AI
Turing test Splotchy chatbots
Can we use these words with AI? search, aware, discover, think, understand, see, learn, play, figure out, design,
Larry Page tedtalk
Yeah, so Deep Mind is a company we just acquired recently. It's in the U.K. First, let me tell you the way we got there, which was looking at search and really understanding, trying to understand everything, and also make the computers not clunky and really understand you -- like, voice was really important. So what's the state of the art on speech recognition? It's not very good. It doesn't really understand you. So we started doing machine learning research to improve that. That helped a lot. And we started just looking at things like YouTube. Can we understand YouTube? But we actually ran machine learning on YouTube and it discovered cats, just by itself. Now, that's an important concept. And we realized there's really something here. If we can learn what cats are, that must be really important. So I think Deep Mind, what's really amazing about Deep Mind is that it can actually -- they're learning things in this unsupervised way.
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G Hinton and A Ng
https://twitter.com/AndrewYNg/status/1667920020587020290?s=20
Fei Fei Li tedtalk
So ultimately, we want to teach the machines to see just like we do: naming objects, identifying people, inferring 3D geometry of things, understanding relations, emotions, actions and intentions.
The first step towards this goal is to teach a computer to see objects, the building block of the visual world. In its simplest terms, imagine this teaching process as showing the computers some training images of a particular object, let's say cats, and designing a model that learns from these training images.
No one tells a child how to see, especially in the early years. They learn this through real-world experiences and examples. If you consider a child's eyes as a pair of biological cameras, they take one picture about every 200 milliseconds, the average time an eye movement is made. So by age three, a child would have seen hundreds of millions of pictures of the real world. That's a lot of training examples. So instead of focusing solely on better and better algorithms, my insight was to give the algorithms the kind of training data that a child was given through experiences in both quantity and quality.
We went to the Internet, the biggest treasure trove of pictures that humans have ever created. We downloaded nearly a billion images and used crowdsourcing technology like the Amazon Mechanical Turk platform to help us to label these images.
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Jeremy Howard tedtalk Geoffrey Hinton
So we now know that computers can learn, and computers can learn to do things that we actually sometimes don't know how to do ourselves, or maybe can do them better than us. One of the most amazing examples I've seen of machine learning happened on a project that I ran at Kaggle where a team run by a guy called Geoffrey Hinton from the University of Toronto won a competition for automatic drug discovery. Now, what was extraordinary here is not just that they beat all of the algorithms developed by Merck or the international academic community, but nobody on the team had any background in chemistry or biology or life sciences, and they did it in two weeks.
Deep learning now in fact is near human performance at understanding what sentences are about and what it is saying about those things.
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Blaise tedtalk
So remember that what's been going on here is that we've been taking a lot of known x's and known y's and solving for the w in the middle through an iterative process. It's exactly the same way that we do our own learning. We have many, many images as babies and we get told, "This is a bird; this is not a bird." And over time, through iteration, we solve for w, we solve for those neural connections.
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Demis Hassabis
If it’s “just” an autocomplete, how can it take people’s jobs? (like mine, as an English teacher?)
Scott Aaronson: Some are angry that GPT’s intelligence is being overstated and hyped up, when in reality it’s merely a “stochastic parrot,” a glorified autocomplete that still makes laughable commonsense errors and that lacks any model of reality outside streams of text. Others are angry instead that GPT’s growing intelligence isn’t being sufficiently respected and feared.
A hundred million people have signed up to use ChatGPT, in the fastest product launch in the history of the Internet.
For a million years, there’s been one type of entity on earth capable of intelligent conversation: primates of the genus Homo, of which only one species remains. Yes, we’ve “communicated” with gorillas and chimps and dogs and dolphins and grey parrots, but only after a fashion; we’ve prayed to countless gods, but they’ve taken their time in answering; for a couple generations we’ve used radio telescopes to search for conversation partners in the stars, but so far found them silent.
Now there’s a second type of conversing entity.
Here’s an example I think about constantly: activists and intellectuals of the 70s and 80s felt absolutely sure that they were doing the right thing to battle nuclear power. At least, I’ve never read about any of them having a smidgen of doubt. Why would they? They were standing against nuclear weapons proliferation, and terrifying meltdowns like Three Mile Island and Chernobyl, and radioactive waste poisoning the water and soil and causing three-eyed fish. They were saving the world. Of course the greedy nuclear executives, the C. Montgomery Burnses, claimed that their good atom-smashing was different from the bad atom-smashing, but they would say that, wouldn’t they?
We now know that, by tying up nuclear power in endless bureaucracy and driving its cost ever higher, on the principle that if nuclear is economically competitive then it ipso facto hasn’t been made safe enough, what the antinuclear activists were really doing was to force an ever-greater reliance on fossil fuels. They thereby created the conditions for the climate catastrophe of today. They weren’t saving the human future; they were destroying it. Their certainty, in opposing the march of a particular scary-looking technology, was as misplaced as it’s possible to be. Our descendants will suffer the consequences.
Unless, of course, there’s another twist in the story: for example, if the global warming from burning fossil fuels is the only thing that staves off another ice age, and therefore the antinuclear activists do turn out to have saved civilization after all.