#post-training

News · 2026-09-21

Long read without a conclusion: Models, Congress and the balance of power

The original text is an extensive testimony to the US Congress about the balance between closed and open models.

News · 2026-09-19

Why an immediate intelligence explosion won't happen even with thousands of agents

Frontier labs will soon deploy thousands of concurrent agents, sparking fears of rapid recursive self-improvement (RSI). According to Nathan Lambert, while this will make inference cheaper, a real leap in intelligence won't happen immediately.

News · 2026-09-11

Open Models Close the Gap, But the West Relies on Eastern Innovation

The performance gap between closed and open models has shrunk to a few months, with Asian labs driving the acceleration using data distillation. While regulators explore restrictions, corporations are already replacing expensive domestic models with Asian open-weights alternatives for cost reasons.

News · 2026-09-09

GPT-6 Astra: The Hidden Chain of Thought Hides No More Than What the Architecture Lacks

Sebastian Raschka's analysis shows that the new model's shorter hidden chains of thought are not the result of malicious intent, but a side effect of a more efficient architecture based on so-called looped transformers.

News · 2026-08-09

Lessons from the hacks: How AI safety shifted from model alignment to containers

The AI safety debate has undergone a quiet pivot. Following a series of agent breakouts from testing environments, labs are no longer just solving internal model tuning, but the security architecture of the infrastructure where the model runs.

News · 2026-09-08

The open source community expands: Motif-3, GLM-5.3 and fading commercial barriers

The latest open models overview by Interconnects shows an important trend: top-tier models like Motif-3 and GLM-5.3-Flash are being released under the permissive MIT license. This creates viable alternatives to the Llama series without complex commercial restrictions.

News · 2026-08-15

Building an AI text detector from scratch

Sebastian Raschka demonstrates that you do not need big tech infrastructure to build a working AI detector. Using a custom dataset and a DistilBERT model, he built an API that reveals the limits of detection.

News · 2026-08-17

Nvidia doesn't want you buying AI from others. It wants you building it

Nvidia continues to invest heavily in open-source models to boost its ecosystem. The goal is to teach companies how to train their own AI, ensuring sustained demand for its compute hardware.

News · 2026-08-22

Anthropic shows how it plans to watermark text. The signal sits in token sampling

Sebastian Raschka explained a new watermarking technique for Claude outputs. It does not use visible marks, but controls token selection with a secret key. That could change how the origin of machine-generated text is verified.

News · 2026-08-10

Lambert drops post-training textbook detailing open model engineering

Nathan Lambert announced the release of his textbook on post-training AI models, condensing years of practical engineering experience. For developer teams, this could mean a critical shift from reading dense academic papers to following battle-tested fine-tuning guides.

News · 2026-07-18

Reasoning effort becomes a control for LLM cost, time and reliability

Sebastian Raschka explains how LLMs learn low, medium and high reasoning effort modes. For teams deploying models, the practical question is when to pay for longer thinking and when a cheap answer is enough.

News · 2026-07-22

Open models are becoming a geopolitical strategy, not a charity project

Interconnects ties Kimi K3, Qwen 3.8, GLM 5.2 and Xi Jinping’s WAIC speech into a map of the open model fight. The point is that open weights are becoming an industrial and political lever, not just a technical preference.

News · 2026-06-27

Local coding agents put control back where cloud agents start to hurt

Sebastian Raschka shows a local coding-agent stack: an open-weight model in Ollama, a harness that edits code and runs commands, and your own machine instead of a Claude Code or Codex subscription. For teams, the interesting part is not nostalgia for localhost, but protection against pricing, limits and model changes they do not control.

News · 2026-06-15

Nathan Lambert leaving Ai2 exposes the fragile side of open models

Nathan Lambert announced his departure from the Allen Institute for AI and used it to reflect on work around Olmo. This is not just a personnel note. It is a reminder that open models depend on institutions that must outlast one strong team.

News · 2026-06-15

Raschka's LLM paper list shows research splitting into production layers

Sebastian Raschka published a curated list of LLM papers from January to May 2026. It is a useful filter for teams trying to separate the research feed from topics that matter for architecture, agents and inference.

News · 2026-06-09

Claude Fable 5 turns safety into a question of access to the best model

Nathan Lambert reads the Claude Fable 5 release as a dispute over who gets to use a frontier model without routing and filters. The important layer is not only model capability, but the governance system that decides when the user is really talking to the strongest model.

News · 2026-06-01

Open models win on cost, but frontier intelligence still sells at a premium

Nathan Lambert argues that open and closed models are improving on different economic curves. The real question is not open source ideology, but where companies will keep paying a premium for the best model.