Machine learning tagged posts

A tool developed by Keele University researchers has been shown to help detect fake news with an impressive 99% level of accuracy, offering a vital resource in combating online misinformation

The researchers Dr. Uchenna Ani, Dr. Sangeeta Sangeeta, and Dr. Patricia Asowo-Ayobode from Keele’s School of Computer Science and Mathematics, used a number of different machine learning techniques to develop their model, which can scan news content to give a judgment of whether a news source is trustworthy and genuine or not.

The method developed by the researchers uses an “ensemble voting” technique, which combines the predictions of multiple different machine learning models to give an overall score.

Impressively, this technique was accurate in identi...

Researchers at the Indian Institute of Science (IISc), with collaborators at University College London, have developed machine learning-based methods to predict material properties even with limited data. This can aid in the discovery of materials with desired properties, such as semiconductors.

In recent years, materials engineers have turned to machine learning models to predict which types of materials can possess specific properties such as electronic band gaps, formation energies, and mechanical properties, in order to design new materials. However, data on material properties—which is needed to train these models—is limited because testing materials is expensive and time consuming.

This prompted researchers led by Sai Gautam Gopalakrishnan, Assistant Professor at the D...

In recent years, roboticists have developed a wide range of systems designed to tackle various real-world tasks, ranging from completing household chores to delivering packages or finding target objects in delineated environments.

A key objective in the field has been to develop algorithms that allow the reliable transfer of specific skills across robots with different bodies and characteristics, which would help to rapidly train robots on new tasks, broadening their capabilities.

Researchers at UC Berkeley have developed RoVi-Aug, a new computational framework designed to augment robotic data and facilitate the transfer of skills across different robots...

Scientists propose a new way of implementing a neural network with an optical system which could make machine learning more sustainable in the future. The researchers at the Max Planck Institute for the Science of Light have published their new method in Nature Physics, demonstrating a method much simpler than previous approaches.

Machine learning and artificial intelligence are becoming increasingly widespread with applications ranging from computer vision to text generation, as demonstrated by ChatGPT. However, these complex tasks require increasingly complex neural networks; some with many billion parameters...