World Models in 2026: Genie 3 at 24 fps, Cosmos 3 at 64B, V-JEPA 2 Planning in 16 Seconds, and an $8.2B Exit to AMD
What a world model is in 2026 and what actually shipped: Genie 3 at 720p and 20 to 24 fps for a few minutes behind a $249.99 subscription, World Labs' Marble and Atlas and the $8.2 billion all-stock sale to AMD, NVIDIA Cosmos 3 at 64B, 16B and 4B under OpenMDW 1.1, V-JEPA 2 planning a robot action in 16 seconds against Cosmos's four minutes, LeCun's AMI Labs raising $1.03 billion at $3.5 billion, the Physics-IQ ceiling of 29.5 out of 100, what inference costs, and a V-JEPA 2 embedding script I ran on a laptop CPU.
14 minOct 5, 2026GPU Clouds in 2026: H100s at $2.59 an Hour, $104B of CoreWeave Backlog on $35B of Debt, and a Six-Year Bet on Silicon
The GPU rental economy from filings and price pages fetched on 5 October 2026: H100 hours that fell from about $8 in 2023 to a $1.70 trough in October 2025 and recovered to $2.59 on the transacted index while list prices rose 25 percent; CoreWeave's $2.58B quarter, $103.7B backlog, $35.1B of debt from 15 percent DDTLs to a 5.9 percent A3 facility, and Microsoft at 67 percent of 2025 revenue; Nebius, Lambda, Crusoe, Oracle's $664B RPO and NVIDIA's $105B of guarantees; who books servers over 5, 5.5 or 6 years and what Burry's $176B means; and an own-versus-rent break-even calculator.
13 minSep 9, 2026Zero-Knowledge in 2026: Ethereum Blocks Proven in 3 Seconds for a Third of a Cent, a 52-Bit Security Gap, and Google Wallet Proving Your Age
Where zero-knowledge proofs actually stand: the Ethereum Foundation's real-time proving definition and the measured numbers on ethproofs (from 16 minutes and $1.69 to 3 seconds and $0.003 a block on consumer GPUs), why the security certification is the hard part (a 52-bit gap between the proven and claimed soundness of the hash used), the zkVM bugs fuzzers found this year, the L2 landscape at $43 billion with zero Stage 2 rollups, and the non-crypto uses shipping now: Google Wallet's ZK age proofs, the EU wallet's December deadline, zkML and zkTLS. Plus a proof you can generate on a laptop.
14 minSep 9, 2026On-Device Inference in 2026: 160 Tokens a Second on a Laptop, a 2-Bit Model in Every iPhone, and the Bandwidth Arithmetic That Decides What Stays Local
What actually runs on the device now: Apple's 3B model trained at 2 bits and the WWDC26 framework that lets any model plug in, Gemini Nano inside AICore, Windows ML and the quiet replacement of Phi Silica, the NPU TOPS numbers and why they are the wrong metric, the small-model field from Gemma 4 E2B to Qwen3.5-2B to LFM2.5 with licences, measured decode speeds from Google's own tables and an independent phone benchmark, the runtimes (llama.cpp with multi-token prediction, LiteRT-LM, ExecuTorch 1.0, MLX), the memory-bandwidth arithmetic that predicts all of it, and the model-extraction attacks nobody has fixed. With commands to run one today.
14 minSep 9, 2026AI for Science in 2026: One Phase III Trial, Two Operational Weather Models, and Erdős Proofs Nobody Wants to Read
What has actually been validated outside the lab that made the claim: rentosertib's Phase III start, ECMWF and NOAA running AI forecasts operationally, Evo 2's viable phage genomes, the Erdős-problem scoreboard and its rediscovery problem, the GNoME and MatterGen materials that turned out not to be new, and the licence and pip-install status of every open model an engineer can run this week.
16 minSep 9, 2026AI Power in 2026: 485 TWh, a 0.3 GW Stargate, a 116 GW Turbine Backlog, and 1,800 MW That Dropped Off the Grid in Seconds
The electricity numbers behind AI, kept honest: IEA's 485 TWh for 2025 and 950 by 2030, LBNL's 4.7 percent of US power heading to 12, what a prompt actually costs (0.24 Wh at Google, 30 times more in reasoning mode), which gigawatt campuses are energised versus announced (Stargate Abilene at 0.3 of 1.2 GW), where the power comes from (a 116 GW gas-turbine backlog with 2031 slots, nuclear restarts in 2027, one SMR construction permit), what the grid operators are doing about 233 GW queues and 1,800 MW load-loss events, rack power from 132 kW to 600 kW, and a script to measure your own job's energy.
14 minSep 8, 2026Robot Foundation Models in 2026: 500,000 Hours of Human Video, 50-Step Action Chunks, and a Winning Score of 0.26
What vision-language-action models actually do, from π0's flow-matching action head to Gemini Robotics 2 and GR00T N1.7; who shipped humanoids (Unitree 5,500, AgiBot 15,000) and who didn't (Tesla, zero); the teleoperation behind the demos; and the benchmark numbers that say a home robot is not close. With a LeRobot dataset I loaded this morning.
14 minSep 8, 2026Confidential Computing for AI in 2026: Apple Moved to Google's TEEs, a $1,000 Interposer Broke the Keys, and Firecracker Still Can't Do It
What a hardware enclave actually promises for an AI workload, what it costs (4 to 28% depending on what you measure), what broke it this year (TEE.fail, Battering RAM, WireTap), who runs inference in one (Apple, Google, Meta, a dozen startups) and who doesn't say (OpenAI, Anthropic). Plus the state of SEV-SNP, TDX and Arm CCA in the kernel, why my microVM platform cannot offer it yet, and the commands to verify an attestation yourself.
15 minSep 7, 2026Quantum Hardware in 2026: Below Threshold, Not Yet Useful, and the Estimates That Fell 200x
Google is below the surface-code threshold, Quantinuum is public, IBM claims advantage three times in one day, and the qubit count needed to break RSA-2048 dropped from 20 million to under 100,000 on paper. What a systems engineer should take from all of it, with a runnable error-correction simulation.
15 minSep 7, 2026LLM Inference in 2026: Prefill Is a Different Machine Now, and the KV Cache Has a Disk Tier
vLLM 0.28, SGLang on 400,000 GPUs, NVIDIA Dynamo 1.0 and llm-d in the CNCF all converged on the same architecture: split prefill from decode, route on cached prefixes, page the KV cache to CPU and SSD, and run MoE experts wide across a rack. What changed this year, with the papers, the flags, and the prices.
15 minSep 6, 2026Neuromorphic Computing in 2026: Real at Microwatts, Not for LLMs
Intel archived Lava and went quiet. BrainChip shipped production silicon. Sandia runs a billion neurons. An infrastructure engineer's honest read of where spiking hardware actually wins, with benchmark numbers and a runnable SNN.
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