What Role Do AI & Computational Language Play in Solving Real-World Problems?

How can computational language help decode the mysteries of nature and the universe? What is ChatGPT doing and why does it work? How will AI affect education, the arts and society?

Stephen Wolfram is a computer scientist, mathematician, and theoretical physicist. He is the founder and CEO of Wolfram Research, the creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. He received his PhD in theoretical physics at Caltech by the age of 20 and in 1981, became the youngest recipient of a MacArthur Fellowship. Wolfram authored A New Kind of Science and launched the Wolfram Physics Project. He has pioneered computational thinking and has been responsible for many discoveries, inventions and innovations in science, technology and business.

"Nobody, including people who worked on ChatGPT, really sort of expected this to work. It's something that we just didn't know scientifically what it would take to make something that was a fluent producer of human language. I think the big discovery is that this thing that has been sort of a proud achievement of our species, human language, is perhaps not as complicated as we thought it was. It's something that is more accessible to sort of simpler automation than we expected. And so, people have been asking me, when ChatGPT had come out, we were doing a bunch of things technologically around ChatGPT because kind of what, when ChatGPT is kind of stringing words together to make sentences, what does it do when it has to actually solve a computational problem? That's not what it does itself. It's a thing for stringing words together to make text. And so, how does it solve a computational problem? Well, like humans, the best way for it to do it is to use tools, and the best tool for many kinds of computational problems is tools that we've built. And so very early in kind of the story of ChatGPT and so on, we were figuring out how to have it be able to use the tools that we built, just like humans can use the tools that we built, to solve computational problems, to actually get sort of accurate knowledge about the world and so on. There's all these different possibilities out there. But our kind of challenge is to decide in which direction we want to go and then to let our automated systems pursue those particular directions.”

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