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Google AI Introduces TransformerFAM: An Innovative Transformer Structure that Utilizes a Feedback Mechanism to Allow the Neural Network to Focus on Its Hidden Representations.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedApril 18, 202435Views0Likes0Comments
Google AI researchers have developed a new Transformer network dubbed TransformerFAM, aimed to enhance performance in handling extremely long context tasks. Despite Transformers proving revolutionary in the domain of deep learning, they have limitations due to their quadratic attention complexity— an aspect that curtails their ability to process infinitely long inputs. Existing Transformers often forget…

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There is potential in deep neural networks as they could effectively serve as models for human auditory perception.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 18, 202435Views0Likes0Comments
A new MIT study has found that computational models derived from machine learning that mimic the structure and function of the human auditory system could help improve the design of hearing aids, cochlear implants, and brain-machine interfaces. Its research explored deep neural networks trained to perform auditory tasks and showed that these models generate internal…

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The computational model accurately identifies the hard-to-detect transition stages of chemical reactions.

Artificial Intelligence, Chemical engineering, Chemistry, Machine learning, National Science Foundation (NSF), Research, School of Engineering, School of Science, UncategorizedApril 18, 202439Views0Likes0Comments
The process of identifying the fleeting chemical transition states that occur during reactions could be significantly sped up thanks to a machine learning system developed by researchers from MIT. At present, these states can be calculated using quantum chemistry, but this process is time and computing power intensive, often taking days to calculate a single…

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Bridging the gap between design and production for optical instruments.

Artificial Intelligence, Biological engineering, Computer science and technology, Electronics, Machine learning, Mechanical engineering, MIT Schwarzman College of Computing, MIT.nano, National Institutes of Health (NIH), Research, School of Engineering, UncategorizedApril 18, 202439Views0Likes0Comments
Photolithography, the technique used to create computer chips and optical devices, often results in minuscule deviations from design intentions. With the goal of closing the gap between design and manufacturing, a team of researchers from MIT and the Chinese University of Hong Kong, led by mechanical engineering graduate student Cheng Zheng, used machine learning to…

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Computational model accurately identifies the hard-to-detect transitional stages of chemical reactions.

Artificial Intelligence, Chemical engineering, Chemistry, Machine learning, National Science Foundation (NSF), Research, School of Engineering, School of Science, UncategorizedApril 18, 202439Views0Likes0Comments
Scientists from the Massachusetts Institute of Technology have used machine learning to expedite calculations of transition states in chemical reactions, a process that could support the invention of new reactions and catalysts with applications in fuels, pharmaceuticals and understanding the origins of life. Using a method known as density functional theory to compute transition states…

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The computational model accurately identifies the hard-to-detect transitional phases of chemical reactions.

Artificial Intelligence, Chemical engineering, Chemistry, Machine learning, National Science Foundation (NSF), Research, School of Engineering, School of Science, UncategorizedApril 18, 202443Views0Likes0Comments
Scientists at MIT have developed a machine learning-based technique for rapidly calculating the transition state of a chemical reaction, a step that was previously extremely time-consuming using traditional quantum chemistry methods. The transition state is a crucial yet fleeting phase in any reaction, marking the point where molecules have gained enough energy for a reaction…

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With the help of AI, researchers at MIT have discovered a new category of potential antibiotics.

Antibiotics, Artificial Intelligence, Biological engineering, Broad Institute, Drug discovery, Drug resistance, Institute for Medical Engineering and Science (IMES), Jameel Clinic, Machine learning, Research, School of Engineering, UncategorizedApril 18, 202440Views0Likes0Comments
Using artificial intelligence in the form of deep learning, researchers from MIT have discovered compounds capable of killing methicillin-resistant Staphylococcus aureus (MRSA), a drug-resistant bacteria that reportedly causes over 10,000 deaths in the U.S. each year. This breakthrough was achieved by training a deep learning model using predictive information based on antibiotic potency of a…

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Oxford researchers introduced Policy-Guided Diffusion: a machine learning approach for managing the creation of artificial trajectories in Offline Reinforcement Learning RL.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedApril 17, 202432Views0Likes0Comments
The transition of Reinforcement Learning (RL) from theory to real-world application has been hampered by sample inefficiency, especially in risky exploration environments. The challenges include a distribution shift between the target policy and the collected data, resulting in overestimation bias and an overly optimistic target policy. A new method proposed by researchers from Oxford University,…

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