How to evaluate and benchmark Large Language Models (LLMs)
together.ai·1d
🔄MLOps
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What if software shipped with a software engineer?
manuel.kiessling.net·1d
🔄MLOps
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OpenSIR: Open-Ended Self-Improving Reasoner
arxiv.org·21h
🧠AI
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Context7 is the most underrated MCP server you're not using for your local LLM
xda-developers.com·1d
🔄MLOps
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I built a small ARM-like virtual system with a custom RTOS and C/C++ toolchain (BEEP-8)
🔧Embedded Rust
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build system tradeoffs
🕸️WebAssembly
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TypeScript Rewrote Itself in Go?! What That “10x Faster” Hype Really Means
🕸️WebAssembly
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From Vibe Coding to Informed Development: How Codalio PRD Transforms Your Cursor Workflow
🕸️WebAssembly
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QuantumBench: A Benchmark for Quantum Problem Solving
arxiv.org·21h
📱Edge AI
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Prompt Injection as an Emerging Threat: Evaluating the Resilience of Large Language Models
arxiv.org·21h
💬NLP
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Introducing Agent-o-rama: build, trace, evaluate, and monitor stateful LLM agents in Java or Clojure
💬NLP
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Position: Vibe Coding Needs Vibe Reasoning: Improving Vibe Coding with Formal Verification
arxiv.org·21h
⚡Zig
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Radar Trends to Watch: November 2025
oreilly.com·14h
🧠AI
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Post-training methods for language models
developers.redhat.com·19h
💬NLP
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Fleming-VL: Towards Universal Medical Visual Reasoning with Multimodal LLMs
arxiv.org·21h
🧠Neural Architecture
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