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machine-learning

163 posts

Jul 15, 20267.50
Llm.c Ported to Mojo with Metal Kernels: 1.72x Faster than PyTorch MPS
The Mojo port of llm.c with Metal kernels achieves 1.72x faster performance than PyTorch MPS.
gpu low precision machine-learning mojo
Jul 14, 20267.50
CTA-Pipelining: A Latency-Oriented Scaling Method for Multi-GPU Systems
CTA-pipelining enhances performance in multi-GPU systems by focusing on latency-oriented scaling.
gpu latency machine-learning parallelism
Jul 13, 20267.50
Your RAG Eval Is Checking the Receipt, Not the Patient
Explore the risks of entity attribution failures in clinical RAG systems and how to improve evaluations.
ai evaluation healthcare machine-learning
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commitbrief.com
Jul 13, 20267.50
No Confirmed Details on Claude Opus 5 Release
The release date for Claude Opus 5 is uncertain. Anthropic emphasizes the need for a new model.
ai machine-learning modeling software
Jul 12, 20267.50
Claude Code Sends 4.7x More Tokens Than OpenCode
Claude Code shows a significant token transmission advantage over OpenCode. Key insights into cost and performance for engineers.
ai cost analysis machine-learning open-source
Jul 12, 20267.50
How Discord Creates Insights from Trillions of Data Points
Discord analyzes data to enhance community safety and inform strategies. With over 15 trillion records, data analysis is critical for decision-making.
analytics bigquery cloud-computing data
Jul 9, 20267.50
Trendyol Speeds Up Search Ranking Model Deployment
Trendyol built a config-driven ranking platform that turns a multi-day Go deployment process into a single YAML file, cutting model lead time dramatically.
config-driven e-commerce machine-learning mlops
Jul 7, 20267.50
How to Design a Cancer Vaccine: Neoantigens and MHC Science
UNC's PIRL lab founders discuss neoantigen detection, MHC prediction, and the engineering challenges of personalized cancer immunotherapy in a three-hour deep dive.
bioinformatics cancer vaccines immunotherapy machine-learning
Jul 7, 20267.52
New study finds language models memorize about 3.6 bits per parameter
Researchers unveil a method to measure LLM memorization capacity, finding GPT-style models store roughly 3.6 bits of information per parameter, with implications for grokking and scaling.
llm machine-learning memorization model-capacity
Aug 17, 20267.40
AutoDesign: Meta-Harness Optimization for Long-Horizon Agentic Design
AutoDesign optimizes long-horizon design with a meta-harness, enhancing human preferences in media output.
ai automation design machine-learning