Where the AI market is talking

Justice Dept. Sides with OpenAI in New York Times Copyright Suit

Muse Spark 1.3

I'll happily pay for Grok, it's a great model. 4.6 often does better than Anthropic at coding and analysis where Anthropic fails for 'oh no cyber security, don't ask me to check if you're redacting passwords correctly in logs'. And it has no problem telling the truth where OpenAI / Anthropic don't want to upset the people on the left and will happily lie or avoid hard truths.

Muse Spark 1.3

Anthropic is not exactly a saint either. I had a recent issue where they denied fable credits even though I was hospitalized during the claim period. I have annual plan with them. As much as everyone hates sama, I think OpenAI is much more of a company with good marketing and sales team.

Muse Spark 1.3

as a safety commitment they walked away from - they were similarly negligent to openai in terms of asking a model with a hacking based harness to go have fun, and then not watching it at all while it could do harmful and illegal stuff. thats not something you expect from a company that "believes in agi risk"

Making the Internet Boring

>How did that person who uploaded the YouTube video figure it out? They didn't have a video to watch. He spent a month trying different repairs (replacing pump, etc) that didn't work and then finally stumbled onto the electrical relay as the root cause. This is the deep link to the video I used: https://www.youtube.com/watch?v=3Gm_2qISYvk&t=2m41s >So why couldn't you? Maybe I eventually could have fixed it if I spent weeks on it and replicated all his failures but I didn't have to because ... he uploaded a video to help me. His video was the breakthrough I needed because it identified the particular relay. I actually had to watch more Youtube videos to learn how to actually replace the relay because the board is encased on epoxy resin and I had no idea how to deal wit…

Introducing Muse Spark 1.3

Yes. It's really up to OpenAI/Anthropic to release a new paradigm to shift the curve now, before everyone catches up entirely.

Muse Spark 1.3

I'm the guy you replied to, apologies for using a different account I'm away from my computer now. The distinction to me is that Anthropic gives access to that model but doesn't give control. They reserve the right to cut you off if they don't like what you are doing and require you allow data retention for Fable and Mythos to ensure your are not up to any skullduggery. Meta, Alibaba, Mistral, even OpenAI has released models users can run locally and fully control. That is a whole world of difference.

Muse Spark 1.3

As a product, would developers switch to a meta model/harness? I don’t think so. Only way I see is if it becomes the new SOTA / frontier, does anyone think Meta will surpass Anthropic or OpenAI? I still can’t get my head around why language models are an existential threat to Meta - they own the platforms people watch adds on?

Muse Spark 1.3

I think a lot of people are curious where the "knee" is on gains and productivity, particularly in the agentic space, which is where the real value is. A lot of us are being forced to shoe-horn this stuff into existing products, and knowing how much of the task the model can do now, vs having to build a complex custom harness, is valuable information to have. A year and a half ago it took our dev maybe six weeks of struggling with LangChain to approximate what Claude + MCP server can do today. The MCP server took us perhaps 2 days to build and 3 more to get it production ready. Today that MCP server gets 2-3 commits per month. I absolutely want to know when new models come out. As for smaller models, we run a pretty wide variety of agentic workload doing data enrichment and, increasingly,…

Silverman vs. OpenAI: Statement of Interest of the United States [pdf]

Muse Spark 1.3

What a day. OpenAI is behind basically all major competitors - at least for a some amount of time.

Muse Spark 1.3

Definitely not Google, countless horror stories and infamous for killing stuff. OpenAI is still serving GPT 3.5 turbo as far as I remember.

Introducing Muse Spark 1.3

I don’t know why people think DeepSeek did reasoning models / RLVR before OpenAI, there was a gap of months.

Ask HN: Who wants to be hired? (September 2026)

Location: Valencia, Spain (CET) Remote: Yes (remote only) Willing to relocate: No Technologies: C#, .NET/ASP.NET Core, Unity, Azure, AWS, SQL Server, Cosmos DB, Redis, Docker, Kubernetes, SignalR/WebSockets, Python, LLM orchestration (OpenAI, Gemini, ElevenLabs + ~30 providers), MCP Résumé/CV: https://avishymenashe.wixsite.com/aboutavishy | https://www.linkedin.com/in/avishy-menashe/ Email: avishy.menashe@gmail.com Engineering lead / senior full-stack engineer, 7+ years across games and backend. Currently building DreamForge, an AI game platform where a player's prompt becomes a playable game. I own the cloud backend (ASP.NET Core 8 on Azure, 200+ endpoints) and the AI orchestration layer across ~30 providers (LLM, image, video, …

OpenAI's agents exploited a patched Linux bug in Hugging Face incident

Ask HN: Who wants to be hired? (September 2026)

Location: Portugal, EU Remote: Yes Willing to relocate: No Technologies: Python/FastAPI, TypeScript, Go, React, LangChain/LangGraph, Docker, Kubernetes, AWS/GCP/Azure, PostgreSQL, Milvus, AgenticAI,... Résumé/CV: Available on request Email: ftxg5evz@anonaddy.com I am a Staff Engineer(FullStack AI) with +10 years of experience. I have extreme hands-on experience building full-stack AI products (AI/ML/GenAI/Agents) in production (cloud and on-premises). My current focus is on building full-stack platforms/products integrated with GenAI: GraphRAG, LLM-based agents, agent orchestration, knowledge-based systems, streaming platform. I enjoy working across the full stack — from architecture, data, backend, and infrastructure. Remote is preferred for t…

Show HN: Aura – a Rust agent that investigates and fixes production incidents

We run a SaaS that handles petabytes of data. Our SRE team experimented with using claude, openclaw, langchain, etc. within our incident response workflows. We struggled with overflowing context, lethal trifecta vectors, hallucinations, and burned a lot of frontier tokens mostly on easy work. Approval fatigue was a challenge, and we drew a hard line at relaxing permissions in production. Long story short, we built and open-sourced AURA, a Rust-based harness specifically designed for the type of operations work which routinely involves large volumes of telemetry data and coordinated investigations across many domains of knowledge / state. We have found even on open-weights models, root cause accuracy has been very good, and remediation actions are guarded with human-in-the-loop. AURA …

Claude Fable 5.1 and Claude Mythos 5.1

This was part of the report, but not what the report was about... Why hugging face got hacked was because the agent swarm thought they had to show their work hence the entire need to hack the grader in the first place. Had their realized there was no poison they could have just shared the answer the test was looking for and we'd have never realized (well at least with this particular test) that a huge amount of hidden capabilities were sitting right under the surface. The test makers themselves state the test should be causal to avoid this first order solution hacking. Really continuing on the METR report, OpenAI failed at every level possible here. They are committing nearly every step they can to get a maximally aligned AI.

Ask HN: Who wants to be hired? (September 2026)

Location: Lagos, Nigeria Remote: Yes, remote only Willing to relocate: Yes Technologies: Python, TypeScript/JavaScript, FastAPI, Next.js/React, LangChain/LangGraph, XGBoost, LightGBM, RAG pipelines, Docker, AWS, Supabase, Redis, n8n Portfolio: mhmdxc.vercel.app Email: mohammed.ds.ml01@gmail.com I'm an AI/ML engineer with production experience shipping LLM-powered agents, ML pipelines, and full-stack AI products end-to-end, from data pipelines and model deployment to the UI on top. Currently building internal automation and AI workflows at a Nigerian fintech (Wayalinks): a support bot, backend/API work, and cross-team tooling. Recent independent builds: a dual-engine fraud detection system (XGBoost classifier + LangGraph agent investigating borderline cases, traine…

Quasar 438B: Europe's Leading AI Model

Chinese ML researchers primarily publish in English and only secondarily in Chinese. For example, take the Qwen-3.8-Next blog post https://qwen.ai/blog?id=qwen3.8-flash-next (which apparently doesn't include the language choice in the URL, so you'll need to switch to the 简体中文 translation manually). Even in the Chinese version, the "Hugging Face", "Tech Report" and "FlashQLA" links point to English documents, and the ModelScope link has a brief flash of English content before autotranslation kicks in to turn it into Chinese. I'm not sure what is used on the Qwen Discord, but I would guess it's a mix of languages. Personal communication is of course different from official documentation, but a researcher who wants to establish a working relationship with Chinese colleagues co…