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25 percent of San Francisco’s convicted pedophiles, rapists, and sex offenders live in government-funded housing. You’re paying for predators to live in the most expensive city in America.

A Defense Manpower Data Center (DMDC) information system experienced unauthorized access of personally identifiable information by a small number of unauthorized users between October 2025 and July 2026. Read more:

KATSEYE’s arrival to pop stardom was quick, and fans are getting a behind-the-scenes peek into the turbulence of their takeoff with ‘KATSEYE: WILD HEARTS’. 💞 More details + watch the trailer: Photo: Julian Song

NextEra $NEE is leading a $22.3B Texas energy project selected by the U.S. and South Korea. Project Star will build 6.47 GW of gas-fired generation, primarily to power Related Digital’s adjacent 5 GW data center campus, with excess power going to ERCOT. Initial generation could begin in 2029.

Ask for "a lizard wearing sunglasses" and you get either no sunglasses or a distorted lizard. Google just gave the control problem behind image generation a mathematical answer. Title: How Diffusion Controller unifies and simplifies AI image generation URL: 📝 Overview Diffusion Controller reframes image generation as a continuous control problem rather than a sequence of isolated steps. It keeps the base model frozen and adds a lightweight side network to steer its behavior. ❓ Problem Solved Inference-time guidance and heavy fine-tuning methods like LoRA sit in two disconnected camps with no unified mathematical principle, leaving engineers to guess their way through balancing preference alignment against image quality. 💡 Method & Approach The side network observes intermediate denoising states and injects tiny steering corrections without touching the model's internal weights. Two implementations — a policy-gradient (PPO) approach and a reward-weighted loss approach — both include guardrails against quality degradation. This design even lets you control closed-source models you can't otherwise access. 📊 Results On Stable Diffusion v1.4, Diffusion Controller outperformed LoRA across both SFT and RWL training tracks despite touching fewer layers, hit a 90% win rate over baseline in its fully unlocked version, and delivered the best subjective quality in human evaluation on complex prompts. #ImageGeneration# #DiffusionModels#

Output token limit just jumped from 64K to a full million. Google's new frontier model is built to solve tough, long-horizon problems in one continuous pass. Title: Gemini 4 Argon: our next era of frontier intelligence URL: 📝 Overview Google's new frontier model built for software engineering, enterprise knowledge work (legal/finance), and cybersecurity defense. It's rolling out first to trusted cyber defenders through the Fairwind Program, with broader availability to follow. ❗ Problem it solves Complex, long-horizon professional tasks used to run into output and context limits. Gemini 4 Argon expands output capacity from 64K to 1 million tokens, enabling deep, sustained reasoning to finish tough problems in a single pass. 🛠️ Method Beyond the expanded token budget, it strengthens multimodal understanding, especially video and visual analysis. On safety, Google highlights four pillars: refusing harmful requests while preserving legitimate dual-use research, automated red-teaming for prompt-injection resilience, chain-of-thought monitoring that can halt execution, and sandboxed, isolated environments. 📊 Results 77.9% on DeepSWE v1.1 (state of the art on real-world long-horizon coding), #1# on AutomationBench at 51.3% for end-to-end business execution, tied for first on CWE-bench v1 (vulnerability remediation) at 68%, and 91.7% on LVBench for video understanding. 🏢 Use cases Inside Google, it beat a published quantum-optimization baseline by 40% in minutes, freed over 300 TiB of data-center memory, and helped migrate 800K+ lines of C/C++ to Rust. #Gemini4Argon# #FrontierAI#