AlphaGenome 2: Deciphering how cells read DNA to better understand disease
Predicting how DNA sequences and their variations impact specific human cell types and disease.
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How Workday Built an Enterprise-Scale AI Agent Platform with LangGraph and LangSmith
See how Workday used LangGraph and LangSmith to build an internal AI agent platform that cut prototype time from months to less than a day and compliance needs.
Optimizing Muse Spark Open on TPU v7 with SGLang-TorchTPU
TL;DR We serve Meta’s Muse Spark Open, an 816B-parameter mixture-of-experts model, on a single TPU v7 host of four chips, with SGLang running on the TorchTPU PyTorch backend. At the... The post Optimizing Muse Spark Open on TPU v7 with SGLang-TorchTPU appeared first on PyTorch.
Show HN: Black Ops II statically recompiled to native ARM64 macOS
I grew up with Black Ops 2 and wanted to see if I could make it work on my 2020 MacBook Pro. So I used Claude Opus 5.5 to create a tool that converts your copy of the game (from Steam) to a native ARM64 Mac app, with almost 60fps in all areas. The whole game is statically recompilated ahead-of-time (AOT) and does not use any emulator whatsoever, be it Wine, Crossover or Rosetta. The best thing is the performance, although some heat issues are still to fix. You get to play the whole Campaign, local Multiplayer (with bots) and local Zombies (all DLCs maps; you need to have them in your Steam library obviously) at about 60fps. Split-screen was not in the PC version, but I've been working on it lately; it's coming soon! LAN mode is on the roadmap for later too :) Comments URL: https://news.ycombinator.com/item?id=50449891 Points: 1 # Comments: 0
UAEF: A framework-agnostic system for closed-loop evaluation of AI agents
The Universal Agent Evaluation Framework (UAEF) is a framework-agnostic system for evaluating AI agents. UAEF converts each framework's traces into one canonical format, scores them with 36 built-in metrics across 7 dimensions, and stores results so teams can compare agent versions and catch regressions.
Clinically Informed Colour Encoding Improves the Localisation and Stability of Explanations in Deep Learning ECG Models: External Validation in a UK Biobank Epilepsy Cohort
arXiv:2611.09971v1 Announce Type: new Abstract: Objective: It is not known whether the input representation governs the quality of explanations of deep learning models for electrocardiogram analysis. Risk of dangerous ventricular repolarisation is judged from the QT-interval and the shape of the T-wave, features that are hard to assess visually and harder still to verify in a model's reasoning. We evaluate a pseudo-colour encoding filling the area beneath the QT interval, its colour sequence designed from clinical electrophysiology knowledge and mapped to a validated risk prediction model, the QT-nomogram. Methods: Two identically configured residual networks were trained on single-heartbeat images from a clinical trial, differing only in whether pseudo-colour encoding was applied, so that any difference is attributable to the chromatic channel alone. To externally validate the effect, both models were applied without fine-tuning or threshold tuning to a previously unseen epilepsy cohort from the UK-Biobank at two visits, and eight explanation methods compared on faithfulness, localisation and stability. Results: The pseudo-colour model achieved areas under the receiver operating characteristic curve of 0.903 and 0.914 at the first and follow-up visits, against 0.719 and 0.720 for the monochrome model, recovering three to five times as many at-risk heartbeats at comparable specificity. Pseudo-colour encoding improved explanation localisation and stability for almost every method, and the improvement reproduced across both visits. Conclusion: The input representation is a controllable and previously overlooked determinant of both predictive performance and explanation quality. Significance: Treating interpretability as a representation-design problem offers a route towards explanations clinicians can check against known electrophysiology.
How CrossnoKaye grounds physical AI with Amazon Bedrock AgentCore
CrossnoKaye brought physical AI to heavy industry with Amazon Bedrock AgentCore. Its ATLAS platform and AURA agentic system ground AI reasoning in live plant data and run verifiable Python in isolated AgentCore sandboxes, giving plant engineers checkable, math-backed answers instead of model guesses.
Make a Robot Arm Feel Weightless with NVIDIA Holoscan 5
Picture guiding a robot arm by hand while its motors supply just enough torque to support its weight and keep the robot upright. This simple interaction, a...
Running AV Reasoning Models Within Onboard Compute and Latency Limits
Autonomous vehicle (AV) developers need reasoning models that can operate within the compute and latency constraints of an onboard system. Larger models provide...
Show HN: I abandoned my AVX2 128-bit fixed-point library
Article URL: https://github.com/arjavsharma91/v4q128 Comments URL: https://news.ycombinator.com/item?id=50434431 Points: 1 # Comments: 1
Show HN: Pg-interleave (Postgres proxy for reproducible race-condition tests)
Article URL: https://github.com/alt-f6/pg-interleave Comments URL: https://news.ycombinator.com/item?id=50437720 Points: 1 # Comments: 0
Start and Restore GPU Workloads in Seconds with NVIDIA Snapshot
NVIDIA Snapshot, a new open-source component of the NVIDIA DSX AI Factory Platform, makes initialized GPU workloads reusable across inference...
The AI Safety Debate Has Lost the Plot. We Asked 10 Experts What the Real Nightmares Are
The risk of nuclear catastrophe is real, as is the fallout of the China–US domination game (hi there, spies). But no need to panic about Skynet.
Weighted State Souping for Efficient Long-Context Retrieval
This paper was accepted at the Workshop on Personalized, Aligned, Long-term Memory for AI Systems (PALM) at NeurIPS 2026. State space models (SSMs) combine fast inference and fixed state size with competitive language-modeling performance. Recently, state souping has been proposed as a procedure whereby an SSM independently encodes chunks of tokens like documents, tool definitions, or memory records. The resulting state encodings may be cached and recombined to cheaply construct a context for downstream queries. However, both state souping and vanilla SSMs deteriorate on long, crowded…
What Is Eval-Driven Development? How to Improve AI Agents
Eval-driven development helps you build AI agents against a consistent set of metrics. Define good behavior, write the eval first, then compare experiments.
Why Is AI Slop So Frustrating to Read?
Article URL: https://zonderlabs.com/slop Comments URL: https://news.ycombinator.com/item?id=50433799 Points: 20 # Comments: 5
Introducing Claude Fable 5.2 and Claude Mythos 5.2
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.
Practice Makes Precise: At CoRL, NVIDIA and Partners Reveal How Robots Rehearse Delicate Work in Simulation
Simulation, which has long been the proving ground for robots learning to walk, roll and hop, is now helping researchers teach robots tasks that require a finer touch: aligning gears, connecting cables and assembling small components. The shift from locomotion to manipulation is taking center stage at this week’s Conference on Robot Learning (CoRL) in […]
Show HN: FELF – AppImage-like single binaries without FUSE, root, or a runtime
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
Show HN: SafeScript, a safe version of JavaScript for executing untrusted code
Article URL: https://github.com/SafeScript/safescript Comments URL: https://news.ycombinator.com/item?id=50417478 Points: 1 # Comments: 0