https://keshavaai.in/news One or two plain-words updates a week on what changed in AI and what it means for builders. Written with AI and checked against the original announcement. en Fri, 23 Oct 2026 02:13:59 GMT https://keshavaai.in/pulse/2026-10-19-vllm-0-32-0 https://keshavaai.in/pulse/2026-10-19-vllm-0-32-0 Mon, 19 Oct 2026 12:00:00 GMT vLLM, the open-source engine many teams use to serve language models, released version 0.32.0, with work from 363 contributors. The notes highlight KV cache formats that use less memory on more kinds of GPU, new start-up commands, support for new models, and fixes for three security advisories. A browser-origin default was also tightened. Why it matters: The KV cache is the memory that grows with every user and every token, and it often limits how many people one GPU can serve. A smaller one can mean more users per GPU. Faster start-up helps scaling, because a slow new replica cannot take traffic. If you expose the server, read the security items. Source: vLLM project, release notes (https://github.com/vllm-project/vllm/releases/tag/v0.32.0) https://keshavaai.in/pulse/2026-10-19-anthropic-independent-evaluators https://keshavaai.in/pulse/2026-10-19-anthropic-independent-evaluators Mon, 19 Oct 2026 12:00:00 GMT Anthropic says a team from METR, a nonprofit that tests frontier AI models, now has access close to what its own staff have. METR will publish what it finds. Anthropic cannot stop that, but it can ask METR to remove some kinds of information. It also works with SecureBio and Accenture, and is talking to other groups. Why it matters: If you rely on an AI provider, outside tests are new evidence to read when you decide how far to trust a model. The company says evaluators need four things: real skill, independence, enough access, and the freedom to publish. That is a good checklist for your own systems too. Source: Anthropic (https://www.anthropic.com/news/an-update-on-independent-evaluators)