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Creating a machine that thinks may have seemed like science fiction in the 1950s. But John McCarthy decided to make it a reality. And he started with a language he called LISP. Colin Garvey describes how McCarthy created the first language for AI. Sam Williams covers how early interest in thinking machines spread from academia to the business world, and how—after certain projects didn’t deliver on their promises—a long AI winter eventually set in. Ulrich Drepper explains that the dreams of AI went beyond what the hardware could deliver at the time.
But hardware gets more powerful each and every day. Chris Nicholson points out that today’s machines have enough processing power to handle the resource requirements of AI—so much so that we’re in the middle of a revolutionary resurgence in AI research and development. Finally, Rachel Thomas identifies the languages of AI beyond LISP—evidence of the different kinds of tasks AI is now being prepared to do.
If you want to dive deeper into LISP and the origins of artificial intelligence, you can check out all our bonus material over at redhat.com/commandlineheroes. You’ll find extra content for every episode.
Follow along with the episode transcript.
4.6
452452 ratings
Creating a machine that thinks may have seemed like science fiction in the 1950s. But John McCarthy decided to make it a reality. And he started with a language he called LISP. Colin Garvey describes how McCarthy created the first language for AI. Sam Williams covers how early interest in thinking machines spread from academia to the business world, and how—after certain projects didn’t deliver on their promises—a long AI winter eventually set in. Ulrich Drepper explains that the dreams of AI went beyond what the hardware could deliver at the time.
But hardware gets more powerful each and every day. Chris Nicholson points out that today’s machines have enough processing power to handle the resource requirements of AI—so much so that we’re in the middle of a revolutionary resurgence in AI research and development. Finally, Rachel Thomas identifies the languages of AI beyond LISP—evidence of the different kinds of tasks AI is now being prepared to do.
If you want to dive deeper into LISP and the origins of artificial intelligence, you can check out all our bonus material over at redhat.com/commandlineheroes. You’ll find extra content for every episode.
Follow along with the episode transcript.
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