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).
Researchers Propose PAPAV Framework: Only 3 of 64 Benchmarks Test Verification
A new paper compares computer-use agents and robots through five PAPAV functions. Of 64 benchmarks, 5 assess outcome prediction and only 3 assess result…
NUS Teaches a Model to Find What It Described: gIoU Rises From 57.5% to 68.2%
Generalized CycleGRPO links describing a region and finding it from text in a single RL loop, with no reference captions and no LLM judge. On GroundingSuite, gIoU…
TenetBench: 11 of 14 LLM Configurations Violate Professional Ethics Codes
A new Russian-language benchmark tests models against specific clauses of professional ethics codes. 11 of 14 configurations produce conflicting content on most…
Cohere taught a 7B model to assess its confidence twice, cutting calibration error by 52.5%
Claude Designed 17 Proteins Against Scorpion Toxins in 64 Hours
250 subagents vs. 4 threads: why orchestration architecture matters more than a loud model name
Six Teams from UCSB, Stanford and J.P. Morgan Release an Agent Memory Benchmark
九章云极 Alaya-DFlash2 speeds up GLM-5.3 decoding by 3.41x
Chinese cloud provider 九章云极 unveiled Alaya-DFlash2: speculative decoding speeds up GLM-5.3 by 3.41x on long inputs, such as 32k-token documents.
MemT 1.0 builds memory into the model and aims at AI self-improvement
MemT 1.0 is out: memory is meant to be a built-in model capability, not an external add-on. A story about DeepSeek and an exhausted context sparked the discussion.
Anhui Bets on Humanoids: A Robotics Park in Hefei and a 15.1 Billion Yuan Project
Lovable Launches Auto-Deletion of "Dead" Apps: 60 Days of Silence, Then the Trash
Jiqizhixin Invites NeurIPS 2026 Authors to an Offline Meetup in Beijing
Xiaohongshu speeds up its sparse-attention indexer: DoSA halves TTFT
RLSplat teaches 3D Gaussian Splatting to economize: up to 4.1× faster and 9.6× less memory
RLSplat generates exactly as many Gaussians as the budget specifies, and spends proportionally less time and memory doing it: up to 4.1× faster and up to 9.6× lower…
Stratified Sparse Attention speeds up decoding 2.96x at 1M context
The SSA sparse attention method combines deterministic top-k with importance-weighted sampling of the remainder. At 50x sparsity on 128K, it retains 85% of…