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TL;DR - GLM-5.2 scored 77.8 on SWE-bench Verified and 56.2 on Terminal Bench 2.0, surpassing every open-weight model to date and beating GPT-5.5 on multiple long-horizon coding benchmarks. - The model costs roughly $1.40 per million input tokens and $4.40 per million

Key Takeaways - Ford's bet-everything-on-AI quality control strategy imploded. Billions in recalls. Defects everywhere. Course correction took three years. - The company quietly rehired 350+ veteran engineers it had replaced. Bloomberg called them "gray beards." - Ford's own VP said it straight: they "

TL;DR - Doubleword.ai ran all benchmarks from Artificial Analysis. Average lag between open-weight and closed-source LLMs sits at a flat level. Hasn't moved. - Coding's the outlier: open models improved significantly on that specific index. - Everything else is getting worse, not better. Some

Three hundred a month for Grok access felt steep until I did the math on AI infrastructure at scale. That number stuck in my head when OpenAI dropped GPT-5.6 Sol's benchmarks this week. 750 tokens per second. Not a research preview. Not a theoretical paper. Something you

How AI Read a Herculaneum Scroll: Vesuvius Challenge Breakthrough TL;DR - Vesuvius Challenge read an unopened Herculaneum scroll — 2,000 Greek characters unseen since ancient times. - A convolutional neural network detected ancient ink ghosting inside carbonized papyrus using X-ray CT scans from Diamond Light Source. - Luke Farritor

TL;DR - IBM crammed 100 billion transistors into something smaller than your fingernail using 3D nanostack tech. - That means 50% more oomph, or 70% less power drain versus their old 2nm nodes. - Training one LLM? Burns 284 tons of CO2. Roughly 125 round-trips JFK to PEK. -