Each retraining may cost millions of dollars in computation.
New research shows that AI models need to be completely retrained to learn new concepts — which is an expensive problem for AI companies.
Utilizing a novel AI-driven method, researchers enhanced the precision of estimating critical cosmological parameters by analyzing galaxy distributions.
This breakthrough allows for more refined studies of dark matter and energy, with implications for resolving the Hubble tension and other cosmic mysteries.
AI Revolution in Cosmology.
Combat AI impersonation fraud with Beyond Identity’s RealityCheck—your shield against deepfake attacks.
Over the past decade or so, computer scientists have developed increasingly advanced computational techniques that can tackle real-world tasks with human-comparable accuracy. While many of these artificial intelligence (AI) models have achieved remarkable results, they often do not precisely replicate the computations performed by the human brain.
Researchers at Tibbling Technologies, Broad Institute at Harvard Medical School, The Australian National University and other institutes recently tried to use AI to mimic a specific type of computation performed by circuits in the neocortex, known as “winner-take-all” computations.
Their paper, published on the bioRxiv preprint server, reports the successful emulation of this computation and shows that adding it to transformer-based models could significantly improve their performance on image classification tasks.
A robot played cello in a curated concert for the Malmö Symphony Orchestra in southern Sweden.
Robotics is driving innovations across various sectors nowadays. This time, a new robot has entered the music arena to transform it. In a recent video, the robot was spotted playing the cello.
The industrial robotic arms with 3D-printed parts performed with the members of the orchestra in Sweden.
Developed by researcher and composer Fredrik Gran, the robot didn’t rely on AI tools to play cello. Instead, it was programmed using composer Jacob Muhlrad’s musical score, which was specially written for the robot.
A research team led by Professor Bonghoon Kim from DGIST’s Department of Robotics and Mechatronics Engineering has developed a “3D smart energy device” that features both reversible heating and cooling capabilities. Their device was recognized for its excellence and practicality through its selection as the cover article of the international journal Advanced Materials.
The team collaborated with Professor Bongjae Lee from KAIST’s Department of Mechanical Engineering and Professor Heon Lee from Korea University’s Department of Materials Science and Engineering.
Heating and cooling account for approximately 50% of the global energy consumption, contributing significantly to environmental problems such as global warming and air pollution. In response, solar absorption and radiative cooling devices, which harness the sun and outdoor air as heat and cold sources, are gaining attention as eco-friendly and sustainable solutions.
DGIST Professor Youngu Lee and Jeonbuk National University Professor Jaehyuk Lim successfully developed an ultra-sensitive, transparent, and flexible electronic skin mimicking the neural network in the human brain. — Applicable across different areas, including healthcare wearable devices and transparent display touch panels.