The Google for Startups Gemini kit is here
blog.google·3h
🚀Startups
The broken rhetoric of AI
uxdesign.cc·5h
🛡️Content Moderation
Reverse Engineering the Microchip CLB Part 1: Background and Reverse Engineering the BLEs
mcp-clb.markomo.me·8h·
Discuss: Lobsters, Hacker News
🔍Binary Analysis
What Problems to Solve – By Richard Feynman
genius.cat-v.org·21h·
Discuss: Hacker News
⚛️Physics
The Distribution of Prime Numbers: A Geometrical Perspective
blog.computationalcomplexity.org·1h·
Discuss: blog.computationalcomplexity.org, Hacker News
🌳Data Structures
GCC 15: Continuously Improving
community.arm.com·1h·
Discuss: Hacker News
🦀Rust Compiler Internals
Claude 4 Sonnet is insanely powerful.
threadreaderapp.com·22h
🎭Claude
Quantum Neural Networks for Propensity Score Estimation and Survival Analysis in Observational Biomedical Studies
arxiv.org·11h
🧠LLM Inference
Probing AI Safety with Source Code
arxiv.org·11h
🛡️AI Safety
A Multi-Pass Large Language Model Framework for Precise and Efficient Radiology Report Error Detection
arxiv.org·11h
🛡️AI Safety
An ab initio foundation model of wavefunctions that accurately describes chemical bond breaking
arxiv.org·11h
🕯️Candle
AI Copilots for Reproducibility in Science: A Case Study
arxiv.org·11h
🎯Qdrant
MATER: Multi-level Acoustic and Textual Emotion Representation for Interpretable Speech Emotion Recognition
arxiv.org·11h
📊ModernBERT
Large Language Models
blog.jsbarretto.com·5h·
Discuss: Hacker News
✏️Code Editors
What Are the Environmental Impacts of Artificial Intelligence?
blog.ucs.org·11h·
Discuss: Hacker News
🖥GPUs
Exploring Graph-Transformer Out-of-Distribution Generalization Abilities
arxiv.org·11h
📊Vector Databases
Google launches Offerwall, a customizable content access tool for publishers
searchengineland.com·2h
😊Emojis
Learning-based safety lifting monitoring system for cranes on construction sites
arxiv.org·11h
🛡️AI Safety
Industrial Energy Disaggregation with Digital Twin-generated Dataset and Efficient Data Augmentation
arxiv.org·11h
📊Vector Databases
A Novel Large Vision Foundation Model (LVFM)-based Approach for Generating High-Resolution Canopy Height Maps in Plantations for Precision Forestry Management
arxiv.org·11h
📊Embeddings