Skip to content Skip to sidebar Skip to footer
Only AI Stuff
Only AI Stuff

Research

Close

Human hearing can potentially be modeled effectively through deep neural networks.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 13, 202470Views0Likes0Comments
A study from the Massachusetts Institute of Technology (MIT) has advanced the development of computational models based on the structure and function of the human auditory system. Findings from the study suggest these models that are derived from machine learning could be used to improve hearing aids, cochlear implants and brain-machine interfaces. The study, conducted by…

Read More

Deep neural networks exhibit potential as representations of human auditory perception.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 13, 202465Views0Likes0Comments
A team of researchers from the Massachusetts Institute of Technology (MIT) has been investigating computational models that are designed to mimic the structure and function of the human auditory system. They claim that these models could have future applications in the development of more advanced hearing aids, cochlear implants, and brain-machine interfaces. In a study that…

Read More

The computational model grasps the hard-to-capture transition phases of chemical reactions.

Artificial Intelligence, Chemical engineering, Chemistry, Machine learning, National Science Foundation (NSF), Research, School of Engineering, School of Science, UncategorizedApril 13, 202462Views0Likes0Comments
During a chemical reaction, molecules gain energy until they reach what is known as the transition state — a point at which the reaction must proceed. This state is extremely short-lived and nearly impossible to observe experimentally. Its structures can be calculated using quantum chemistry techniques, but these methods are very time-consuming. Recently, a team of…

Read More

A versatile approach to assist animators in enhancing their artwork.

Algorithms, Artificial Intelligence, Arts, Augmented and virtual reality, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical Engineering & Computer Science (eecs), Mathematics, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Research, UncategorizedApril 13, 202474Views0Likes0Comments
A new technique developed by researchers from MIT promises to revolutionize how artists animate characters in video games and animated films. Utilizing mathematical functions called barycentric coordinates, which define how 2D and 3D shapes can move, bend, and stretch in space, will give animators greater control over the motion of characters. Traditional animating methods often provide…

Read More

Bridging the gap between design and production for optical equipment.

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 13, 202466Views0Likes0Comments
Researchers from MIT and the Chinese University of Hong Kong are using machine learning to close the gap between design and manufacturing processes in photolithography - a method used in the creation of computer chips and optical devices. Photolithography involves using light to etch features onto a surface. However, tiny variations during production often lead…

Read More

Deep neural networks demonstrate potential in simulating human auditory perception.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 13, 202470Views0Likes0Comments
A study by Massachusetts Institute of Technology (MIT) shows that machine learning-based computational models are making strides towards mimicking the human auditory system, potentially improving the design of devices like hearing aids and cochlear implants. The research indicated that these models’ internal data structures have similarities to those seen in the human brain in response…

Read More

The computational model successfully records the difficult-to-detect transition phases of chemical reactions.

Artificial Intelligence, Chemical engineering, Chemistry, Machine learning, National Science Foundation (NSF), Research, School of Engineering, School of Science, UncategorizedApril 13, 202465Views0Likes0Comments
Chemical reactions reach a 'transition state' when molecules gain enough energy for the reaction to proceed. This state is brief and hard to observe experimentally. The arrangement of these transition states can be calculated through quantum chemistry, but it is highly time-consuming. Scientists at MIT have developed a faster method using machine learning which computes…

Read More

An adaptable approach to assist creators in enhancing animation.

Algorithms, Artificial Intelligence, Arts, Augmented and virtual reality, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical Engineering & Computer Science (eecs), Mathematics, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Research, UncategorizedApril 13, 202472Views0Likes0Comments
A group of MIT researchers have developed a technique that will allow artists better control over their 3D animations. The method uses mathematical functions known as barycentric coordinates, allowing 3D shapes to be manipulated. This offers more flexibility than traditional animation methods, which require starting from scratch for every change in animation. The developed method…

Read More

Bridging the gap between design and production in the field of optical devices.

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 12, 202471Views0Likes0Comments
Photolithography, the process of manipulating light to etch features on to a surface, is crucial in making computer chips and optical devices. However, the performance of devices made using this process often falls short of their original designs due to minute deviations during manufacturing. To address this design-to-manufacturing gap, researchers from MIT and the Chinese…

Read More

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 12, 202473Views0Likes0Comments
Photolithography, a process of etching detailed patterns onto surfaces using light, is a crucial technique in the design and production of computer chips and other optical devices, such as lenses. However, minute deviations during manufacturing can cause a discrepancy between the designer's intentions and the actual produced device. To help bridge this gap between design…

Read More

Deep neural networks demonstrate potential in being models for human auditory systems.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 12, 202467Views0Likes0Comments
MIT researchers have conducted a study that suggests machine learning models might be used to better design hearing aids, cochlear implants, and brain-machine interfaces. In the largest research project to date involving deep neural networks trained to carry out auditory tasks, the researchers showed that most of these models mimic the human brain’s behaviour when…

Read More

Computational model successfully identifies the hard-to-catch transitional stages of chemical reactions.

Artificial Intelligence, Chemical engineering, Chemistry, Machine learning, National Science Foundation (NSF), Research, School of Engineering, School of Science, UncategorizedApril 12, 202465Views0Likes0Comments
A team of researchers from the Massachusetts Institute of Technology (MIT) has developed a machine learning model that can quickly calculate the structures of transition states in chemical reactions. These fleeting moments occur when molecules have gained enough energy to proceed with a reaction, but are notoriously difficult to study due to their ephemeral nature.…

Read More

+60 12-462 2768
hello@goacademyai.com