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.
What this episode covers
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.
NOW PLAYING
Why intent prediction needs more than an LLM
No transcript for this episode yet
Similar Episodes
Mar 26, 2026 ·1m
Mar 19, 2026 ·34m
Feb 18, 2026 ·11m
Feb 11, 2026 ·45m