Latest from MIT : AI model identifies certain breast tumor stages likely to progress to invasive cancer

Ductal carcinoma in situ (DCIS) is a type of preinvasive tumor that sometimes progresses to a highly deadly form of breast cancer. It accounts for about 25 percent of all breast cancer diagnoses. Because it is difficult for clinicians to determine the type and stage of DCIS, patients with DCIS are often overtreated. To address…

Latest from MIT Tech Review – AI companies promised the White House to self-regulate one year ago. What’s changed?

One year ago, on July 21, 2023, seven leading AI companies—Amazon, Anthropic, Google, Inflection, Meta, Microsoft, and OpenAI—committed with the White House to a set of eight voluntary commitments on how to develop AI in a safe and trustworthy way. These included promises to do things like improve the testing and transparency around AI systems,…

Latest from MIT Tech Review – A new weather prediction model from Google combines AI with traditional physics

Google DeepMind researchers have built a new weather prediction model that combines machine learning with more conventional techniques, potentially yielding accurate forecasts at a fraction of the current cost.  The model, called NeuralGCN and described in a paper in Nature today, bridges a divide that’s grown among weather prediction experts in the last several years. …

UC Berkeley – Are We Ready for Multi-Image Reasoning? Launching VHs: The Visual Haystacks Benchmark!

Humans excel at processing vast arrays of visual information, a skill that is crucial for achieving artificial general intelligence (AGI). Over the decades, AI researchers have developed Visual Question Answering (VQA) systems to interpret scenes within single images and answer related questions. While recent advancements in foundation models have significantly closed the gap between human…

Latest from MIT : Machine learning unlocks secrets to advanced alloys

The concept of short-range order (SRO) — the arrangement of atoms over small distances — in metallic alloys has been underexplored in materials science and engineering. But the past decade has seen renewed interest in quantifying it, since decoding SRO is a crucial step toward developing tailored high-performing alloys, such as stronger or heat-resistant materials….

Latest from MIT Tech Review – Building supply chain resilience with AI

If the last five years have taught businesses with complex supply chains anything, it is that resilience is crucial. In the first three months of the covid-19 pandemic, for example, supply-chain leader Amazon grew its business 44%. Its investments in supply chain resilience allowed it to deliver when its competitors could not, says Sanjeev Maddila,…

Latest from MIT : Creating and verifying stable AI-controlled systems in a rigorous and flexible way

Neural networks have made a seismic impact on how engineers design controllers for robots, catalyzing more adaptive and efficient machines. Still, these brain-like machine-learning systems are a double-edged sword: Their complexity makes them powerful, but it also makes it difficult to guarantee that a robot powered by a neural network will safely accomplish its task….

Latest from MIT : AI method radically speeds predictions of materials’ thermal properties

It is estimated that about 70 percent of the energy generated worldwide ends up as waste heat. If scientists could better predict how heat moves through semiconductors and insulators, they could design more efficient power generation systems. However, the thermal properties of materials can be exceedingly difficult to model. The trouble comes from phonons, which…

Latest from MIT Tech Review – A short history of AI, and what it is (and isn’t)

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. It’s the simplest questions that are often the hardest to answer. That applies to AI, too. Even though it’s a technology being sold as a solution to the world’s problems, nobody…