Articles about AI System Design in Technology & AI
Ever wonder how robots see the world and decide what to do next? Let's pull back the curtain and build a simple AI agent from scratch that learns to navigate its world just by looking at pixels. No complex libraries, just pure concepts.
LoRA is a go-to for efficient fine-tuning, but it has a hidden flaw. We break down why it struggles to learn new facts and how a simple fix, RS-LoRA, can solve the problem.
Traditional RAG systems rely on vector similarity, but often fail on complex documents. Discover PageIndex, a new approach that uses an LLM to reason over a document's structure, leading to more accurate, human-like retrieval.
We've all been there: you ask an AI to change one function, and it unknowingly breaks 47 other things. GitNexus is an open-source tool that fixes this by giving AI agents a complete map of your code, so they finally understand the consequences of their edits.
Training massive AI models is incredibly fragile—one chip failure can halt everything. Google DeepMind's new Decoupled DiLoCo system fixes this by creating 'self-healing' islands of compute that could change how we build AI.
Feeling overwhelmed by endless AI tools? You're not alone. Learn how to stop chasing shiny new apps and build a lean, effective AI productivity system that actually saves you time and reduces friction.
Anthropic never revealed the inner workings of Claude Mythos, but a new open-source project called OpenMythos has a fascinating theory. It's a full PyTorch reconstruction suggesting a radical idea: what if true reasoning power comes from iteration, not just size?
Ever feel like your AI assistant has the memory of a goldfish? Let's fix that. This guide shows you, step-by-step, how to build a universal long-term memory for your AI agents using Mem0 and OpenAI.
Forget AI agents that use your computer. Researchers from Meta AI have a wild new idea: a "Neural Computer" where the AI model *is* the entire machine—computation, memory, and interface all in one.
Ever feel like "AI agents" are all hype? Let's get our hands dirty and build a real, working agent from scratch using Z.AI's GLM-5, from basic chat to multi-tool workflows.
AI agents that act on their own can be scary. Learn how to build a "plan-and-execute" agent that proposes a plan, waits for your approval, and only acts when you say so, using LangGraph and Streamlit.
Forget scattered files and endless searching. We're building a "second brain" where your notes are connected, and an AI agent can navigate them to find answers, uncover insights, and even help you fill in the gaps.