …”

“And it's worth realizing that the art system doesn't really understand what it's doing. It's just correlating words with images in its database. It doesn't have the same intentionality about the objects as a person does, but it can still be a very effective te…”

“I think it probably will change art. I think in general that humans are still going to be like the creative inspiration and are often going to be filtering things.”

“There's no machinery in our brains innately to tell us the difference between a person and machine. And what happens is that in evolutionary perspective, anything that could talk was probably a person, right?”

“And, in fact, the point of the company that we formed is to add common sense, which the Roomba lacks.”

“We wanted Rosie the robot, and instead we got Roomba.”

“So when you start to look at the errors that these things make, they're not human-like errors, and again, they seem almost like hallucinations.”

“Finance is really fundamentally a sparse data problem because The financial markets aren't stationary.”

“This is what DeepMind used in their systems, and they used a version called deep reinforcement learning. And what they did is they collected billions or, you know, probably millions of data points for each game.”

“So the old traditions are much better at dealing with abstract knowledge The new traditions are much better at learning things quickly.”

“I'm very interested in that. Let's put it that way.”

“There was another mind-blowing study this week that showed that one of the best Go programs, KataGo, could be fooled by some silly little strategy that would be obvious to a human player. But, you know, somebody was able to follow this strategy and, like, an a…”