Browsing: accuracy

Tabular data—structured information stored in rows and columns—is at the heart of most real-world machine learning problems, from healthcare records to financial transactions. Over the years,…

The scaling of Large Language Models (LLMs) is increasingly constrained by memory communication overhead between High-Bandwidth Memory (HBM) and SRAM. Specifically, the Key-Value (KV) cache size…

Post-training Large Language Models (LLMs) for long-horizon agentic tasks—such as software engineering, web browsing, and complex tool use—presents a persistent trade-off between computational efficiency and model…

Fitbit has started rolling out major software updates in 2026, which promise a 15 percent boost in sleep tracking accuracy for its Premium subscribers. The company…

Not all screens and monitors are built to the same standards of color depth and accuracy, and your eyes also have their limits. Now, you can…

At first glance, adding more features to a model seems like an obvious way to improve performance. If a model can learn from more information, it…

Building a Retrieval-Augmented Generation (RAG) pipeline is easy; building one that doesn’t hallucinate during a 10-K audit is nearly impossible. For devs in the financial sector,…

For the last few years, the AI world has followed a simple rule: if you want a Large Language Model (LLM) to solve a harder problem,…

In this tutorial, we implement an agentic chain-of-thought pruning framework that generates multiple reasoning paths in parallel and dynamically reduces them using consensus signals and early…

The future of sequential attentionAs the increasing integration of AI models in science, engineering and business makes model efficiency more relevant than ever, model structure optimization…