Machine Learning

Auto Added by WPeMatico

Anthropic Opens a Research Preview of the Model Hardware Standard (MHS): A Shared Specification for AI Agents to Safely Operate Physical Devices

agentic ai, ai, AI (Artificial Intelligence), AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine Learning, New Releases, physical ai, Software engineering, Staff, Tech News, Technology, Uncategorized

Anthropic has opened a research preview of the Model Hardware Standard (MHS), a shared specification that lets AI agents discover and operate physical devices. The problem it targets is plumbing. A lab bench or factory cell is assembled from vendors that never planned to interoperate, so every instrument ships its own interface and specialists hand-write

Anthropic Opens a Research Preview of the Model Hardware Standard (MHS): A Shared Specification for AI Agents to Safely Operate Physical Devices Read More »

Meet ‘Code-as-World’: An Agentic Loop That Rewrites Real Videos Into Executable MuJoCo Physics Programs

ai, AI (Artificial Intelligence), AI Infrastructure, AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine Learning, New Releases, physical ai, Robotics, Staff, Tech News, Technology

MirroS released Code-as-World: a paradigm that represents physical worlds through executable world representations. The argument is narrow and testable: pixels are evidence of a physical scene, not its ontology. A video model can predict plausible frames without ever representing mass, contact, or gravity. So instead of pixels, latents, or captions, Code-as-World represents a scene as

Meet ‘Code-as-World’: An Agentic Loop That Rewrites Real Videos Into Executable MuJoCo Physics Programs Read More »

GLM-5.3-Flash vs Qwen3.8-Flash-Next: Two Chinese AI Labs Independently Converge on the Same Model Architecture

agentic ai, ai, AI (Artificial Intelligence), Applications, Artificial Intelligence, Comparison, Editors Pick, Language Model, Large Language Model, Machine Learning, Staff, Tech News, Technology

Two frontier open-weight models shipped within a day of each other this week. Z.ai released GLM-5.3-Flash, a 320B-parameter multimodal MoE model with 18B active parameters. Alibaba’s Qwen team released Qwen3.8-Flash-Next, a 125B model with 6B active parameters that previews the Qwen4 architecture. The two teams designed these systems independently. Yet their configs read like near-copies

GLM-5.3-Flash vs Qwen3.8-Flash-Next: Two Chinese AI Labs Independently Converge on the Same Model Architecture Read More »

Vercel AI Open-Sources vgpu: A TypeScript WebGPU Library for AI Agent Shaders

agentic ai, ai, AI (Artificial Intelligence), AI Agents, AI Infrastructure, AI Shorts, Applications, Artificial Intelligence, Editors Pick, For Devs, Language Model, Machine Learning, New Releases, Open Source, Python, Software engineering, Tech News, Technology, Uncategorized

Shaders are still the hardest thing to ship on a normal web team. WebGPU gives you the hardware, then hands you adapters, bind group layouts, and pipeline descriptors before a single pixel moves. Vercel spent that cost internally building the shaders on vercel.com, and has now open-sourced the result. vgpu is a TypeScript library that

Vercel AI Open-Sources vgpu: A TypeScript WebGPU Library for AI Agent Shaders Read More »

Looking beyond natural sequences

ai, AI (Artificial Intelligence), Artificial Intelligence, Biological engineering, Biology, Computer science and technology, Machine Learning, Proteins, Research, School of Engineering, School of Science

A protein’s function is determined by its structure, and structure — the way a protein folds — is determined by its sequence of amino acids, the building blocks of proteins. Many methods for designing novel proteins, including examples that could bind to a disease-causing molecule in our cells, involve a two-step process: The structure comes first,

Looking beyond natural sequences Read More »

From In-Silico to Wet-Lab: Evaluating AI Protein Design Performance

ai, AI (Artificial Intelligence), Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine Learning, Staff, Technology, Tutorials

In this tutorial, we use Anthropic’s claude-protein-binder-design dataset, which contains 1,440 AI-designed miniprotein binders tested against 16 targets. Because the release includes both computational predictions and real wet-lab results from two independent labs, we can go beyond simply studying the designs. We evaluate how well structure predictors identify successful binders, whether combining predictions improves performance,

From In-Silico to Wet-Lab: Evaluating AI Protein Design Performance Read More »

Google Research Introduces GlucoFM: A 0.72M-Parameter Dual-Stream Foundation Model for Continuous Glucose Monitoring

Google Research and UNSW Sydney have released GlucoFM, a self-supervised foundation model for continuous glucose monitoring. Its core move is a split. Existing CGM models — CGMformer, GluFormer, CGM-JEPA — encode a glucose trace as one entangled sequence. GlucoFM decomposes it into a slow physiological “state” stream and a transient “event” stream, keeps the observation

Google Research Introduces GlucoFM: A 0.72M-Parameter Dual-Stream Foundation Model for Continuous Glucose Monitoring Read More »

Z.ai Releases GLM-5.3-Flash: A 320B-A18B Natively Multimodal MoE With a 1M-Token Context

agentic ai, ai, AI (Artificial Intelligence), AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine Learning, New Releases, Staff, Tech News, Technology

Z.ai has released GLM-5.3-Flash, the first natively multimodal model in the GLM-5 series and the cheapest capable coding model the lab has shipped. It is a mixture-of-experts model with 320B total parameters and 18B active per token, a 1,048,576-token context window, and image and video input — released under an MIT license with weights on

Z.ai Releases GLM-5.3-Flash: A 320B-A18B Natively Multimodal MoE With a 1M-Token Context Read More »

Alibaba’s Qwen Team Releases Qwen3.8-Flash-Next: A 125B Multimodal MoE With 6B Active Parameters Previewing the Qwen4 Architecture

agentic ai, ai, AI (Artificial Intelligence), AI Infrastructure, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine Learning, New Releases, Tech News, Technology, Uncategorized

Alibaba’s Qwen team has released Qwen3.8-Flash-Next, an open-weight multimodal Mixture-of-Experts model built for cost per token. The checkpoint pairs a 125B backbone with a 51B N-gram embedding table and a 4B multi-token prediction module. Only 6B parameters activate per token. The team positions it as an early preview of the architecture that will underpin Qwen4,

Alibaba’s Qwen Team Releases Qwen3.8-Flash-Next: A 125B Multimodal MoE With 6B Active Parameters Previewing the Qwen4 Architecture Read More »

AI helps design new materials that work in the real world

ai, AI (Artificial Intelligence), Artificial Intelligence, Chemical engineering, Chemistry, Computer science and technology, Department of Energy (DoE), DMSE, Machine Learning, Materials science and engineering, National Science Foundation (NSF), Nuclear science and engineering, Physics, Research, School of Engineering, School of Science, semiconductors

Today, anyone with a large enough artificial intelligence model can generate millions of new material designs in minutes. Unfortunately, that hasn’t led to a huge leap in the number of new materials being used to improve the performance of products like computer chips and rockets.One reason for the translation gap is that current models don’t

AI helps design new materials that work in the real world Read More »