Curated coverage of frontier model launches, AI framework updates, agent skills, and peer-reviewed research milestones. Original summaries with engineering takeaways — never copy-paste.
TL;DR: this is just a thought dump about how I moved from network training to deployment and why I am making peace with (maybe) not getting back to model training, nothing too interesting. I used...
Anyone in the biomedical and ai/ml research space? I’m looking to connect and collaborate on research projects.
I know AI use must be disclosed, and I'm fine with it. However, I'm being careful on not using LLMs to actually check my review (more than prose-wise) and see if it catches something important in...
TL;DR: this is just a thought dump about how I moved from network training to deployment and why I am making peace with (maybe) not getting back to model training, nothing too interesting. I used...
Accepted at NeurIPS 2026 TLDR: The paper presents a library of synthetic time series generators and augmentations to train time series foundation models, in their case a DeltaProduct based linear...
Asmsense is a dataset and a small model (Qwen3-8B + LoRA) for naming and describing functions in stripped binaries. I compiled permissively licensed C projects myself, so every function has its...
I built GPT-2 small and a KV cache in PyTorch as a learning project, then compared the mathematical savings with measured latency and memory. I have published the implementation and a detailed...
I'm considering building customizable ML software for businesses, mainly focused on data classification and anomaly detection. The idea is to develop a reusable ML framework that can be adapted...
A Meta spokesperson insisted that the updated terms did not reflect a change in the way Meta crawls the web.
Hey, CS student here. for the past few days I've been building DenseCore, a small deep learning framework in rust with a pytorch-like python API.
The data comes from Vercel's AI gateway, a unified API service similar to OpenRouter.
Weekly intelligence report tracking velocity across 197 open-source AI repositories. Key findings include an 84% surge in FastMCP server implementations and a shift toward hybrid dense-sparse RAG retrieval.
An architectural comparison of leading open-source AI agent frameworks in 2026. Learn when to use state graphs, multi-agent swarms, or minimal tool loops.
A practical guide to deciding between Retrieval-Augmented Generation (RAG) and model fine-tuning (LoRA/PEFT) for enterprise LLM applications.
The official Model Context Protocol server for secure filesystem access — read, write, search, and navigate files from AI clients within configured directory boundaries.
Anthropic's official Claude Skills for working with document formats — fill, merge, and extract data from PDFs, Word files, PowerPoint decks, and Excel spreadsheets inside agent workflows.
Reverse engineer anything with agents, from app behavior down to native binaries.
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Stay ahead with real-time RSS updates on frontier models, tool frameworks, and research papers. Compatible with Feedly, Inoreader, Slack, and Google News aggregators.
