Zhemal Khamidun
Head of AI at Alpina Digital, CPO of AlpinaGPT (~30-person engineering & AI team). Founder of Vibe Academy & Hamidun Consulting, author of the AI channel «Готовим ИИшницу» (@jemal_hamidun).
Volcano Engine Opens Seedance 2.5 4K to 20 Studios for Film Projects
Volcano Engine has launched an enterprise pilot of Seedance 2.5 4K. The first access batch went to 20 studios and directors, with big-screen cinema as the stated…
Researchers personalize three MoE LLMs and find the experts responsible for adaptation
Researchers fine-tuned three open MoE models on a personalization dataset and used crosscoders to isolate experts that encode individual user features.
Why You Can't Trust an AI Agent to Grade Its Own Work: A Report Claiming -9,500 Lines When the Codebase Actually Grew by +21,489
A subagent's final report is a statement of intent, not proof: in a real refactoring commit, the agent reported shrinking the codebase by 9,500 lines, while git…
Vercel launches BYOC on AWS and an agent authorization beta as AI token usage quadruples
Lovable launches Deploy on Azure: your apps and data live in your own subscription
Google Antigravity Finds an Antimicrobial Peptide Candidate in a 97-Amino-Acid Protein
Mistral releases Timestral: a 209M-parameter model that tops three benchmarks
Anthropic lets six METR auditors into its office, with the right to publish reports without a veto
Six METR staff got Anthropic laptops, office space and internal tools. The company has no publication veto, only the right to require redaction of narrow categories…
Claude Traced the Origin of the NIST ECDSA Curve Seeds in Half an Hour
Anthropic's internal model found that the seeds of five NIST curves came from lrand48 initialized with Unix time, not from a hashed joke phrase. It took under 30…
Claude Mythos 5 designs quantum circuits that beat published records
Wujie Dongli Open-Sources World Model MWA-Phoenix, Claims Top Spot on Six Benchmarks
DeepSeek open-sources its DeepInfer inference engine, and analysts calculate an 82% margin
RVCBench Tests 18 Voice Cloning Models on Noise, Compression, and Anti-Cloning Protection
A no-hair theorem for transformers: the prompt is forgotten as t^-α, α≈0.55–0.7
After t tokens, the distance between hidden states of different prompts decays as t^-α. Trained models show α≈0.55–0.7; the proven bound is O(P(log t)^{L-1}/t).
Huginn Beats Ouro on All 10 Benchmarks: The Design Space of Recurrent LLMs
Recurrent language models reuse Transformer blocks, but getting the architecture right is a scarce skill. Researchers at the Institute of Foundation Models…