The Future of AI: Consciousness and Ethical Dilemmas

The Michael Shermer Show

Michael Shermer

Dialogue, Science, Reason, Michaelshermer, Natural Sciences, Skeptic

4.4 • 921 Ratings

🗓️ 15 October 2024

⏱️ 100 minutes

🔗️ Recording | iTunes | RSS

🧾️ Download transcript

Summary

How should we go about understanding LLMs? Do these language models truly understand what they are saying? Or is it possible that what appears to be intelligence in LLMs may be a mirror that merely reflects the intelligence of the human observer?

In this episode, Terry Sejnowski explores the history and future of AI and its profound implications for understanding the human mind. He explains AI’s evolution from early logic-based systems to cutting-edge advancements like deep learning and large language models, including ChatGPT, emphasizing the need for clear operational definitions and a strong mathematical foundation to advance AI research. Sejnowski also highlights the parallels between scientific discovery and engineering, discussing practical applications of AI in areas such as language translation and weather prediction.

Terry Sejnowski is the Francis Crick Chair at The Salk Institute for Biological Studies and a Distinguished Professor at the University of California, San Diego. He has published over 500 scientific papers and 12 books, including ChatGPT and The Future of AI: The Deep Language Revolution.

Transcript

Click on a timestamp to play from that location

0:00.0	You're listening to the Michaelber Show. This episode is brought to you by Brilliant, the online learning platform that allows
0:27.8	you to learn about interesting and important topics through a fun and
0:31.4	interactive method of teaching that enables anyone to master almost any topic.
0:36.0	Brilliant helps you build your critical thinking skills, that's what we do here at Skeptic,
0:40.0	through problem solving, not memorizing oh the brilliant lessons are active
0:46.4	interactive in fact the way it works is you cue up the lesson and you just start
0:51.0	playing along it's big fun and then they give you little
0:53.9	quizzes and if you get it right they go yay and you move on you continue if you get it
0:57.8	wrong they go man try again and so you try again explains why you're wrong
1:01.1	and then when you get it right explains why you're right it's great I've been doing a bunch of the lessons of brilliant
1:07.1	And I find them most useful including one I just got a new one queued today. They send you a little notices that there's new courses,
1:16.3	lessons.
1:16.8	This one's under probability theory, which I love.
1:20.3	And this is a case study on going viral and X.
1:22.5	Why do some posts go viral and X and others don't?
1:25.5	Most of mine don't, but some do.
1:28.2	And so why is that?
1:29.7	And you could put those calculations into a model,
1:32.3	which is what this lesson does here, and then make
1:34.7	predictions about which posts are likely to go viral and which are not.
1:38.2	So go to brilliant.org slash Geptic, or just scan the QR code right there on the screen or in the
1:45.0	description below you'll see the link to Brilliant.org slash Skeptic.
	...

Please login to see the full transcript.

Previous episode | Next episode

Disclaimer: The podcast and artwork embedded on this page are from Michael Shermer, and are the property of its owner and not affiliated with or endorsed by Tapesearch.

Generated transcripts are the property of Michael Shermer and are distributed freely under the Fair Use doctrine. Transcripts generated by Tapesearch are not guaranteed to be accurate.