
[AINews] LLMs can read & write neural network weights: "Weight Space Programming" cuts Autoresearch out of the RSI loop
Editing Qwen’s weights to reduce reasoning loops, DeepSeek’s super-agent prototype, and the GDPx benchmark.
Nouveaux modèles et souterrain de l'IA
20 sessions en cours

Editing Qwen’s weights to reduce reasoning loops, DeepSeek’s super-agent prototype, and the GDPx benchmark.

PRs: https://github.com/QwenLM/qwen-code/pull/15762: "Measured on main at 79a9b753c60 , before this change: qwen4 , qwen4-max , qwen4-plus , qwen4.5-max , qwen4-coder-plus , qwen4-max-2026-10-01 , openai/qwen4-max and qwen4-omni-120b-think all resolved to 262,144. The last of those is already in use as the session model in the omni fixtures, so these ids are not hypothetical."…
Release: llm 0.37 There's a lot of stuff in this new release of my LLM CLI tool and Python library, representing around two months of accumulated features and fixes. I added gpt-6.1-sol and gpt-6.1-terra , plus a new llm openai endpoint add command to make it easier to configure additional models that use OpenAI-compatible endpoints. I switched the default model (if you have not set your own…
The New York Times is suing privacy-focused web browser company Brave for allegedly scraping the outlet’s copyrighted content and unlawfully distributing it to its own customers, like Anthropic and Perplexity.

Depuis des années, des communautés de passionnés travaillent d’arrache-pied pour déchiffrer et reproduire le code de certains jeux afin de les réinventer ou de les faire fonctionner sur d’autres machines. Mais l’arrivée fulgurante de l’intelligence artificielle vient tout bouleverser.

The New York Times and a group of other publications have filed lawsuits against the company that makes the Brave web browser over alleged unlawful scraping to train AI and also letting users bypass their paywalls, as reported by Reuters. According to a complaint filed by the New York Daily News, the Chicago Tribune, and […]
In 2024 i purchased an RTX 8000 48gb for $2400. As the market has changed I’ve kept an eye on prices. Two years later, they are available around $2100. Its a little slower than 3090 at inference (672gb/s vs 936gb/s) but it has double the memory so it can run larger models / contexts / higher quants. Rtx 8000 also wins on power, 265w vs 700w (2x 3090 to match 48gb) In 2024 two 3090s would cost…
Here's a question straight out of sci-fi: What if AI could predict what you were going to do before you decided to, even in a completely new situation?
Kind of a random thing, but I've gotten to the age where I'm starting to care about what the city council is doing. So I downloaded all the available council meeting notes from the last 16 years and pointed Qwen 3.8 27B Q6 at them and started having it dig through notes. Namely I wanted to see who approved the purchase of Flock cameras for our town. Turns out the police chief got a $9,000 grant…

This model looks quite spectacular. According to LiquidAI's own benchmarks, it scores higher than MiniCPM5-2B across the board, while offering 2x the context and taking up half the space in VRAM (3.6 GiB vs. 7.1 GiB for a quasi-lossless quant). Read the report: https://github.com/crusaderky/pixi-llm-recipes/blob/main/perplexity/LFM3-1.7B/README.md Raw plots as interactive HTML…
For fun, I gave Qwen 3.8 27b a physics problem involving some heavy math. A little bit into its reasoning, Qwen took a look at its tools, found that it had access to Blender via blender mcp - and that it could write and execute arbitrary python code through that. So it engaged Blender's python support to write itself bits of python code to do its math faster. You really have to tell this model…
I've been getting more into running LLMs locally, and I'm starting to wonder if fine-tuning is even worth the effort anymore. Models are getting really good, context windows are huge, and with things like RAG, subagents, and reasoning models, it seems like you can get pretty far without touching the model weights. For most use cases, wouldn't you be better off just using a good base model and…

submitted by /u/1-800-methdyke [link] [comments]

I compared two published benchmark charts for DeepSeek-V4.1-Flash-1017 and noticed something rather unusual. All four Unsloth quantizations AND the Q8 baseline simultaneously improved by approximately 2–3 percentage points on LiveCodeBench v6. Meanwhile, the GSQ-RCO results changed much less consistently. 1. The numbers Model First chart Updated chart Change Unsloth IQ1_S 88.95% 91.0% +2.05…
I'm not on anyone's side, I just love the competition. Both teams pushing each other means better quants for all of us. What I don't understand is why ISTA doesn't publish KLD for their quants. It doesn't depend on how long the model thinks, so it would make this a lot easier to compare. The only KLD I've seen for GSQ-RCO is in Unsloth's charts. Maybe there's a reason I'm missing. (English isn't…

submitted by /u/teakhop [link] [comments]
While fast inference is very welcome, I would like to know if it's worth increasing the speed over strata-nvfp4 or am I paying some unacceptable penalties. One thing I've noticed with Basalt is that it doesn't have dynamic rope scaling, so it goes off with the yarn scaling statically (2 for 524K context) from the get-go. Basalt also lacks a censorship switch, but the machinery exists so it's…
https://www.tomshardware.com/tech-industry/artificial-intelligence/anthropic-confirms-new-claude-code-limits-to-prevent-game-cloning-users-report-opus-5-5-is-also-actively-blocking-reverse-engineering-tasks Besides privacy and being in control of your data. Besides being able to control the quality of the inference compute. Besides being able to discuss things with the model and not have the cops…
another win for GLM. Chenru Duan on X: "We’re introducing Hydrogen-1.0, our first open-weight model for scientific research. We post-trained GLM-5.3 (@Zai_org) on our internal scientific data, lab records, and discovery trajectories. It scores 38.3% on FrontierScience-Research vs GPT-6-Astra’s 33.3% submitted by /u/Choice_Celery9481 [link] [comments]

There were some rumours the last few days that Qwen4 will be the last open-weight series of Qwen, and future ones would be API only. The following statement contradicts the rumours and clearly states the stance that Qwen is taking regarding their future releases. Qwen Head Liu Dayi Heng Clearly States : Future Qwen 4.0 and Qwen 5.0 Will Continue to Be Open Source! He believes that the value of AI…

Do you run multiple agents locally like I do? If so, this is a really nice speedup for the unified KV cache submitted by /u/jacek2023 [link] [comments]

We ran DeepSWE, Terminal Bench, Automation Bench, HLE, SciCode at 512K context on our DeepSeek UD version 3.1 GGUFs and show we're >10-20% better than GSQ-RCO We ran all other benchmarks (14 in total) to 128K. AIME2025 64x, DeepSWE/TB 3x. We addressed some issues people mentioned with these new benchmarks: 32K context was too short - we did 512K context for agentic + 128K for general tasks…

Measured, refusals 85%→0% even in thinking, 3 sizes 12 GB GPU VRAM, 64GB RAM + SSD via Strata Engine We took ISTA-DASLab's GSQ-RCO quants of DeepSeek-V4.1-Flash-1017 (the ones people run in Strata with a 12 GB GPU and the Engram table on SSD) and removed the refusals. We only touched 82 dense tensors per file: attention output, shared expert down proj and the Engram value proj. The 384 routed…

My first fully vibe coded Desktop app with Qwen 3.8 27B as someone with near 0 coding knowledge lol. Was paying $100 a year for an online Invoicing App so i decided to cook up one for myself. The results are mind blowing..I basically one shotted everything throughout development & implementation as Open Code's coding agents did all the work, fixing bugs, web search etc. All i did is connect my…