Wearable devices, from smartwatches to fitness trackers, have become ubiquitous, continuously capturing a rich stream of data about our lives. They record our heart rate, count our steps, track our fitness and sleep, and much more. This deluge of information holds immense potential for personalized health and wellness. However, while we can easily see what our body is doing (e.g., a heart rate of 150 bpm), the crucial context of why (say, "a brisk uphill run" vs. "a stressful public speaking ...| research.google
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 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
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
