LLM-Based Instance-Driven Heuristic Bias in the Context of a BRKGA
researchgate.net·1d·
Discuss: Hacker News
🪜Recursive Descent
Solving Reproducibility Challenges in Deep Learning and LLMs: Our Journey
ingonyama.com·2d·
Discuss: Hacker News
🗺️Region Inference
A case for learning GPU programming with a compute-first mindset – Maister's Gr
themaister.net·3h·
Discuss: Lobsters, Hacker News, r/programming
🔗Language Toolchains
Lazy text capitalization with low latency large language models
blog.florianschulz.info·2d·
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🔄Incremental Lexing
State of the Art of AI Tools in Micro-Frontend Architectures • Luca Mezzalira • GOTO 2025
youtube.com·3h
💬Smalltalk VMs
Understanding the KV Cache (feat. Self-Attention)
dev.to·8h·
Discuss: DEV
🔄Subinterpreters
Embracing the parallel coding agent lifestyle
simonw.substack.com·15h·
Discuss: Substack
⚡Live Coding
WASM in the Kernel: Tales of Triumph and Trouble
riptides.io·2h·
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🌐WASM Runtimes
Stochastic Activations
gonzoml.substack.com·1d·
Discuss: Substack
🗺️Region Inference
Is Odin Just a More Boring C?
dayvster.com·4h·
Discuss: Hacker News
🐹Go Internals
BULaMU-The First Luganda Large Language Model Trained from Scratch
reddit.com·1d·
Discuss: r/LocalLLaMA
🌱Minimal ML
Benchmark: Spark vs. Ray Data vs. Daft on Multimodal Workloads
daft.ai·2d·
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🗺️Region Inference
Eliminating the Precision–Latency Trade-Off in Large-Scale RAG
thenewstack.io·2d
🔍Text Indexing
Why do LLMs freak out over the seahorse emoji?
vgel.me·13h·
Discuss: Lobsters, Hacker News
🔍Parsing Algorithms
A grand week
blog.mitrichev.ch·1d·
Discuss: blog.mitrichev.ch
🧩Constraint Solvers
It's Almost Time for Python 3.14 and Other Python News
realpython.com·1h
💬Interactive REPLs
why & how i learnt ML
abinesh-mathivanan.vercel.app·1d·
Discuss: r/programming
🔍ML Language
Understanding the 4 Main Approaches to LLM Evaluation (From Scratch)
magazine.sebastianraschka.com·1d·
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🌱Minimal ML
CPU Cache-Friendly Data Structures in Go: 10x Speed with Same Algorithm
skoredin.pro·9h·
Discuss: Hacker News
⚡Cache Optimization
Retrv-R1: A Reasoning-Driven MLLM Framework for Universal and Efficient Multimodal Retrieval
arxiv.org·11h
🪜Recursive Descent