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).
Malaysia's Premier Anwar Ibrahim to Launch AI Digital Double with His Own Voice
Malaysia's Prime Minister Anwar Ibrahim is creating an unprecedented AI digital double with his own voice — a rare move for a head of state aimed at meeting with…
MiniMax Raises $2B for AI Model Development Through Share Offering
Chinese company MiniMax has launched fundraising of $2 billion through new share issuance and convertible bonds, joining the wave of AI investments.
Ragas, DeepEval, RAGChecker, Opik: Which RAG Metrics Actually Work
A study compared four popular RAG metrics libraries on data from real business systems and identified which of them correlate with human quality assessments.
AWS published 6 approaches to optimizing MCP tools to save context
The Era of 100,000 GPUs: China Achieves Independence in AI Computing
LangChain vs LlamaIndex: how developers choose a framework for LLM applications
Microsoft releases Aurora 1.5: a model for weather and climate forecasting
Baidu updated its Assistant so it can handle 90% of work tasks
Chinese company Baidu has updated its AI assistant so it can handle complete work tasks more effectively instead of individual questions.
Apple identified when on-policy distillation helps model training
Apple ML researchers identified the conditions under which on-policy distillation is effective for training reasoning models, and when it may be ineffective or even…
Self-Reflective Program Search: Apple improved LLM performance with long contexts
Facewatch launches police integration: facial recognition in stores in 4 seconds
Apple developed TGPO to train video models to understand time
Anthropic surges to a $1.2 trillion valuation — up 550% in a year
SynthAVE: when 21 models labeled 12 thousand products instead of humans
The SynthAVE dataset: 12,726 products in 4 languages annotated by an LLM arena of 21 judges. Results match manual annotation at 95.2%.
DeLS-Spec accelerated LLM inference without retraining models
Researchers proposed DeLS-Spec—a method for accelerating LLM inference by adding a lightweight adapter trained separately from the base model.