Jan Nano + Deepseek R1: Combining Remote Reasoning with Local Models using MCP
huggingface.co·5h·
Discuss: r/LocalLLaMA
📋MCP
Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning
arxiv.org·10h
📊Vector Databases
The 20+ most common AI terms explained, simply
threadreaderapp.com·22h
🧠LLM Inference
Getting an LLM to set its own temperature
amanvir.com·14h·
Discuss: Hacker News
🕳LLM Vulnerabilities
HW Security: Multi-Agent AI Assistant Leveraging LLMs To Automate Key Stages of SoC Security Verification (U. of Florida)
semiengineering.com·7h
🕳LLM Vulnerabilities
Quantum computers just got an upgrade – and it’s 10× more efficient
sciencedaily.com·8h
🔬RaBitQ
Build a Compiler from Scratch, Part 1.2: Intermediate Representation and Code Generation
blog.sylver.dev·14h
🦀Rust Compiler Internals
Speaker ID, Database Timeouts & Content Hashing
askthegame.bearblog.dev·14h
💾Prompt Caching
Flynn Was Right: How a 2003 Warning Foretold Today’s Architectural Pivot
semiwiki.com·21h
⚡Hardware Acceleration
An Analogy for Interpretability
lesswrong.com·23h
🔍AI Interpretability
The one-more-re-nightmare compiler (2021)
applied-langua.ge·21h·
Discuss: Lobsters, r/programming
🔍RegEx Engines
Scaling Pinterest ML Infrastructure with Ray: From Training to End-to-End ML Pipelines
medium.com·21h·
Discuss: Hacker News
🕯️Candle
How to use Gemini 2.5 to fine-tune video outputs on Vertex AI
cloud.google.com·22h
📊Feed Optimization
After a year in the LLM wilderness, I think the 'memory problem' isn't a bug—it's a business model. So I went a different way.
reddit.com·15h·
Discuss: r/LocalLLaMA
🪄Prompt Engineering
AI and humans see objects differently: Meaning versus visual features
techxplore.com·21h
📊Embeddings
Introduction to Problem of Language Modeling
infinitely-fallible.bearblog.dev·16h
🧠LLM Inference
June 25, 2025 Flight Tracking Workshop (4 hour) [Americas / Europe-friendly time]
bellingcat.com·14h
🪄Prompt Engineering
The Internal Inconsistency of Large Language Models
blog.kortlepel.com·21h·
Discuss: Hacker News
🪄Prompt Engineering
Polaris: A Post-training recipe for scaling RL on Advanced ReasonIng models
github.com·17h·
Discuss: r/LocalLLaMA
🗜️Zstd
Learning from Anatomy: Supervised Anatomical Pretraining (SAP) for Improved Metastatic Bone Disease Segmentation in Whole-Body MRI
arxiv.org·10h
🐘pgvector