AI vibe coders have yet another reason to thank Andrej Karpathy, the coiner of the term. The former Director of AI at Tesla and co-founder of OpenAI, now running his own independent AI project, recently posted on X describing a "LLM Knowledge Bases" approach he's using to manage various topics of research interest. By building a persistent, LLM-maintained record of his projects, Karpathy is solving the core frustration of "stateless" AI development: the dreaded context-limit reset.As anyone who has vibe coded can attest, hitting a usage limit or ending a session often feels like a lobotomy for your project. You’re forced to spend valuable tokens (and time) reconstructing context for the AI, hoping it "remembers" the architectural nuances you just establ [...]
This weekend, Andrej Karpathy, the former director of AI at Tesla and a founding member of OpenAI, decided he wanted to read a book. But he did not want to read it alone. He wanted to read it accompan [...]
Over the weekend, Andrej Karpathy—the influential former Tesla AI lead and co-founder and former member of OpenAI who coined the term "vibe coding"— posted on X about his new open source [...]
Enabling LLMs to acquire new knowledge after training remains a major hurdle for enterprise AI — current solutions are either too expensive, too slow, or constrained by context window limits.MeMo, a [...]
Enabling LLMs to acquire new knowledge after training remains a major hurdle for enterprise AI — current solutions are either too expensive, too slow, or constrained by context window limits.MeMo, a [...]
Something shifted in enterprise RAG in Q1 2026. VB Pulse data spanning January through March tells a consistent story: the market stopped adding retrieval layers and started fixing the ones it already [...]
DeepSeek, the Chinese artificial intelligence research company that has repeatedly challenged assumptions about AI development costs, has released a new model that fundamentally reimagines how large l [...]
The vector database category is undergoing a shift in response to the needs of agentic AI. The retrieval-augmented generation (RAG)-to-vector database pipeline doesn't cut it anymore; agentic AI [...]
Retrieval-augmented generation (RAG) has become the de facto standard for grounding large language models (LLMs) in private data. The standard architecture — chunking documents, embedding them into [...]