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Machine learning

The unseen hurdle of today’s AI: Accuracy in image identification.

MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) researchers, in collaboration with the MIT-IBM Watson AI Lab, have developed a new metric, the "minimum viewing time" (MVT), to measure the difficulty of recognizing an image. The researchers aimed to close the gap between the performance of deep learning-based AI models and humans in recognizing and…

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MIT researchers harness artificial intelligence to discover potential new antibiotic classes.

Using deep learning, a form of artificial intelligence, researchers at MIT have discovered a group of compounds that can eliminate methicillin-resistant Staphylococcus aureus (MRSA), a drug-resistant bacterium that causes over 10,000 deaths in the US annually. The compounds, which display low toxicity against human cells, are considered good potential drug candidates. In a paper published in…

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Utilizing language to comprehend machines.

MIT engineering students Irene Terpstra ’23 and Rujul Gandhi ’22 are collaborating with the MIT-IBM Watson AI Lab to advance Artificial Intelligence (AI) systems using Natural Language Processing (NLP), taking advantage of the vast amount of natural language data available. Terpstra is focusing on the application of AI algorithms for computer chip design, leveraging the…

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Intricate and unknown phrases influence the brain’s linguistic network to exert more effort.

A study by MIT neuroscientists, utilising an artificial language network, discovered the type of sentences most likely to stimulate the brain’s key language processing centers. The study concluded that complex sentences, with unusual grammar or unexpected meaning, generate stronger responses. In contrast, simplistic sentences marginally engaged these regions, while nonsensical sequences of words had little…

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AI representatives assist in elucidating other AI frameworks.

Interpreting the functions and behaviors of large-scale neural networks remains a complex task and a significant challenge in the field of Artificial Intelligence. To tackle this problem, researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a strategy that uses AI models to investigate the computations inside other AI systems.  Central to this…

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This method may effectively resolve partial differential equations for a multitude of uses.

Partial differential equations (PDEs) are used in fields like physics and engineering to model complex physical processes, offering insight into some of the world's most intricate systems. To solve these equations, researchers use high-fidelity numerical solvers, which are time-consuming and computationally expensive. A simplified alternative, data-driven surrogate models, compute the goal property of a solution…

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Numerous AI systems assist robots in carrying out intricate strategies with greater clarity.

MIT's Improbable AI Lab has developed a novel multimodal framework for artificial intelligence (AI) called the Compositional Foundation Models for Hierarchical Planning (HiP). The aim of this system is to help robots conduct complex tasks that involve numerous smaller steps, from household chores to more elaborate industrial processes. Traditionally, AI systems have required paired visual,…

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Safety Guidelines in the Stratosphere: The Potential Influence of Aviation on Regulating Health-based AI Systems

A 2022 report from the International Air Transport Association revealed that the odds of dying in a plane crash are extremely low, with an industry fatality risk of 0.11. This implies that a person would need to fly daily for over 25,000 years to have a 100% chance of experiencing a fatal accident, underscoring why…

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Logical thinking and dependability in Artificial Intelligence

MIT PhD students interning at the MIT-IBM Watson AI Lab are researching ways to improve the efficiency and accuracy of AI systems in understanding and communicating through natural language. The team, including Athul Paul Jacob, Maohao Shen, Victor Butoi, and Andi Peng, aims to enhance each stage of the process involving natural language models, from…

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AI-based risk prediction provides fresh optimism for timely intervention in pancreatic cancer.

MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) scientists, in collaboration with Limor Appelbaum, a scientist in the Department of Radiation Oncology at Beth Israel Deaconess Medical Center (BIDMC), have developed two machine-learning models for the early detection of pancreatic cancer. The two models PRISM and the logistic regression model both surpassed current diagnostic methods.…

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How to handle AI in healthcare?

The MIT Abdul Latif Jameel Clinic for Machine Learning in Health (Jameel Clinic) held an AI and Health Regulatory Policy Conference on December 4, sparking debates among faculty, regulators from the US, EU, and Nigeria, and industry experts about the regulation of AI in health. The conference centered around the question of whether the "black…

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Inquiry and Response: A Design Plan for Long-Term Innovation

Atacama Biomaterials is a startup led by co-founder Paloma Gonzalez-Rojas, which combines machine learning, architecture, and chemical engineering to create eco-friendly materials. The company aims to contribute to sustainability by creating innovative materials for various industries such as biofuels, biological drugs, and mining. The company was started in 2020 and has gone through several entrepreneurship…

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