AI

What the latest tech-marketing buzzword has to say about the future of automotive.

Artificial intelligence has captured headlines recently for its rapidly growing energy demands, and particularly the surging electricity usage of data centers that enable the training and deployment of the latest generative AI models. But it’s not all bad news — some AI tools have the potential to reduce some forms of energy consumption and enable cleaner grids.

Every autumn, as the Northern Hemisphere moves toward winter, Judah Cohen starts to piece together a complex atmospheric puzzle. Cohen, a research scientist in MIT’s Department of Civil and Environmental Engineering (CEE), has spent decades studying how conditions in the Arctic set the course for winter weather throughout Europe, Asia, and North America. His research

Tech companies are calling AI the next platform. But some developers are reluctant to let AI agents stand between them and their users.

This blog post is based on work co-developed with Flo Health. Healthcare science is rapidly advancing. Maintaining accurate and up-to-date medical content directly impacts people’s lives, health decisions, and well-being. When someone searches for health information, they are often at their most vulnerable, making accuracy not just important, but potentially life-saving. Flo Health creates thousands

Online detectives are inaccurately claiming to have identified the federal agent who shot and killed a 37-year-old woman in Minnesota based on AI-manipulated images.

Organizations handle vast amounts of sensitive customer information through various communication channels. Protecting Personally Identifiable Information (PII), such as social security numbers (SSNs), driver’s license numbers, and phone numbers has become increasingly critical for maintaining compliance with data privacy regulations and building customer trust. However, manually reviewing and redacting PII is time-consuming, error-prone, and scales

This post is cowritten with Aashraya Sachdeva from Observe.ai. You can use Amazon SageMaker to build, train and deploy machine learning (ML) models, including large language models (LLMs) and other foundation models (FMs). This helps you significantly reduce the time required for a range of generative AI and ML development tasks. An AI/ML development cycle

New Gmail features, powered by the Gemini model, are part of Google’s continued push for users to incorporate AI into their daily life and conversations.

Millennials are still using Craigslist to find jobs, find love, and even to cast creative projects—eschewing other AI- and algorithm-dominated online spaces. “There’s a purity to it.”