Episode 25: Machines of Loving Grace, Entropix, AI and elections, GSM8K

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This is a podcast episode titled, Episode 25: Machines of Loving Grace, Entropix, AI and elections, GSM8K. The summary for this episode is: Can AI solve infectious disease? In Episode 25 of Mixture of Experts, host Tim Hwang is joined by Kaoutar El Maghraoui, Maya Murad, and Ruben Boonen. Today we analyze some papers. First, the experts dissect Machines of Loving Grace, a 15,000 word essay written by Anthropic’s CEO making some major AI predictions. Then, Apple generated a new benchmark based of GSM8K in a recent paper, the findings were intriguing. Next, we talk Entropix, a sampler intending to replicate chain of thought features. Finally, OpenAI disclosed they are seeing an increase in AI models faking articles, what can we do to fix this? All this and more, on today’s Mixture of Experts. The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity.

Key Takeaways

Will AI help us solve nearly all natural infectious diseases?

01:15 MIN

AI's Promise vs. Reality: A Balanced Debate

01:39 MIN

Machines of Loving Grace

09:39 MIN

Entropix

10:56 MIN

GSM8K

09:37 MIN

AI and Elections

09:00 MIN

DESCRIPTION

Can AI solve infectious disease? In Episode 25 of Mixture of Experts, host Tim Hwang is joined by Kaoutar El Maghraoui, Maya Murad, and Ruben Boonen. Today we analyze some papers. First, the experts dissect Machines of Loving Grace, a 15,000 word essay written by Anthropic’s CEO making some major AI predictions. Then, Apple generated a new benchmark based of GSM8K in a recent paper, the findings were intriguing. Next, we talk Entropix, a sampler intending to replicate chain of thought features. Finally, OpenAI disclosed they are seeing an increase in AI models faking articles, what can we do to fix this? All this and more, on today’s Mixture of Experts.

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity.