2026-09-21

Release: datasette-explain 0.2.2 Explain plans now work on read-only stored-query pages. I upgraded datasette.simonwillison.net to Datasette 1.0a40, which inspired me to ship a new version of this explain plugin. Tags: sqlite , datasette

TypeSafe AI released Jev, a System One model that answers typed questions with probabilities instead of generating text. Input costs $0.042 per 1M tokens, and output tokens are free. We cover the API, the vendor benchmarks and their caveats, what developers are already building, and the documented limits. The post TypeSafe AI Releases Jev: A System One Model That Returns Typed, Calibrated Decisions Instead of Text appeared first on MarkTechPost .

9月18日，在第一届中国网络空间安全大会上，《网络安全人才实战能力报告—AI赋能篇》正式发布

To test what it can do. Qwen3.8-Flash-Next Intel Autoround W4A16 running locally on 4xV620 ~2k prefill and 70ts decode.. Were running around 3 hours. Harness is OMP (I think it made a big difference). Most of the time model was running 2 browsers simultaneously and testing/fixing everything. The most sloppy prompt possible: create a game where a space traveller in the space he neets eniemes who shoots in him and asteroids which he should avoid. he have a blaster gun to shoot enemies and asteroid

Hey everyone, After wrestling with hardware and engine issues for days, I finally got Qwen 3.8 Next running properly on my multi-GPU rig. Thought I’d share the setup journey, benchmarks, and thermal results for anyone trying something similar. Seeing all the ongoing memes on Reddit about multi-GPU setups turning into absolute space heaters and catching fire, I decided to run some rigorous thermal tests to see for myself. he Troubleshooting Odyssey PCIe Link Speed Issue: Right after installation,

After seeing u/Nandakishor_ml’s post introducing Laya , I wanted to see how fast it could run in a standalone C++ implementation. Credit to u/Nandakishor_ml for the architecture, training and open-source release. My contribution is the inference implementation: laya.cpp , built on ggml with custom CUDA kernels. It supports all three checkpoints—English, multilingual and typed-decisions—with native tokenization, model execution and output formatting. There’s also an HTTP server with a JEV-compati

I'v been thinking recently with the AI safety incidents (hugging face, frontier labs whistleblowers etc.) how self-hosting is more important now than ever. Basically there there are three ways self-hosting impedes an oncoming cyber apocalypse - which leaving everyday services to centralized providers would accelerate. I'v boiled this down to: Data accessibility - our data on our infra means no 3rd party has unauthorised acccess like an employer/service provider/state would have access if we gave

Just find it interesting, since if Taalas tried to get into the consumer market, it could be interesting. Kind of like how we have game discs on CDs. Of course, a Qwen3.8-27B chip is stuck on 3.8-27B, but it's not going to $0 when Qwen4-27B launches, since it runs magnitudes faster than GPUs and is still pretty good. Assume it's Q4 (or Q8, or whatever you'd prefer it to be). I think the bigger question is if you'd buy a chip of an LLM on it, in a more general sense. Or, when ? What about Qwen4.5

I’ve spent basically the last 8 hours testing different models on the exact same web-development prompt, and I finally finished. The whole point of this nine-hour test was that which local model matches the frontier-level intelligence at size and could fit easily in an RTX 3060-like consumer card. My setup: GPU: RTX 3060 12GB RAM: 16GB DDR4, single-channel OS: CachyOS (Arch Linux) Local models were run through my local llama.cpp setup. Same prompt for every model. I recorded the generations so y

Overclocking the CMP 170HX 40GB I was able to get the memory bandwidth from 1,386.2 GB/s to 1,890.1 GB/s, that's a +36.4% increase. Qwen 3.8 27B token generation jumped from 110 T/S to 202 T/S, same config, nothing changed except the overclock. Just throwing this out there for whoever owns one of these cards. It's good to look into overclocking them as it's potential is severely cut down. Edit: GPU wattage is at 300 watts GPU temps are slightly lower now