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A 9th grader from Snellville, Georgia, has won the 3M Young Scientist Challenge, after inventing a handheld device designed to detect pesticide residues on produce.

Sirish Subash set himself apart with his AI-based sensor to win the grand prize of $25,000 cash and the prestigious title of “America’s Top Young Scientist.”

Like most inventors, Sirish was intrigued with curiosity and a simple question. His mother always insisted that he wash the fruit before eating it, and the boy wondered if the preventative action actually did any good.

For our AI industry people, if you werent aware, some kind of research prizes for solving technical challenges related to AI.

Prize information, rules, and key dates.

The combined results also speak to a more fundamental goal. For decades, the quantum computing community has been trying to establish quantum advantage —a task that quantum computers can do that a classical one would struggle with. Usually, researchers understand quantum advantage to mean that a quantum computer can do the task in far fewer steps.

The new papers show that quantum memory lets a quantum computer perform a task not necessarily with fewer steps, but with less data. As a result, researchers believe this in itself could be a way to prove quantum advantage. “It allows us to, in the more near term, already achieve that kind of quantum advantage,” said Hsin-Yuan Huang, a physicist at Google Quantum AI.

But researchers are excited about the practical benefits too, as the new results make it easier for researchers to understand complex quantum systems.

This blog is adapted from an original post by Groq CEO and Founder, Jonathan Ross.

Feline-inspired vision technology enhances accuracy in challenging environments, paving the way for smarter, more efficient autonomous systems.

Researchers have unveiled a vision system inspired by feline eyes to enhance object detection in various lighting conditions. Featuring a unique shape and reflective surface, the system reduces glare in bright environments and boosts sensitivity in low-light scenarios. By filtering unnecessary details, this technology significantly improves the performance of single-lens cameras, representing a notable advancement in robotic vision capabilities.

Autonomous systems like drones, self-driving cars, and robots are becoming more common in our daily lives. However, they often struggle to “see” well in different environments — like bright sunlight, low light, or when objects blend into complex backgrounds. Interestingly, nature may already have the solution to this problem.

By using sensor-embedded sponges and data, Vienna researchers quickly trained robots to clean washbasins.

Thanks to researchers at TU Wein in Vienna, the promise of housecleaning robots is one step closer. The team has developed a self-learning robot to mimic humans to complete simple tasks like cleaning washbasins.

Continue reading “This robot mimics humans, cleans washbasins, completes multiple tasks” »

With its unique design consisting of two wheels and gripper arms, evoBOT keeps itself balanced while performing a range of tasks.

EvoBOT, a uniquely shaped autonomous mobile robot, recently completed its first test runs at the Munich Airport.

A study introduces AI2BMD, an artificial intelligence-based dynamics simulation program that uses protein fragmentation with a machine learning force field to accurately and efficiently model the folding and unfolding of large proteins.