AI

It’s still possible to just take normal-looking photos. Use these apps for Android and iOS to give your phone’s camera a more natural eye.

The hype is fading, and people are asking what generative artificial intelligence is really good for. So far, no one has a decent answer.

Whether you’re a fulfillment center, a manufacturer, or a distributor, speed is king. But getting products out the door quickly requires workers to know where those products are located in their warehouses at all times. That may sound obvious, but lost or misplaced inventory is a major problem in warehouses around the world. Corvus Robotics

Frida Polli, a neuroscientist, entrepreneur, investor, and inventor known for her leading-edge contributions at the crossroads of behavioral science and artificial intelligence, is MIT’s new visiting innovation scholar for the 2024-25 academic year. She is the first visiting innovation scholar to be housed within the MIT Schwarzman College of Computing. Polli began her career in

WIRED is following every copyright battle involving the AI industry—and we’ve created some handy visualizations that will be updated as the cases progress.

Crafting a unique and promising research hypothesis is a fundamental skill for any scientist. It can also be time consuming: New PhD candidates might spend the first year of their program trying to decide exactly what to explore in their experiments. What if artificial intelligence could help? MIT researchers have created a way to autonomously

Generative AI offers many benefits for both you, as a software provider, and your end-users. AI assistants can help users generate insights, get help, and find information that may be hard to surface using traditional means. In addition, they can help your employees reduce repetitive tasks and focus on high-value work. However, adding generative AI

Large language models (LLMs) have demonstrated remarkable capabilities in a wide range of linguistic tasks. However, the performance of these models is heavily influenced by the data used during the training process. In this blog post, we provide an introduction to preparing your own dataset for LLM training. Whether your goal is to fine-tune a pre-trained

As generative AI capabilities evolve, successful business adoptions hinge on the development of robust problem-solving capabilities. At the forefront of this transformation are agentic systems, which harness the power of foundation models (FMs) to tackle complex, real-world challenges. By seamlessly integrating multiple agents, these innovative solutions enable autonomous collaboration, decision-making, and efficient problem-solving in diverse