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A novel method enables AI chatbots to communicate continuously without failure.

Algorithms, Artificial Intelligence, Computer science and technology, Electrical Engineering & Computer Science (eecs), Human-computer interaction, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Research, School of Engineering, UncategorizedMay 17, 202439Views0Likes0Comments
Researchers from MIT and other institutions have found a solution to an issue that causes machine-learning model-run chatbots to malfunction during long, continuous dialogues. They found that significant delays or crashes happen when the key-value cache, essentially the conversation memory, becomes overloaded leading to early data being ejected and the model to fail. The researchers…

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Scientists employ generative artificial intelligence to tackle intricate queries in the field of physics.

Artificial Intelligence, Computer modeling, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Machine learning, Mathematics, MIT Schwarzman College of Computing, Physics, Research, School of Engineering, School of Science, UncategorizedMay 16, 202439Views0Likes0Comments
Researchers from MIT and the University of Basel in Switzerland have developed a new machine-learning framework that can map phase diagrams for novel physical systems automatically. By applying generative artificial intelligence models, the team has developed a more efficient method for tracking and understanding phase transitions in water and other complex physical systems, which offers…

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Physicians encounter greater challenges in identifying diseases when examining images of darker skin tones.

Artificial Intelligence, Computer science and technology, Ethics, Health care, Media Lab, Medicine, Research, School of Architecture and Planning, Social justice, Technology and society, UncategorizedMay 15, 202428Views0Likes0Comments
A new study by researchers from Massachusetts Institute of Technology (MIT) has found that doctors are less accurate in diagnosing skin diseases based on images when the patient has darker skin. The study included over 1,000 dermatologists and general practitioners; dermatologists accurately diagnosed 38 percent of images overall, but only 34 percent of darker skin…

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An innovative method enables AI chatbots to engage in conversations all day without experiencing errors or shutdowns.

Algorithms, Artificial Intelligence, Computer science and technology, Electrical Engineering & Computer Science (eecs), Human-computer interaction, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Research, School of Engineering, UncategorizedMay 15, 202432Views0Likes0Comments
A team of researchers from MIT, Meta AI, Carnegie Mellon University, and NVIDIA, have found a solution to the problem of the performance degradation of AI chatbots during extended human-AI conversations. They identified a challenge associated with AI conversation memory, known as the key-value cache, where data is bumped out when the cache exceeds its…

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Physicians often find it more challenging to identify diseases when examining images of darker skin tones.

Artificial Intelligence, Computer science and technology, Ethics, Health care, Media Lab, Medicine, Research, School of Architecture and Planning, Social justice, Technology and society, UncategorizedMay 15, 202439Views0Likes0Comments
Doctors are less accurate when diagnosing skin diseases in people with darker skin, according to a study by MIT researchers. The researchers found that dermatologists accurately characterized 38% of images of skin diseases, but only 34% of those images were of darker skin. The results were similar for general practitioners. The research team suggested that…

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Improving the dependability of language models by leveraging concepts from game theory.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Game theory, Human-computer interaction, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Natural language processing, Research, Robotics, School of Engineering, UncategorizedMay 15, 202434Views0Likes0Comments
Researchers from MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) have designed a new type of game to enhance how artificial intelligence (AI) comprehends and produces text. This "consensus game" includes two parts of an AI system - the part that generates sentences and a part that evaluates those sentences. This model significantly improved the…

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Diagnosing illnesses can be more challenging for physicians when examining images of darker skin tones.

Artificial Intelligence, Computer science and technology, Ethics, Health care, Media Lab, Medicine, Research, School of Architecture and Planning, Social justice, Technology and society, UncategorizedMay 14, 202439Views0Likes0Comments
Doctors struggle to diagnose skin disease accurately in patients with darker skin tones, according to new research from MIT. The study found that dermatologists correctly diagnosed images of skin disease in just 34% of cases involving darker skin, compared with 38% involving lighter skin. The researchers also examined the effect of AI assistance on diagnostic…

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Physicians face greater challenges in identifying diseases when examining images of darker skin tones.

Artificial Intelligence, Computer science and technology, Ethics, Health care, Media Lab, Medicine, Research, School of Architecture and Planning, Social justice, Technology and society, UncategorizedMay 14, 202437Views0Likes0Comments
A new study from MIT researchers suggests that doctors are less accurate in diagnosing skin diseases on patients with darker skin through images alone. The study analyzed the accuracy of over 1,000 dermatologists and general practitioners and found that dermatologists correctly diagnosed about 38% of the images they saw, but only 34% for those of…

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Diagnosing diseases becomes more challenging for physicians when examining images of skin with a darker complexion.

Artificial Intelligence, Computer science and technology, Ethics, Health care, Media Lab, Medicine, Research, School of Architecture and Planning, Social justice, Technology and society, UncategorizedMay 13, 202439Views0Likes0Comments
A study by MIT researchers has found that doctors are less accurate at diagnosing skin diseases in patients with darker skin tones. Over 1,000 dermatologists and general practitioners took part in the study, which found that dermatologists correctly diagnosed images of skin diseases 38% of the time, with the figure falling to 34% for darker…

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