Highlights the desire to replace tokenization with a general method that better leverages compute and data. We'll see tokenization's fragility and review the Byte Latent Transformer arch.| ⛰️ lucalp
We’ve compiled a comprehensive dataset of the training compute of AI models, providing key insights into AI development.| Epoch AI
We have identified how millions of concepts are represented inside Claude Sonnet, one of our deployed large language models. This is the first ever detailed look inside a modern, production-grade large language model.| www.anthropic.com
Part IV of A Conceptual Guide to Transformers| benlevinstein.substack.com
We have identified how millions of concepts are represented inside Claude Sonnet, one of our deployed large language models. This is the first ever detailed look inside a modern, production-grade large language model.| www.anthropic.com
For decades, AI progress meant bigger models, faster GPUs, and larger datasets. But what if there were a fundamentally different, and possibly more efficient way? A way that’s more flexible and fault-tolerant? A way that only needs a tiny fraction of the power to run? Neuromorphic computing, which aims to mimic the human brain in […]| Exoswan Insights
A Comprehensive Overview of Prompt Engineering| www.promptingguide.ai