LazyLLM: Low-Code Framework for Multi-Agent Applications Curiosity: What if building multi-agent systems could be as simple as connecting building blocks? How can we make LLM application developme...

How Linux Works: A Comprehensive Guide Curiosity: How does Linux boot and operate? What are the key components and processes that make Linux work? Linux is a powerful, open-source operating syste...

Even 𝗡𝗩𝗜𝗗𝗜𝗔 𝗡𝗜𝗠 𝗶𝘀 𝗿𝘂𝗻𝗻𝗶𝗻𝗴 𝗼𝗻 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀, what is 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 and why is it worth learning 𝗮𝘀 𝗠𝗟𝗢𝗽𝘀/𝗠𝗟/𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿? 👉 Today we look into the Kubernetes system from a bird’s eye view. 𝗦𝗼, 𝘄𝗵𝗮𝘁 ...

Apple Intelligence Foundation Language Models 👉 Paper : https://arxiv.org/pdf/2407.21075 Two models: On-device: ~3B param with task-specific LoRA adapters Server: ~70B (my estimation),...

Awesome Production LLM: Curated Open-Source Libraries Curiosity: What are the best open-source libraries for building production-ready LLM applications? How can we systematically organize tools ac...

Not sure if you chunked your data right to enable optimal context retrieval? Not sure which embedding model will work best for your data? Don’t worry, you’re not alone.. A RAG has several movi...

Unlocking the Power of RLHF in Large Language Models Curiosity: How do LLMs learn to align with human preferences? What is Reinforcement Learning from Human Feedback (RLHF) and how does it work? ...

Accelerating LLMs by 2× with Graph-Structured Speculative Decoding Curiosity: How can we make LLM inference faster? What happens when we use graph structures to optimize speculative decoding? Res...

GPT-4’s Struggle with Long-Context Bilingual Reasoning Curiosity: Despite being one of the leading LLMs, GPT-4 struggles with long-context bilingual reasoning tasks, even with text lengths shorter...

It is extremely important to ensure Data Quality upstream of ML Training and Inference Pipelines, trying to do that in the pipelines will cause unavoidable failure when working at scale. Curiosi...