In this episode, Nathan sits down with Paige Bailey, Lead Product Manager of Generative Models at Google Deepmind. In this conversation, they discuss what it's like to be a PM for an LLM as opposed to an app, defining ideal LLM behaviour, and reasoning - how do you distinguish real abilities vs pattern matching? If you're looking for an ERP platform, check out our sponsor, NetSuite: http://netsuite.com/cognitive

TIMESTAMPS:
(00:00) Episode Preview
(00:01:15) Introducing Paige Bailey
(00:04:21) Paige’s background at Google Brain and the Deepmind merger
(00:07:00) PM for a LLM vs being a PM for an app
(00:11:21) The development timeline and compute budget of PaLM-2
(00:14:30) Paige’s role in the PaLM 2 project
(00:15:30) Sponsors: Netsuite | Omneky
(00:17:26) Defining desired capabilities for PaLM-2
(00:19:17) The amount of work that went into elevating PaLM 2 from PaLM 1
(00:20:28) Has Google lost its ability to ship?
(00:24:240) Paige's "eureka" moment seeing GitHub Copilot capabilities
(00:27:47) Competing PaLM 2 with other models
(00:32:20) Grokking and the predictability of emergent capabilities
(00:37:30) Citizen scientists and the multilingual capabilities of PaLM 2
(00:39:29) Distinguishing real reasoning vs pattern matching
(00:45:51) Products using PaLM-2 that people should try
(00:50:35) Most exciting AI projects that you can try out
(00:52:29) Curriculum learning and successor to the transformer

LINKS:
PaLM 2: g.co/palm2
Duet AI for developers: https://cloud.google.com/blog/products/application-development/introducing-duet-ai-for-developers
Avenging Polayni’s Revenge: https://www.youtube.com/watch?v=BmyB-4S9QuY

X/TWITTER:
@DynamicWebPaige (Paige)
@labenz (Nathan)
@eriktorenberg
@CogRev_Podcast


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Music Credit: GoogleLM