Reproducing GPT-2 (124M) in llm.c in 90 minutes for $20 · karpathy/llm.c · Discussion #481
Let's reproduce the GPT-2 (124M) in llm.c (~4,000 lines of C/CUDA) in 90 minutes for $20. The 124M model is the smallest model in the GPT-2 series released by OpenAI in 2019, and is actually quite ...
The Surprising Power of Next Word Prediction: Large Language Models Explained, Part 1 | Center for Security and Emerging Technology
Large language models (LLMs), the technology that powers generative artificial intelligence (AI) products like ChatGPT or Google Gemini, are often thought of as chatbots that predict the next word. But that isn't the full story of what LLMs are and how they work. This is the first blog post in a three-part series explaining some key elements of how LLMs function. This blog post covers pre-training—the process by which LLMs learn to predict the next word—and why it’s so surprisingly powerful.
A Survey of Techniques for Maximizing LLM Performance
Join us for a comprehensive survey of techniques designed to unlock the full potential of Language Model Models (LLMs). Explore strategies such as fine-tunin...
AI Engineering: From Agents to LLM OS (plus demos from AI Engineer Singapore meetup)
i gave a talk at the recent AI Eng Singapore meetup (https://www.latent.space/p/community, scroll down) about the past 1 year in agents thinking and the bui...
Experts.js is the easiest way to create and deploy OpenAI's Assistants and link them together as Tools to create advanced Multi AI Agent Systems with expanded memory and attention to detail. - ...
How to build your own Perplexity for any dataset - Learnings from building “Ask Hacker Search”
How does something like Perplexity work, and how do we make our own? And having done that, what turned out to be the most interesting or challenging parts?
Why I'm Staying Away from Crew AI: My Honest Opinion
Crew AI is not suitable for production use cases. I’ll be going through why I believe this is the case and what you should do instead when building your own ...
The unreasonable effectiveness of embeddingsOr how I learned to stop worrying and love the hallucinations.This week I dived deep into vector databases. My go...
When evaluating RAG, it's not just the final answer that is worth evaluating
Evaluating intermediate steps (like query rephrasing and retrieved documents) is also super important when trying to make sure RAG works
Goo tutorial by on how to do this!
— Harrison Chase (@hwchase17)