Students, here are 5 key things to know when learning how to train large language models
techradar.com·1d
💻Local LLMs
Computer-vision, Pi3 and losing hackathons
mtende.blog·12h·
Discuss: Hacker News, r/programming
🖥Retro Computing
Gradual negation types and the Python type system
jellezijlstra.github.io·1h·
Discuss: Hacker News
🔬Refinement Types
Situated Software (2004)
web.archive.org·12h·
Discuss: Hacker News
🚀Indie Hacking
ToMacVF : Temporal Macro-action Value Factorization for Asynchronous Multi-Agent Reinforcement Learning
arxiv.org·2d
🔲Cellular Automata
LiLM-RDB-SFC: Lightweight Language Model with Relational Database-Guided DRL for Optimized SFC Provisioning
arxiv.org·1d
🌀Brotli Internals
Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data
arxiv.org·4h
🔍Information Retrieval
Abhigyan Khaund on the Systems Engineering Behind AI Applications
hackernoon.com·15h
🌊Stream Processing
It’s Not What You Pay, It’s How Fast You Play: A History of MEV
hackernoon.com·1d
🖥️Terminal Renaissance
GPS to ROI: Real Cost of Building a Fleet Management App in 2025
dev.to·2h·
Discuss: DEV
🔌Operating system internals
Building an AI-Powered Project Management Dashboard with Bolt.new
dev.to·1d·
Discuss: DEV
🌊Stream Processing
A Leap-on-Success Exhaustive Search Method to Find Optimal Robust Minimum Redundancy Arrays (RMRAs): New Array Configurations for Sensor Counts 11 to 20
arxiv.org·1d
🔄CRC Algorithms
Finding Order-Preserving Subgraphs
arxiv.org·1d
🕸️Graph Algorithms
oapi-codegen v2.5.0 is out
github.com·1d·
Discuss: r/golang
📜Proof Carrying Code
Project Servfail: One Year In
sdomi.pl·10h·
Discuss: Hacker News
🔌Interface Evolution
2025 Technical Guide: When to Choose Local or Cloud AI
dev.to·6h·
Discuss: DEV
🏠Homelab Federation
Creating Custom File Systems: Implementing the FS Interface 7/9
dev.to·4d·
Discuss: DEV
📋Format Specification
Building an AI-Powered Image Search Engine with Daft.ai
dev.to·1d·
Discuss: DEV
🌀Brotli Internals
Machine Learning Fundamentals: decision trees project
dev.to·1d·
Discuss: DEV
🔗Topological Sorting
From Equal Weights to Smart Weights: OTPO’s Approach to Better LLM Alignment
towardsdatascience.com·1d
🧮Kolmogorov Bounds