Human review is emerging as the backbone of AI evaluation, with teams using domain experts to build golden datasets that power increasingly accurate automated scoring systems over time.
Chinese AI models are seizing over 60% market share on developer platforms, with costs up to nine times cheaper than American rivals like Anthropic, threatening the massive $800 billion-plus valuations OpenAI and Anthropic are counting on ahead of their upcoming IPOs.
Google launches Agent Executor and Agent Substrate, two open-source tools designed to power massive, long-running AI agent workflows spanning hours or days, with Kubernetes-based infrastructure capable of scaling to hundreds of millions of agent instances.
Andrej Karpathy's free 'Neural Networks: Zero to Hero' course on GitHub is empowering learners worldwide to build GPT models from scratch through 8 hands-on video lectures covering everything from backpropagation to Transformer architecture and Byte Pair Encoding tokenization.
Spotify engineers reveal a powerful two-stage AI development strategy, combining LLM evaluations and A/B testing in a feedback-driven funnel that filters weak candidates early and validates real-world impact, making both tools smarter over time.
A GitHub repository featuring 42 advanced Retrieval-Augmented Generation tutorials has exploded past 27,400 stars, reflecting surging demand from AI developers seeking hands-on guidance across cutting-edge RAG architectures including Graph RAG, RAPTOR, and Self-RAG.
Google launches Gemini 3.5 Flash, a frontier AI model four times faster than competitors, now available globally, while introducing Gemini Spark, a personal AI agent running 24/7 on users' behalf, set to enter Beta for Google AI Ultra subscribers in the US next week.
A staggering 63% of workers admit to lying about their AI skills, with Gen Z topping the charts at 80%, as automation fears drive a credentials crisis that leaves businesses vulnerable and exposes a dangerous gap between claimed and actual AI competency.
A new open-source CLI tool called 'whichllm' instantly scans your hardware and recommends the best local AI models you can actually run, ranked by real benchmark data from top leaderboards with a single command.
LLM Wiki v2 revolutionizes AI knowledge management by introducing decaying confidence scores, a typed knowledge graph, hybrid search, and self-healing automation that keeps knowledge bases accurate, scalable, and production-ready with minimal human oversight.