As AI agents gain popularity in 2025, gathering and improving the right data for their training remains a significant challenge. Labelbox is tackling this issue with new features in its Multimodal Chat Editor, simplifying the creation of high-quality training datasets. Users can create, edit, and annotate agent trajectories to better evaluate and enhance AI agents. ...
Large language models (LLMs) are evolving into autonomous agents that can tackle complex tasks requiring reasoning and adaptability. As they operate in areas like web navigation and personal assistance, they encounter multi-turn interactions that complicate decision-making. Training these agents effectively requires methods beyond simple response generation, leading to the exploration of reinforcement learning (RL). The ...
In Santa Clara, California, Interview Kickstart has launched a comprehensive Machine Learning Course to meet the rising demand for skilled professionals in AI and machine learning. The six-month program trains participants in essential concepts such as Python programming, data analysis, and deep learning, with a strong emphasis on hands-on projects using real-world datasets. Additionally, the ...
Discover the incredible potential of AI agents by enrolling in our unique bootcamp, “AI Agents: From Theory to Practice.” This program will teach you how to build, deploy, and manage AI agents that can automate complex tasks across various industries. Right now, we’re offering a special price of $890 for Business Analytics Review readers, down ...
Hammerspace is redefining how data should be accessed for AI training and inference. Rather than focusing solely on object storage, they emphasize the importance of universal data access across various formats. With notable clients like Meta, Hammerspace supports multiple data access protocols while prioritizing scalability and efficiency. According to Molly Presley, Hammerspace’s SVP of Marketing, ...
MIT researchers have discovered a surprising new training method for artificial intelligence (AI) that could improve their performance in unpredictable environments. Instead of training AI agents in noise-filled conditions, they found that training them in quieter settings, like a calm indoor space, often led to better results when tested in noisier real-world scenarios. This phenomenon, ...
MIT researchers have uncovered a surprising phenomenon called the indoor training effect, which suggests that training AI agents in less uncertain environments can lead to better performance when they face unpredictable real-world scenarios. Traditionally, engineers strive to match training conditions with actual deployment to ensure success. However, the study, which involved training AI to play ...
Training your AI agent is essential for improving its responses and efficiency. A great way to enhance its performance is by building a knowledge base that the AI can refer to for accurate answers. You can train your agent using various formats, including links to webpages, documents like PDFs, and specific Q&A pairs. Simply follow ...
