Bryan Cantrill's 'The Peril of Laziness Lost' argues that LLMs have zero cost to write code and no motivation to abstract. Humans must serve as the 'deletion engine' or systems will bloat endlessly.
I tested local Vision LLMs (Gemma 3, Qwen2.5-VL, Llama 3.2 Vision, Gemma 4) to see if they could look at character illustrations and pixel art and generate RPG-style stats in JSON format.
colleague.skill, yourself-skill, nuwa-skill and other 'human distillation' OSS tools are exploding in popularity, primarily in China. Seeing a tool that distills colleagues, I wondered 'what if I distilled myself?' and researched how.
UC Berkeley's RDI team demonstrated that major benchmarks including SWE-bench and WebArena can be manipulated to near-perfect scores without completing any tasks. They identified 7 vulnerability patterns and released BenchJack, an automated benchmark attack tool.
Four Japanese tech giants form a new company backed by mega-banks and Nippon Steel to build a trillion-parameter foundation model for physical AI, with roughly ¥3 trillion in combined public-private funding.
Based on the 2025 Maintainers Summit consensus, coding-assistants.rst was merged into the Linux kernel, establishing rules for AI-assisted contributions: no Signed-off-by for AI, Assisted-by tag attribution, and full human responsibility.
A research project reverse-engineered Google DeepMind's SynthID image watermark using FFT-based spectral analysis. The V3 bypass achieves 91% phase removal while maintaining SSIM 0.997. Is removing an invisible watermark copyright infringement? Analysis from DMCA, EU AI Act, and Japanese law perspectives.
Sentence Transformers v5.4 adds multimodal support. Eight embedding models and four rerankers including Qwen3-VL and NVIDIA Nemotron can now be used through a unified API.
Meta unveils Muse Spark, the first model from its new Meta Superintelligence Labs. The Scale AI acquisition, the shift from open-weight to proprietary, multi-agent reasoning via Contemplating mode, and the evaluation awareness problem.
Zhipu AI's GLM-5.1 is a 744B MoE (40B active, 200K context, MIT) targeting long-horizon agent tasks. Hits 58.4% SOTA on SWE-Bench Pro (edging out GPT-5.4 and Claude Opus 4.6) and sustains performance across 8-hour sessions with 6,000+ tool calls without degradation.
9 Japanese-specialized LLMs as of April 2026 — LLM-jp-4 (11.7T tokens from scratch), PLaMo, Nemotron Nano 9B JP (#1 sub-10B on Nejumi 4), Swallow 30B-A3B, Namazu — broken down by whether they were scratch-trained, continued pre-trained, or post-trained, with size, license, benchmark scores.
WordPress staple plugin ACF 6.8 adds Abilities API integration, automatic Schema.org structured data, and WP-CLI commands. How AI agents can now discover and manipulate WordPress content models.
