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Fear and optimism in the age of AI

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Manage episode 484060391 series 3667050
Content provided by Andrea Jones-Rooy. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Andrea Jones-Rooy or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

Vasant Dhar has been working on AI since way before it was cool (and before most people thought it was possible). I've admired his work for a long time and since I started this show have wanted to have him on as a guest to talk about the strengths and limitations of LLMs. A few days ago, he published an article in The Hill about how DOGE is using AI wrong, and I knew I had to talk to him immediately.


We discuss, indeed, what DOGE is doing wrong, as well as the broader lessons we all can learn from this example about what makes a good vs. not-so-good use case for LLMs. We also talk about his recent and completely earth-shattering Severance-esque research where he and a colleague create a bot with the goal of simulating the valuation reasoning of investing legend Aswath Damodaran. Naturally, throughout the conversation, I pepper him with questions about how scared or optimistic we should be about all of this, as well as how AI can somehow be both incredible and limited at the same time.


Follow Vasant!

I'm @jonesrooy on Instagram and at jonesrooy.com.


And, because I'm trying to make friends with AI, below is a chapter summary! Woo hoo.


Chapters


00:00 The Evolution of AI: A Personal Journey

01:49 Understanding LLMs: Are They Thinking?

04:35 The Fear of AI: Balancing Optimism and Caution

06:57 Explaining LLMs to Newcomers

09:37 Learning and The Integration of the Senses

12:24 DOGE's Approach to AI in Government

15:22 The Need for Better AI Implementation in Government

17:47 Could This Actually Work?

20:16 A Problem with Using AI on Data from Humans

21:47 Contextualizing Project Failures

22:33 Applying AI to Investing

23:45 Building an AI Investor

27:36 The Science of Long-Term Investing

28:40 Simulating Expertise: The Damodaran Bot

32:33 The Art of Questioning in AI

36:07 Expectations and Realities of AI Development

40:10 Be the AI Change You Wish to See in the World

Behind the Data is a podcast that uncovers the hidden stories within the data shaping our world. From political polls to global happiness trackers, we dive into the datasets that influence the decisions we make—while showing you why data isn’t just numbers, but a way to understand the world. Whether you're a data newbie or a seasoned pro, each episode makes complex data approachable, revealing surprising insights and the human side of every dataset. Come for the discoveries, stay for the stories.


We are proud to be part of the Daily Tech News Show network of podcasts.


Subscribe and leave a review!


Hosted on Acast. See acast.com/privacy for more information.

  continue reading

17 episodes

Artwork
iconShare
 
Manage episode 484060391 series 3667050
Content provided by Andrea Jones-Rooy. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Andrea Jones-Rooy or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

Vasant Dhar has been working on AI since way before it was cool (and before most people thought it was possible). I've admired his work for a long time and since I started this show have wanted to have him on as a guest to talk about the strengths and limitations of LLMs. A few days ago, he published an article in The Hill about how DOGE is using AI wrong, and I knew I had to talk to him immediately.


We discuss, indeed, what DOGE is doing wrong, as well as the broader lessons we all can learn from this example about what makes a good vs. not-so-good use case for LLMs. We also talk about his recent and completely earth-shattering Severance-esque research where he and a colleague create a bot with the goal of simulating the valuation reasoning of investing legend Aswath Damodaran. Naturally, throughout the conversation, I pepper him with questions about how scared or optimistic we should be about all of this, as well as how AI can somehow be both incredible and limited at the same time.


Follow Vasant!

I'm @jonesrooy on Instagram and at jonesrooy.com.


And, because I'm trying to make friends with AI, below is a chapter summary! Woo hoo.


Chapters


00:00 The Evolution of AI: A Personal Journey

01:49 Understanding LLMs: Are They Thinking?

04:35 The Fear of AI: Balancing Optimism and Caution

06:57 Explaining LLMs to Newcomers

09:37 Learning and The Integration of the Senses

12:24 DOGE's Approach to AI in Government

15:22 The Need for Better AI Implementation in Government

17:47 Could This Actually Work?

20:16 A Problem with Using AI on Data from Humans

21:47 Contextualizing Project Failures

22:33 Applying AI to Investing

23:45 Building an AI Investor

27:36 The Science of Long-Term Investing

28:40 Simulating Expertise: The Damodaran Bot

32:33 The Art of Questioning in AI

36:07 Expectations and Realities of AI Development

40:10 Be the AI Change You Wish to See in the World

Behind the Data is a podcast that uncovers the hidden stories within the data shaping our world. From political polls to global happiness trackers, we dive into the datasets that influence the decisions we make—while showing you why data isn’t just numbers, but a way to understand the world. Whether you're a data newbie or a seasoned pro, each episode makes complex data approachable, revealing surprising insights and the human side of every dataset. Come for the discoveries, stay for the stories.


We are proud to be part of the Daily Tech News Show network of podcasts.


Subscribe and leave a review!


Hosted on Acast. See acast.com/privacy for more information.

  continue reading

17 episodes

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