Article URL: https://github.com/willderai/willder-core Comments URL: https://news.ycombinator.com/item?id=50436876 Points: 2 # Comments: 0
Eval-driven development helps you build AI agents against a consistent set of metrics. Define good behavior, write the eval first, then compare experiments.
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The Metal kernel for ggml_tri has been updated to use a select operation instead of scaling by comparison, aligning its behavior with the CPU kernel. This change ensures that values outside the triangle are set to zero rather than becoming NaN when encountering ±inf. A new test, test_tri_special, validates this fix across all four triangle types, confirming it passes with the update but failed previously.
Our most capable models for daunting technical work, Claude Fable 5.2 and Claude Mythos 5.2 set a new bar in coding, finance, and the sciences.
Article URL: https://github.com/infrixo-systems/rag-evaluation-starter Comments URL: https://news.ycombinator.com/item?id=50422943 Points: 1 # Comments: 0
Hello HN!I've always had a bad time redistributing programs that use shared libraries, AppImage in my opinion does too much, and a container is an overkill - not always integrates smoothly.I've moved to nix since long ago, but redistributing between nix and other distros or vice versa it's still a pain in the ass, more so if you want to run an alien app in nix or a nix app without the package manger in any other distro.For that, with the help of Claude, I've implemented a format that deduces at pack-time all the shared libraries a program needs, puts them, together with its own glibc and a patched dynamic linker into a single executable.This means that you don't actually need a runtime nor any special capability, it can run inside a FROM SCRATCH docker, alpine linux etc... And it also supports coreutils-like multiple programs accessible via symlinks, so it is a good fit for that purpose.You can just use:> felf pack $(which git) --output git.felfand you'll have already a git binary that works everywhere, no matter which distro you are building this from. This only packs the binary and their dependencies.Essentially, the effect is similar as if you LD_PRELOAD's all the libraries that it requires.In the end, we have been fighting these demons since long long ago, chroots/docker/appimage/flatpack/nix etc...So this xkcd applies: https://xkcd.com/927/I'm happy to share the project, I hope it inspires new discoveries/tools in this regard! Comments URL: https://news.ycombinator.com/item?id=50415219 Points: 2 # Comments: 0
Article URL: https://github.com/voidixyn/glassbrain Comments URL: https://news.ycombinator.com/item?id=50423154 Points: 1 # Comments: 1
Article URL: https://github.com/alam00000/bentopdf-hyper-compress Comments URL: https://news.ycombinator.com/item?id=50416782 Points: 1 # Comments: 0
Hi, Dmitri from Radioso here, an open-source platform to design AI agents for customers and visitors in any channel, in the style of Fin/Ada/Decagon. The repo is https://github.com/radioso-ai/radioso and our website is https://radioso.aiToday, your choices are:1. Buy a very expensive service for your vertical (usually starting with $$ five figures monthly) 2. Get a cheap off-the-shelf chatbot that mostly answers FAQs 3. Build your own, and then also build the inbox, human handoff, audit trail and integrations around itAt Radioso we wanted an open-source option that combines the best of all 3. You can integrate it with your own software via API/SDK or your CRM, or run it standalone, either self-hosted or in our cloud.The engine runs multi-step interactions and takes actions: calling your APIs, updating records, booking things. Maybe you’ve tried Parlant; Radioso is the alternative “with batteries included”: RAG, audit trail, customer service inbox, and integrations like Slack and email.Under the hood it’s plain TypeScript + PostgreSQL, works with OpenAI/Anthropic/other models, and is licensed under Apache 2.0 which includes all features (The only thing we keep under EE license is the multi-tenant layer we use to run our own cloud).We have existing customers running it for technical Q&A, course booking, online product recommendations and goods returns, among others, some reaching 92% of conversations automated. We’re currently working on voice support so we can offer a call center.Our ambition is to be “the WordPress of customer-facing AI” :), where people can contribute their favorite plugins and benefit from the ecosystem.Longer term, we think browsing the web will mostly mean talking to your own agent, and when you need a service or a purchase, your agent will talk to the vendor’s agent to get things done. For this, Radioso already publishes an A2A Agent Card and we’re working on the rest. Your Radioso services are also callable over MCP, for customers who already use it.Thanks for your attention. We’d especially love to hear which integrations you’d want, whether you’d self-host it, and what’s stopped you from deploying a customer-facing AI agent so far. Tell us what you think. Comments URL: https://news.ycombinator.com/item?id=50423820 Points: 1 # Comments: 0
