Ad hoc networks are decentralized, self-configuring networks where nodes communicate without fixed infrastructure. They are commonly used in military, disaster…
Machine Learning
Interactive digital agents (IDAs) leverage APIs of stateful digital environments to perform tasks in response to user requests. While IDAs…
There is consistent customer feedback that AI assistants are the most useful when users can interface with them within the…
Reinforcement Learning RL trains agents to maximize rewards by interacting with an environment. Online RL alternates between taking actions, collecting…
As large language models (LLMs) become increasingly integrated into customer-facing applications, organizations are exploring ways to leverage their natural language…
Large Language Models (LLMs) have demonstrated notable reasoning capabilities in mathematical problem-solving, logical inference, and programming. However, their effectiveness is…
This post is co-written with Andrés Vélez Echeveri and Sean Azlin from OfferUp. OfferUp is an online, mobile-first marketplace designed…
This post is co-written with Martin Holste from Trellix. Security teams are dealing with an evolving universe of cybersecurity threats.…
Despite progress in AI-driven human animation, existing models often face limitations in motion realism, adaptability, and scalability. Many models struggle…
Graph Neural Networks (GNNs) have found applications in various domains, such as natural language processing, social network analysis, recommendation systems,…
In our previous tutorial, we built an AI agent capable of answering queries by surfing the web and added persistence…
Despite recent advancements, generative video models still struggle to represent motion realistically. Many existing models focus primarily on pixel-level reconstruction,…
The development of transformer-based large language models (LLMs) has significantly advanced AI-driven applications, particularly conversational agents. However, these models face…
Large language model (LLM) post-training focuses on refining model behavior and enhancing capabilities beyond their initial training phase. It includes…
Vision-language models (VLMs) face a critical challenge in achieving robust generalization beyond their training data while maintaining computational resources and…
In this tutorial, we’ll walk through how to set up and perform fine-tuning on the Llama 3.2 3B Instruct model…
Large neural networks pretrained on web-scale corpora are central to modern machine learning. In this paradigm, the distribution of the…
Generative AI has revolutionized technology through generating content and solving complex problems. To fully take advantage of this potential, seamless…
Directed graphs are crucial in modeling complex real-world systems, from gene regulatory networks and flow networks to stochastic processes and…
Neural Ordinary Differential Equations are significant in scientific modeling and time-series analysis where data changes every other moment. This neural…