Tech Explainer for Proximity Networking: Essential Wireless Standards
aptiv.com·14h·
Discuss: Hacker News
📡IoT Protocols
Show HN: Daily Clash Royale Card Guessing Game
clashle.app·7h·
Discuss: Hacker News
🦀Rust
The stone wall
christosdoulou.bearblog.dev·1d
🛡️Byzantine Consensus
We are a mosaic of everything we come across
raccoon.bearblog.dev·2d
🕸️Knowledge Graphs
AI and the Future of American Politics
schneier.com·1d·
Discuss: Hacker News
🎤Voice Interfaces
Monument Engine: Jx
monument.ai·2d·
Discuss: Lobsters
⚡Tokio
How to Use AI to Help with Software Engineering Tasks
newsletter.eng-leadership.com·1d·
Discuss: Hacker News, r/programming
🧩Low-code
Is the AI Conveyor Belt of Capital About to Stop?
gizmodo.com·16h·
Discuss: Hacker News
🏗️AI Infrastructure
Dimensionality Reduction in Machine Learning: Why It Matters and How It Works
dev.to·6h·
Discuss: DEV
🎯Vector Databases
Show HN: Local Full-Rank Fine-Tuning Library for LLMs with Evolutionary Methods
github.com·13h·
Discuss: Hacker News, r/LocalLLaMA
🏗️AI Infrastructure
The Quiet AI Revolution in Your Doctor's Office
dev.to·1h·
Discuss: DEV
🧠AI
AI Ethics Curriculum Evolution via Recursive Preference Learning & Adversarial Validation
dev.to·19h·
Discuss: DEV
🏗️AI Infrastructure
Active Confusion Expression in Large Language Models: Leveraging World Models toward Better Social Reasoning
arxiv.org·4d
🏗️AI Infrastructure
CIR-CoT: Towards Interpretable Composed Image Retrieval via End-to-End Chain-of-Thought Reasoning
arxiv.org·4d
🎯Vector Databases
Forecasting the Buzz: Enriching Hashtag Popularity Prediction with LLM Reasoning
arxiv.org·4d
🎙️Whisper
Chaos engineering on Google Cloud: Principles, practices, and getting started
cloud.google.com·19h
⚖️Consensus Networks
Python For Data Engineering
dev.to·4d·
Discuss: DEV
📐Data Modeling
Investigating Identity Signals in Conversational Facial Dynamics via Disentangled Expression Features
arxiv.org·7h
🎯Vector Databases
Logits Replay + MoClip: Stabilized, Low-Cost Post-Training with Minimal Forgetting
arxiv.org·1d
💻Local LLMs
A Design-based Solution for Causal Inference with Text: Can a Language Model Be Too Large?
arxiv.org·1d
💻Local LLMs