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

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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?

(00:24:24 0) 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

Duet AI for developers

Avenging Polayni’s Revenge

X/TWITTER:

@DynamicWebPaige (Paige)

@labenz (Nathan)

@eriktorenberg

@CogRev_Podcast

SPONSORS: NetSuite | Omneky

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Music Credit: GoogleLM