Browsing: Research

Smartwatches have gotten pretty good at detecting atrial fibrillation, the most common heart rhythm disorder in the world, affecting nearly 38 million people globally. But many…

Training AI agents that can actually use a computer — opening apps, clicking buttons, browsing the web, writing code — is one of the hardest infrastructure…

Writing a research paper is brutal. Even after the experiments are done, a researcher still faces weeks of translating messy lab notes, scattered results tables, and…

Designing algorithms for Multi-Agent Reinforcement Learning (MARL) in imperfect-information games — scenarios where players act sequentially and cannot see each other’s private information, like poker —…

In the world of voice AI, the difference between a helpful assistant and an awkward interaction is measured in milliseconds. While text-based Retrieval-Augmented Generation (RAG) systems…

World Models (WMs) are a central framework for developing agents that reason and plan in a compact latent space. However, training these models directly from pixel…

In this tutorial, we build an uncertainty-aware large language model system that not only generates answers but also estimates the confidence in those answers. We implement…

Large language models (LLMs) are transitioning from conversational to autonomous agents capable of executing complex professional workflows. However, their deployment in enterprise environments remains limited by…

Over the last few months, various academics and AI companies have attempted to predict how artificial intelligence is going to impact the labor market. These studies,…

Conclusion Several larger conclusions emerge from this test case. The two models that drew from curated databases of experimental literature, NotebookLM and our custom-built tool, outperformed…