Pure Storage Data Stream is an AI pipeline data dream
blocksandfiles.comยท1d
๐Ÿ Local-first
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Show HN: GlitterIDE The next level Scratch-inspired coding tool
glitter.nzยท11hยท
Discuss: Hacker News
๐Ÿฆ€Rust
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A community-designed experiment tests open questions in predictive processing
thetransmitter.orgยท6h
๐Ÿค–LLM
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Scientists unveil digital twin tech to slash power losses in energy storage systems
techxplore.comยท18h
๐Ÿค–LLM
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Code Rewrites Often Solve the Wrong Problem
stevenstuartm.comยท1dยท
Discuss: DEV
๐Ÿค–LLM
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Integrated microoptical system for continuous fluorescence monitoring of microtissues
nature.comยท2h
๐Ÿค–LLM
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Loom: Universal AI Runtime for Local, Cross-Platform Inference
medium.comยท3hยท
๐Ÿค–LLM
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High-Performance and Reliable Probabilistic Ising Machine Based on Simulated Quantum Annealing
link.aps.orgยท11h
๐Ÿค–LLM
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Distinct Theta Synchrony across Speech Modes: Perceived, Spoken, Whispered, and Imagined
arxiv.orgยท6h
๐Ÿค–LLM
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Why I Built DataForge โ€” and How I Automated Excel-to-PDF Generation with Python
dev.toยท1dยท
Discuss: DEV
๐Ÿฆ€Rust
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Maestro: Learning to Collaborate via Conditional Listwise Policy Optimization for Multi-Agent LLMs
arxiv.orgยท1d
๐Ÿค–LLM
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Versatile and Risk-Sensitive Cardiac Diagnosis via Graph-Based ECG Signal Representation
arxiv.orgยท6h
๐Ÿฆ€Rust
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Sloppy : Chrome Extension for AI Slop Detection with Agentic Postgres
dev.toยท2dยท
Discuss: DEV
๐Ÿฆ€Rust
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Taurus Database: How to be Fast, Available, and Frugal in the Cloud
muratbuffalo.blogspot.comยท3dยท
๐Ÿค–LLM
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How We Cut LLM Batch Inference Time in Half with Dynamic Prefix Bucketing
dev.toยท1dยท
Discuss: DEV
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A Practical Guide to Building AI Agents with Java and Spring AI - Part 2 - Add Memory
dev.toยท1dยท
Discuss: DEV
๐Ÿ Local-first
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Built a way for Claude to query 6M rows without touching context windows. Anyone testing MCP at scale want to try it?
reddit.comยท12hยท
Discuss: r/ClaudeAI
๐Ÿค–LLM
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TAI #178: Kimi K2 Thinking Steals the Open-Source Crown With a New Agentic Contender
pub.towardsai.netยท20h
๐Ÿค–LLM
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When You Should โ€œWetโ€ Your Code: Why Blindly Following DRY Can Hurt Your Project
dev.toยท2hยท
Discuss: DEV
๐Ÿฆ€Rust
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DPRM: A Dual Implicit Process Reward Model in Multi-Hop Question Answering
arxiv.orgยท6h
๐Ÿค–LLM
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