TEO the UC3M Robotics Lab humanoid robot painting a flower. Credit: Fernandez-Fernandez et al The rapid advancement of deep learning algorithms and generative models has enabled the automated production of…
Tag: Machine learning & AI
A new generative AI tool for power grid visualization
Credit: Pixabay/CC0 Public Domain Every minute of every day, grid operators monitor the ebb and flow of electricity from generators to substations to homes, businesses, schools, hospitals and more. They…
OpenAI’s new generative tool Sora could revolutionize marketing and content creation
Credit: Unsplash/CC0 Public Domain OpenAI’s new generative Sora tool has sparked lively technology discussions over the past week, generating both enthusiasm and concern among fans and critics. Sora is a…
Automated machine learning from the perspective of bilevel optimization
(a) Illustration of key issues of ML task. (b) Formulation of AutoML paradigm from the perspective of bilevel optimization. Credit: Science China Press Recently, professors Risheng Liu from Dalian University…
New system combines human, artificial intelligence to improve experimentation
The workflow of the human-AI collaborator system developed at ORNL to improve experimentation. Credit: Arpan Biswas and Rama Vasudevan/ORNL, U.S. Dept. of Energy Though artificial intelligence decreases human error in…
What is Sora? A new generative AI tool could transform video production and amplify disinformation risks
Credit: OpenAI Late last week, OpenAI announced a new generative AI system named Sora, which produces short videos from text prompts. While Sora is not yet available to the public,…
OpenAI in deal valuing it at $80 billion: Media
Credit: Unsplash/CC0 Public Domain OpenAI has concluded a deal with investors that reportedly values the California start-up at $80 billion or more, after a roller-coaster year for the inventor of…
New machine learning method predicts future data patterns to optimize data storage
Credit: CC0 Public Domain Researchers have developed a new machine-learning technique that helps computer systems predict future data patterns and optimize how information gets stored. They found these predictions could…
An integrated shuffler optimizes the privacy of personal genomic data used for machine learning
KAUST researchers developed a machine-learning approach aimed at preserving privacy while analyzing omics data for medical research. Credit: 2024 KAUST; Heno Hwang By integrating an ensemble of privacy-preserving algorithms, a…
