Jack Altman

speaker
4,592 appearances 200 recordings 1 series first heard May 2025 last heard yesterday

Jack Altman’s voice in public audio — every appearance, attributed to the second.

Trend

recordings per month · last 12 months
24 · Sep OctJan 26AprJulnow

Recordings per month over the last 12 months — 139 in all, peaking in Sep 2026 with 24.

Appearances

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Personalization isn't an edge case. voice-verified
It's fundamental to how the treatment works. voice-verified
They also get into the extraordinary operational challenge behind this. voice-verified
How do you manufacture thousands of different medicines, one patient at a time, quickly and reliably enough to make personalized medicine work at scale? voice-verified
And finally, they look at where the platform could go next. voice-verified
From other cancers to rare genetic and autoimmune diseases. voice-verified
Thanks for listening to this episode of the A sixty Z podcast. voice-verified
If you liked this episode, be sure to like, comment, subscribe, leave us a rating or a review, and share it with your friends and family. voice-verified
For more episodes, go to YouTube, Apple Podcasts, and Spotify. voice-verified
Follow us on X at A16Z and subscribe to our Substack at a16z.substack.com. voice-verified
Thanks again for listening, and I'll see you in the next episode. voice-verified
As a reminder, the content here is for informational purposes only, should not be taken as legal business, tax, or investment advice, or be used to evaluate any investment or security, and is not directed at any investors or potential investors in any A16Z fund. voice-verified
Please note that A16Z and its affiliates may also maintain investments in the companies discussed in this podcast. voice-verified
For more details, including a link to our investments, please see A16Z.com forward slash disclosures. voice-verified
AI can increasingly solve math problems that would challenge professional mathematicians. voice-verified
But solving a problem isn't necessarily the same thing as understanding it. voice-verified
In this episode, A16Z infra partner Licia Lee sits down with University of Toronto mathematician Daniel Litt to separate the headlines about AI and mathematics from what the models can actually do today. voice-verified
Daniel explains why recent results have changed his views of AI, where frontier models already resemble human mathematicians, and where they still fall short, particularly when it comes to intuition, developing new theories, and even figuring out which questions are worth asking. voice-verified
They also explore what happens to mathematics when generating a proof becomes cheap. voice-verified
Why academic incentives may need to change, and how mathematicians can use AI without outsourcing the understanding that makes the work valuable in the first place. voice-verified
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