Episode 18 · · 17:17
Google rejoins the open model party and gets some backlash for a frequent problem for generative AI.This is AI generated audio with Python and 11Labs. Music generated by Meta's Music...
Episode 17 · · 14:58
10 Sora and Gemini 1.5 follow-ups: code-base in context, deepfakes, pixel-peeping, inference costs, and moreThis is AI generated audio with Python and 11Labs. Music generated by Meta...
Episode 16 · · 09:07
Emergency blog! Three things you need to know from the ML world that arrived yesterday.This is AI generated audio with Python and 11Labs. Music generated by Meta's MusicGen.Source co...
Episode 15 · · 07:44
In an era dominated by direct preference optimization and LLMasajudge, why do we still need a model to output only a scalar reward?This is AI generated audio with Python and 11Labs. ...
Episode 14 · · 10:19
Scale's making over $750 million per year selling data for RLHF, who's coming to take it?This is AI generated audio with Python and 11Labs. Music generated by Meta's MusicGen.Source ...
Episode 13 · · 09:28
A small model at the beginning of big changes.This is AI generated audio with Python and 11LabsSource code: https://github.com/natolambert/interconnects-toolsOriginal post: https://w...
Episode 12 · · 19:05
Note: some of the audio in the second half is a little wonky, but the general voice was upgraded so hopefully it's a little less "poppy" until then!I'm trying to fix little pronuncia...
Episode 11 · · 09:59
Local LLMs: the latency solution, Meta's open AGI, personalization myth, and moats X factorThe deployment path that'll break through in 2024. Plus, checking in on strategies across B...
Episode 10 · · 08:18
A fun demo on how generative AI can transform content creation, and tools for my fellow writers on Substack!This is AI generated audio with Python and 11LabsSource code: https://gith...
Episode 9 · · 15:59
A sampling of recent happenings in the multimodal space. Be sure to expect more this year.This is AI generated audio with Python and 11LabsSource code: https://github.com/natolambert...
Episode 8 · · 13:41
And why the comparisons don't really matter. Repeated patterns in the race for reproducing ChatGPT, another year of evaluation crises, and people who will take awesome news too far.T...
Episode 7 · · 09:57
The state of the ML communities big and small starting 2024. My general expectations for the year.This is AI generated audio with Python and 11LabsSource code: https://github.com/nat...
Episode 6 · · 14:45
The core themes of ML and the blog this year. What changes in 2024.This is AI generated audio with Python and 11Labs. Source code can be found here: https://github.com/natolambert/in...
Episode 5 · · 35:47
Michael Poli is a PhD student at Stanford and a researcher at Together AI. https://zymrael.github.io/Tri Dao is the Chief Scientist at Together AI and an incoming assistant professor...
Episode 4 · · 10:31
Big Tech's LLM evals are just marketingA PSA everyone needs. The importance of a wait and see attitude when it comes to new models, big and small, open and closed.Read the post here:...
Episode 3 · · 16:46
(some buggy audio in this one, from MoE rather than Mixtral lol)Mixtral: The best open model, MoE trade-offs, release lessons, Mistral raises $400mil, Google's loss, vibes vs marketi...
Episode 2 · · 17:27
Direct vs. RL methods for preferences, more RLHF models, and hard truths in open RLHF work. We have more questions than answers.Read the full post here.
Episode 1 · · 17:03
Synthetic data is the accelerator of the next phase of AI — what it is and what it means.For the post, see it here: https://www.interconnects.ai/p/llm-synthetic-data
