Deep Dives

landed on arXiv just before Christmas 2025, very much an early present from the team at Google DeepMind, with the title “Towards a Science of Scaling Agent Systems.” I discovered this paper to be a...

within the federated learning series I'm doing, and should you just landed here, I might recommend going through the primary part where we discussed how federated learning works at a high level. For...

After dinner in downtown San Francisco, I said goodbye to friends and pulled out my phone to work out how you can get home. It was near 11:30 pm, and Uber estimates were unusually...

forecasting errors are usually not brought on by bad time-series models. They're brought on by ignoring structure. SKUs don't behave independently. They interact through shared plants, product groups, warehouses, and storage locations. A requirement shock...

, context really is every thing. The standard of an LLM’s output is tightly linked to the standard and amount of knowledge you provide. In practice, many real-world use cases include massive contexts: code...

: Limitations of Machine Learning As an information scientist in today’s digital age, it's essential to be equipped to reply quite a lot of questions that go far beyond easy pattern recognition. Typical machine learning...

of the AI boom, the pace of technological iteration has reached an unprecedented level. Previous obstacles now appear to have viable solutions. This text serves as an “NMT 101” guide. While introducing our...

a part of a series of posts on optimizing data transfer using NVIDIA Nsight™ Systems (nsys) profiler. Part one focused on CPU-to-GPU data copies, and part two on GPU-to-CPU copies. On this post, we turn our attention...