Latest from MIT Tech Review – Investing in AI to build next-generation infrastructure

The demand for new and improved infrastructure across the world is not being met. The Asian Development Bank has estimated that in Asia alone, roughly $1.7 trillion needs to be invested annually through to 2030 just to sustain economic growth and offset the effects of climate change. Globally, that figure has been put at $15…

Latest from MIT : Making it easier to verify an AI model’s responses

Despite their impressive capabilities, large language models are far from perfect. These artificial intelligence models sometimes “hallucinate” by generating incorrect or unsupported information in response to a query. Due to this hallucination problem, an LLM’s responses are often verified by human fact-checkers, especially if a model is deployed in a high-stakes setting like health care…

Latest from MIT Tech Review – The race to find new materials with AI needs more data. Meta is giving massive amounts away for free.

Meta is releasing a massive data set and models, called Open Materials 2024, that could help scientists use AI to discover new materials much faster. OMat24 tackles one of the biggest bottlenecks in the discovery process: data. To find new materials, scientists calculate the properties of elements across the periodic table and simulate different combinations…

Latest from MIT Tech Review – AI could help people find common ground during deliberations

Reaching a consensus in a democracy is difficult because people hold such different ideological, political, and social views.  Perhaps an AI tool could help. Researchers from Google DeepMind trained a system of large language models (LLMs) to operate as a “caucus mediator,” generating summaries that outline a group’s areas of agreement on complex but important…

Latest from MIT Tech Review – Transforming software with generative AI

Generative AI’s promises for the software development lifecycle (SDLC)—code that writes itself, fully automated test generation, and developers who spend more time innovating than debugging—are as alluring as they are ambitious. Some bullish industry forecasts project a 30% productivity boost from AI developer tools, which, if realized, could inject more than $1.5 trillion into the…

Latest from MIT : Combining next-token prediction and video diffusion in computer vision and robotics

In the current AI zeitgeist, sequence models have skyrocketed in popularity for their ability to analyze data and predict what to do next. For instance, you’ve likely used next-token prediction models like ChatGPT, which anticipate each word (token) in a sequence to form answers to users’ queries. There are also full-sequence diffusion models like Sora,…

Latest from MIT : Equipping doctors with AI co-pilots

Most doctors go into medicine because they want to help patients. But today’s health care system requires that doctors spend hours each day on other work — searching through electronic health records (EHRs), writing documentation, coding and billing, prior authorization, and utilization management — often surpassing the time they spend caring for patients. The situation leads to…

Latest from MIT Tech Review – OpenAI says ChatGPT treats us all the same (most of the time)

Does ChatGPT treat you the same whether you’re a Laurie, Luke, or Lashonda? Almost, but not quite. OpenAI has analyzed millions of conversations with its hit chatbot and found that ChatGPT will produce a harmful gender or racial stereotype based on a user’s name in around one in 1000 responses on average, and as many…

Latest from MIT Tech Review – Intro to AI: a beginner’s guide to artificial intelligence from MIT Technology Review

It feels as though AI is moving a million miles a minute. Every week, it seems, there are product launches, fresh features and other innovations, and new concerns over ethics and privacy. It’s a lot to keep up with. Maybe you wish someone would just take a step back and explain some of the basics. …