New AI models reviewed and compared, how they work, and what the labs behind them are betting on.
Most read by people in Engineering, Executives and Legal & Compliance.
If ChatGPT feels worse lately, check its reasoning level. Here is where the setting lives on mobile, what each plan offers, and why the model can't say.
Meta's Muse Ember matches Haiku 5.5 on the Artificial Analysis index at about a third of the cost. See Automation Bench, OS World results and delegation tips.
Solve Intelligence builds AI for patent attorneys, used by 700+ IP teams and backed by $55M. How it started and why patents resist generic chatbots.
Underdog Woof is a 40.6 MB English text-to-speech model that runs on a CPU with NumPy. Setup steps, voices, test results and the non-commercial license catch.
Nvidia's board is probing a Jensen Huang relationship tied to Megaspeed while 600,000 H200s wait in Hong Kong. The timeline, export rules and stakes.
Qwen4 Max preview tested on Blender animation, an 82-language naming task, satellite map reasoning and seat belt laws, plus where it struggled.
Boston Dynamics put scooter wheels on Atlas, trained rolling in simulation, and landed a 360 spin first try. Here is how it works and why it matters.
Underdog Woof claims a 1.42% word error rate. Hands-on tests of Juno and Mira on phone numbers, prices, titles and dates show where it slips.
Nvidia shrank a 120B model to a 74B model with 2-bit experts that fits in 24 GB. Here is the pruning, distillation and QAD recipe, and why it matters.
People split on saying please and thank you to AI. Here are the reasons: token cost, water use, better answers, habit and hedging against a robot takeover.
Anthropic reportedly tracks progress on a composite benchmark in log-odds. Here is how saturation hides gains and why Model 4 is hard to measure.
METR's audit of Anthropic and an amended S-1 point to AI-led research rising from 1% to 26%, a 1.9x speedup estimate, and heavy redactions.
AREX-2 is BAAI's 27B open-weights model trained to try, check and revise for hours. See its MLE-Bench Light scores and what it means for harnesses.
Inkling 2 Small is a 594B-parameter, 17B-active multimodal MoE. Hands-on tests in HTML, multilingual output, circuits and vision, plus benchmark standing.
Local votes blocked data centers while AI use climbs. Here is how that hits neo clouds, big tech, offshore siting, overbuild risk and orbital compute.
DSpine is Tencent's roughly 2B draft model for Qwen3.8-27B. See how it speeds up speculative decoding and how it differs from DFlash2 and Eagle 3.
Clover from Diffuse Space AI is a 35B diffusion language model with 3B active parameters. See how it works and how it fared against Qwen 3.6 Flash.
Traction raised a Series D at a $1.4B valuation with over $100M ARR. Here is how its sensors and AI predict failures in industrial machines.
How Traction won industrial buyers: 88 site visits in year one, an SDR as first hire, up-front risk assessments and 2,500 on-sites a year.
Croton Alpha is a free-to-try stealth model with 1M-token context for subagents. See what is known and how it did on coding, vision and translation tests.
MIT's Sparks of Weight Space Programming paper has GPT-6 Astra read and edit another model's weights, lifting a small Qwen's math from 7.9% to 48.1%.
Meta's Muse hit 10 million setups in six weeks. Here is who built it, how a team under 200 did it, the polish details, and the cost-to-serve questions.
Tencent Hy4 adds vision and computer use over the text-only preview, reports a 75.2 Apex Agents score, and is API only for now. Weights are promised.
Ripple-65B is a dense 80-layer transformer where all 65B parameters run per token. How it differs from MoE, plus its attention tweaks and training.