Why intent prediction needs more than an LLM episode artwork

EPISODE · Jun 30, 2026 · 29 MIN

Why intent prediction needs more than an LLM

from The Stack Overflow Podcast

Ryan sits down with Frank Portman, CTO at Yobi, to talk about why next-token prediction, though great for language, isn’t the right inductive bias for forecasting human behavior. They discuss how Yobi builds a “foundation model of behavior” using transformers and graph neural networks instead of chat-style LLMs, and what it takes to run millions of personalization decisions per second while keeping consumer data private.Episode notes:Yobi is a behavioral AI company building foundation models that predict future behavior for ad tech, marketing, and more.Connect with Frank via fportman.com or at yobi.ai.Congrats to Hooked on winning a Populist badge for their answer to Removing whitespace around a saved image.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Episode metadata supplied by the publisher feed · Published Jun 30, 2026

Embed this episode

Ryan sits down with Frank Portman, CTO at Yobi, to talk about why next-token prediction is limited when it comes to forecasting human behavior.

Distinct summary based on available episode metadata or transcript content.

NOW PLAYING

Why intent prediction needs more than an LLM

0:00 29:58

No transcript for this episode yet

We transcribe on demand. Request one and we'll notify you when it's ready — usually under 10 minutes.

No similar episodes found.

No similar podcasts found.

Frequently Asked Questions

How long is this episode of The Stack Overflow Podcast?

This episode is 29 minutes long.

When was this The Stack Overflow Podcast episode published?

This episode was published on June 30, 2026.

Can I download this The Stack Overflow Podcast episode?

Yes. Use the download control on the episode player to save the publisher-provided media file.
URL copied to clipboard!