Archive - Interconnects AI

Gemma 4 and what makes an open model succeed

Hint: it's not benchmark scores.

Apr 3 • Nathan Lambert

March 2026

Latest open artifacts (#20): New orgs! New types of models! With Nemotron Super, Sarvam, Cohere Transcribe, & others

New orgs! New types of models! With Nemotron Super, Sarvam, Cohere Transcribe, & others

Mar 30 • Florian Brand and Nathan Lambert

Lossy self-improvement

The case for why self-improvement is real but it doesn't lead to fast takeoff.

Mar 22 • Nathan Lambert

GPT 5.4 is a big step for Codex

On evaluating and understanding the frontier of agents, and why I still turn to Claude.

Mar 18 • Nathan Lambert

What comes next with open models

Markets, capabilities, cope, and bewilderment in the industrialization of language models.

Mar 16 • Nathan Lambert

Dean Ball on open models and government control

Subtle precedents on the future of open models set by the unfolding Anthropic v. Department of War case.

Mar 6 • Nathan Lambert and Dean W. Ball

35:35

Olmo Hybrid and future LLM architectures

The latest Olmo model and discussions at the frontier of open-source post training tools.

Mar 5 • Nathan Lambert

Latest open artifacts (#19): Qwen 3.5, GLM 5, MiniMax 2.5 — Chinese labs' latest push of the frontier

Welcome to the year of the horse!

Mar 3 • Florian Brand and Nathan Lambert

February 2026

How much does distillation really matter for Chinese LLMs?

Reacting to Anthropic's post on "distillation attacks."

Feb 24 • Nathan Lambert

Open models in perpetual catch-up

The open-closed gap, distillation, innovation timescales, how open models win, specialized models, what’s missing, etc.

Feb 17 • Nathan Lambert

Opus 4.6, Codex 5.3, and the post-benchmark era

On comparing models in 2026.

Feb 9 • Nathan Lambert

Why Nvidia builds open models with Bryan Catanzaro

Interconnects interview #17 on the past, present, and future of the Nemotron project.

Feb 4 • Nathan Lambert

1:07:41

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