31 related articles

LLM training explained as baking a cake: from data ingredients and architecture recipes to compute baking and fine-tuning alignment — an intuitive metaphor for pre-training, gradient descent, and RLHF.

CMU professor David Brumley reveals how RL trains AI for cybersecurity offense, exposes flaws in current benchmarks, and demonstrates sandbox escapes on Chrome V8.

UnFlow is an open-source tool that models ML experiments as directed graphs instead of flat lists, automatically building experiment lineage by tracking code and parameter changes.

Learn how to use GitHub Copilot's Power Platform Skills plugin to generate, modify, and debug Power Automate cloud flows with natural language, including setup, Azure auth, demos, and cost analysis.

Deep dive into how the open-source library llm-sketchkit uses HLL++, Bloom filters, MinHash and other probabilistic data structures to solve high-cardinality and privacy challenges in LLM telemetry.

Mem0 is an AI memory middleware for developers, providing a persistent memory layer for AI agents and apps to solve LLM cross-session amnesia.

A deep dive into the complete workflow of training a 1.3B parameter LLM from scratch, covering Transformer architecture design, data preparation, and distributed training optimization.

MCP-Billing is a self-hosted Next.js boilerplate providing OAuth 2.1 auth, Stripe usage billing, API key management, and Redis rate limiting for MCP servers—one-time €79 payment with no revenue share.

Exploring whether the ACM Digital Library should open to LLM training. Analyzing the value of academic corpora for AI, data exhaustion concerns, copyright battles, and pragmatic paths including licensing and RAG.

Global airlines operated over 150,000 flights in a single day, setting a civil aviation record. This article analyzes the drivers, ADS-B tracking technology, high-density airspace challenges, and AI applications in air traffic optimization.

AI research automation will look more like data cleaning than inventing the Transformer. Explore how automating 60%-80% of repetitive research work reshapes the AI research paradigm.

Why AI research automation looks more like data cleaning than inventing the Transformer. Exploring the value of automating 60%-80% of repetitive research work and how human-AI collaboration reshapes the research paradigm.

Poolside launches Laguna open-weight model after 18 months of silence, pitting 118B parameters against Kimi K3's 2.8 trillion. Can Silicon Valley's open-source push close the gap with Chinese AI?

Poolside releases its Laguna open-weight model after 18 months of silence, challenging Moonshot's Kimi K3 with 118B vs 2.8T parameters. Can Silicon Valley close the gap with Chinese AI?

Build a local AI knowledge base with MiniMax M2 in OpenCode: source tracing, fact vs. opinion separation, conflict preservation, and timeliness management.

How Boundary built a self-healing AI Agent loop that automatically writes BAML code, discovers bugs, and generates fix PRs — a practical software factory with deduplication, human-in-the-loop leverage points, and extensible multi-loop design.

PawFlow decouples vision and reasoning into two models, letting a text-only LLM reliably control a Linux desktop. A deep dive into its dual-model architecture, pre-click guard, and caching strategy.

Knowing how to call an API doesn't make you an AI engineer. This article breaks down the complete skill structure of an AI application engineer, covering Python fundamentals, LLM fine-tuning, Agent development, and enterprise projects.

SGLang's team converted expert knowledge into agent skills, achieving 71.4% throughput gains, TTFT reduced from 456ms to 168ms. A deep dive into agent-assisted kernel optimization methodology.

ManagedAgents.sh is a model-agnostic managed agent platform from OpenComputer, supporting Claude, Pi, and Codex runtimes with Slack and GitHub integration.