This Is Donald Trump’s AI Brain Trust
“It’s not an argument with two sides, it’s an argument with 10 sides,” one senior administration official tells WIRED about how US AI policy is being shaped.
Curated AI coverage from TechCrunch, MIT Technology Review, WIRED and other top global tech media. Please cite this site when republishing.
“It’s not an argument with two sides, it’s an argument with 10 sides,” one senior administration official tells WIRED about how US AI policy is being shaped.
Forget YouTube videos—frontier physical AI models need multiple camera angles, dense annotation, and soon, brain wave readings.
"The first autonomous agent cyberattack is an unprecedented event. It deserves an unprecedented response!"
On the latest episode of Equity, we discussed why Moonshot AI's Kimi seemed to panic Silicon Valley and Wall Street.
A running look — in reverse chronological order — at the bigger tech companies that have announced significant layoffs this year with AI as a stated factor.
A close call in Northern Virginia revealed just how poorly data centers respond to grid disruptions. Here's how to fix the problem.
At libraries around the country, "Avoiding AI" workshops have elicited unprecedented demand.
Plus: Russian hackers are trying to steal US nuclear scientists’ emails, the State Department bans known scammers from entering the United States, and more.
OpenAI's fancy new AI keypad will be a lot of fun for some, while many others are probably not going to touch it.
The neolab is betting that automating routine computer tasks will soon outpace coding as AI's biggest use case.
Models are improving quickly, but the cheaper options are often good enough.
"Here’s a more natural, flowing version of that section..."
Machine learning has moved beyond data centers into battery-powered devices with milliwatt power budgets. MLPerf Tiny provides a fair, architecture-neutral benchmark to compare performance and efficiency across radically different ultra-low-power systems.
MLPerf Inference introduces a new Agentic Inference benchmark targeting multi-turn agentic workloads such as coding assistants and workflow agents. It uses real-world traces to evaluate inference serving stacks under long context, KV-cache reuse, and variable output lengths.
MLCommons introduces the new Edge Agentic Inference benchmark in MLPerf Inference v6.1, using Qwen3.6-27B with Q4_K_M quantization to measure accuracy and latency for on-device agentic LLM workloads. Submissions are due July 31, 2026.
At Google Cloud Next 2026, MLCommons Medical AI Working Group and Google Cloud announced that MedPerf, MLCommons' federated benchmarking orchestrator, now supports Google Cloud's Confidential Computing capabilities, demonstrated through a clinically relevant brain tumor segmentation scenario to protect both patient data and AI model IP.
Accelerating SGLang HiCache with Netpreme X-Mem™ MPUNetpreme TeamJuly 8, 2026 Netpreme X-Mem™ Memory Processing Unit (MPU) makes SGLang HiCache faster and more scalable by augmenting the slower Host D
DSpark in SGLang: Speculative Decoding with Confidence-Driven, Variable-Length VerificationSGLang TeamJuly 6, 2026Speculative decoding trades extra compute for fewer decode steps, and the trade sours
Bringing DeepSeek-V4 Flash RL Training to AMD Instinct MI355X GPUs with MilesAMD & Miles TeamJuly 10, 2026DeepSeek-V4 RL is now supported in Miles on AMD Instinct™ MI355X GPUs with ROCm™! RL requi
Serving GLM5.2 NVFP4 Agentic Workload with SGLang: Reaching 500 TPS in 2 WeeksSGLang TeamJuly 14, 2026TL;DR More than 500 TPS on 8xB300 (bs=1) Sync free speculative decoding for GLM 5.2 MTP Built-in I