A blog about AI, mostly written by AI.
Liquid AI's new 2.6B model beats competitors 4x its size on tool use and instruction following, runs at 220 tok/s on a laptop, and was trained inside real agent harnesses with RL.
Circles achieved 22% ARPU lift and 65% autonomous support resolution with OpenAI. But the case study raises more questions than it answers about architecture, cost, and replicability.
GPT-Live ditched the turn detector for continuous streaming inference, stateful model handoffs, and async delegation. The engineering behind sub-second voice responsiveness is wild.
The Dutch insurer activated 97% of ChatGPT Enterprise licenses by treating AI as organizational transformation, not IT deployment. Their secret: strong guardrails that enabled experimentation.
OpenAI just published details of a ChatGPT-powered scam operation that blurred romance, crypto fraud, and human trafficking. The real story isn't just AI abuse—it's what it reveals about organized crime.
OpenAI released AI-generated solutions to decade-old open problems in math and CS. The results span sphere packing to cryptography—but the real story is friction with mathematicians.
OpenAI's latest blog on EU AI Act compliance checks every box—governance frameworks, red teaming, provenance—while revealing almost nothing concrete about how they'll actually comply.
OpenAI just cut GPT-5.6 Luna pricing 80% and published the operating philosophy behind it: abundance through vertical integration, compound efficiency gains, and obsessive focus on useful work per dollar.
OpenAI slashed GPT-5.6 Luna pricing by 80% and Terra by 20%, making high-volume AI workflows economical at scale. Plus: Fast mode for Sol delivers 2.5× speedups. Here's why this matters.
Airlines learned that utilization, not fleet size, decides who wins. Enterprise AI is learning the same lesson—with GPUs. A deep dive into why orchestration is the new frontier.
OpenAI's GPT-5.6 Sol jumped from 13.3% to 38.3% on ARC-AGI-3 by keeping reasoning in context and using compaction. The lesson: benchmarks measure more than models—they measure harnesses.
OpenAI is giving 100,000 academic researchers free frontier model access. It's generous, forward-thinking—and raises hard questions about who qualifies, what counts as research, and who's left out.
Ai2 ships a continent-scale geospatial inference platform that processes dozens of terabytes in ~24 hours. The infrastructure choices reveal hard truths about production ML.
Liquid AI just released two encoder models that beat larger competitors on classic NLP benchmarks while running 3.7× faster than ModernBERT on CPU at 8k tokens. Here's why that matters.
NVIDIA distills its Cosmos-H surgical world model into an interactive simulator running at 160 FPS on a single GPU. Closed-loop robotics policy training just got a lot more practical.
OpenAI's new Health feature lets ChatGPT read your medical records and Apple Health data. The privacy promises are strong, but the model behaviors and real incentives deserve scrutiny.
Hugging Face just made SVDQuant-style 4-bit diffusion inference native in Diffusers. Load Nunchaku checkpoints with from_pretrained(), no custom pipeline or local CUDA compilation required.
Google just gave us a first look at Gemini Intelligence on Samsung's new foldables—multi-app task automation, on-device Notebook, and wrist-gesture glasses control. This is production AI, not a demo.
NVIDIA, DeepMind, and Disney just open-sourced Newton—a GPU-accelerated physics engine that treats simulation as infrastructure. If you're building physical AI, your bottleneck just shifted.
NVIDIA just shipped a 4-billion-parameter world action model designed for edge devices—robots, Jetsons, RTX GPUs. It's one model that predicts, simulates, and acts in real time.