Interconnects

Home
Navigation
Llama 3.1 405B, Meta’s AI strategy, and the new, open frontier model ecosystem
Defining the future of the AI economy and regulation. Is Meta’s AI play equivalent to the Unix stack for open-source software?
 • 
Nathan Lambert
2
SB 1047, AI regulation, and unlikely allies for open models
The rallying of the open-source community against CA SB 1047 can represent a turning point for AI regulation.
 • 
Nathan Lambert
2
Artifacts Log 2: Gemma 2, more Chinese LLMs, high quality datasets, and domain-specific training
A roundup of interesting open ML models in June (and July) 2024.
 • 
Nathan Lambert
Switched to Claude 3.5
Speculations on the role of RLHF and why I love the model for people who pay attention.
 • 
Nathan Lambert

June 2024

Interviewing Dean Ball on AI policy: CA SB 1047, upcoming AI disaster response, Llama 3 405B, Chinese open-source AI, and scaling laws
A roundup on current happenings in AI policy.
 • 
Nathan Lambert
 and 
Dean W. Ball
56:30
RLHF roundup: Getting good at PPO, sketching RLHF’s impact, RewardBench retrospective, and a reward model competition
Things to be aware of if you work on language model fine-tuning.
 • 
Nathan Lambert
Frontiers in synthetic data
Trends in synthetic data that I'm watching closely in the leading open and closed models.
 • 
Nathan Lambert
Text-to-video AI models are already abundant, but the products?
Signs point to a general use Sora-like model coming very soon, maybe even open-weights.
 • 
Nathan Lambert
AI for the rest of us
Apple Intelligence makes a lot of sense when you get out of the AI bubble. Plus, the cool technical details Apple shared about their language models…
 • 
Nathan Lambert
A case study in reproducibility of evaluation with RewardBench
A very technical deep dive. Lessons in evaluating, using, and training reward models on open-source infrastructure.
 • 
Nathan Lambert
A realistic path to robotic foundation models
Some thoughts and excitement after revisiting the industry thanks to Physical Intelligence founders Sergey Levine and Chelsea Finn. Not “agents” and not…
 • 
Nathan Lambert
4

May 2024

We aren’t running out of training data, we are running out of open training data
Data licensing deals, scaling, human inputs, and repeating trends in open vs. closed LLMs.
 • 
Nathan Lambert
© 2024 Nathan Lambert
Privacy ∙ Terms ∙ Collection notice
Start WritingGet the app
Substack is the home for great culture