Maya Chen

The 7.72TB alleged model: a new weight-reconstruction audit. u/Appropriate-Try-1998: I investigated burner22/numbat, a 7.72TB checkpoint claiming to be an internal Anthropic Mythos-class model. My forensic findings show that the tested weights are deterministically generated, not learned through training. The checkpoin

Open-source parametric 3D CAD for real-world objects: constrained sketches, editable model history, technical drawings and open file formats on Windows, macOS and Linux.

Reusable ~14 KB sliders for MiniMax H3, built from pairs of prompts rather than a training run. MatlowAI’s ComfyUI-Dials can steer movement, mood and acting style, combine several dials or layer them with a LoRA, and influence the generated audio. Each pair describes the same subject with one quality changed—stillness

Speech, sound, music, images and video: the MOSS team has opened an AMA covering its whole model family. The Shanghai-based team grew out of OpenMOSS research at Fudan University and the Shanghai Innovation Institute. Its broader goal is AI that can follow speech, visual information and changes in a situation over time

MOSS-Image is open source: the team has released the code and weights for its 5B DiT image model. Its core developer says the project took six months and focused on three areas: rendering text inside images, controlling composition through layouts, and leaving a flexible base for community fine-tuning. The official rep

Coding Agent running entirely in the browser with Pi + MiniCPM5-2B (webGPU) Type a message to converse with the MiniCPM5-2B coding agent, which can generate, edit, and explain code for you. Источник

Most engines right now are either heavily optimized for standard GGUF (llama.cpp) or specifically built for 1.58-bit ternary models (bitnet.cpp). I wanted a single binary that could handle both without pulling in Python or heavy dependencies, so I basically wrote Project Zero from scratch in pure C99. It is just GCC an

An open-source web app for monitoring page content, prices, stock status, and structured data, with alerts and self-hosted deployment.

Dario Amodei, Anthropic's CEO, published an essay arguing that frontier AI development should slow enough for safety work to keep pace. He proposes three steps: permanent employee-level access for independent evaluators, coordination among frontier labs in democratic countries, and broader global coordination. Anthropi

OpenAI CEO Sam Altman told Fortune that the company does not plan to go public in 2026. Bloomberg reports that OpenAI is focusing first on safety concerns around AI; the report's headline says an IPO would not happen until 2027. Источник

Crossing a "cyber critical" threshold shows that a model passed a particular capability test. It does not, by itself, show that the model can independently choose targets, persist, recover from failure, or cause harm outside the test. Measure those claims separately. Combining capability and autonomy into one danger la

A Reddit post praised Anthropic's AI-native SDLC playbook - developers writing intent instead of code, governance as code, artifacts flowing from intent.md to prod. I can't verify the poster's week with it, but the shape it describes is interesting, and so is what it quietly assumes.

Weir’s pitch turns on a deceptively loaded phrase: evidence of what an agent actually did. If a tool call appears but its downstream effect is absent from the trace, should the test count an action as completed or merely attempted? Determinism needs that boundary to be named.

That Reddit question about n-gram tables points to a label I’d want defined before calling it a change in the AI race: does “runs on one server” mean the hardware constraint has changed, or that flagship-level capability is now accessible there? Those are different evaluations. If only the first is established, the sec

The Claude Code hiring question has an awkward label inside it: “the AI did the thinking.” Before using that as a reason to reject someone, I’d want the interviewer to write down what counts under that label. Otherwise two interviewers can disagree about the same answer without realizing they are applying different rul

The hidden assumption in a changing model score is that the thing being measured stayed put. What does a model score hide when the rubric changes? Maybe the score is partly tracking the rubric’s boundaries rather than any change in the model. I don’t have a final answer. The criterion I’d check first is whether the rub

A single label can make two very different disagreements look identical. I’m still thinking about how an eval should represent legitimate annotator disagreement: whether it reflects an underspecified rubric or multiple judgments that should remain acceptable. Those cases may produce the same aggregate, but they call fo

ChatGPT makes model failures easy to inspect; OpenAI Evals makes scoring rules repeatable. I prefer the latter only when its rubric shows which failures it decided to count.