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Category: robotics/AI – Page 53

How Much Information is in DNA?

Such questions quickly run into the limits of knowledge for both biology and computer science. To answer them, we need to figure out what exactly we mean by “information” and how that’s related to what’s happening inside cells. In attempting that, I will lead you through a frantic tour of information theory and molecular biology. We’ll meet some strange characters, including genomic compression algorithms based on deep learning, retrotransposons, and Kolmogorov complexity.

Ultimately, I’ll argue that the intuitive idea of information in a genome is best captured by a new definition of a “bit” — one that’s unknowable with our current level of scientific knowledge.

System lets robots identify an object’s properties through handling

A human clearing junk out of an attic can often guess the contents of a box simply by picking it up and giving it a shake, without the need to see what’s inside. Researchers from MIT, Amazon Robotics, and the University of British Columbia have taught robots to do something similar.

They developed a technique that enables robots to use only internal sensors to learn about an object’s weight, softness, or contents by picking it up and gently shaking it. With their method, which does not require external measurement tools or cameras, the can accurately guess parameters like an object’s mass in a matter of seconds.

This low-cost technique could be especially useful in applications where cameras might be less effective, such as sorting objects in a dark basement or clearing rubble inside a building that partially collapsed after an earthquake.

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NASA Cracks 30-Year X-ray Mystery With Blazing Black Hole Light Show

Astronomers using NASA’s IXPE satellite have finally cracked a cosmic mystery—how X-rays are produced in the energetic jets of supermassive black holes like the blazar BL Lacertae. The blazar BL Lacertae—a type of active galaxy powered by a supermassive black hole with bright, fast-moving jets ai

The Rise of the Humanoid Robotic Machines Is Nearing

By Chuck Brooks.

Source: Forbes

Robotics is now revolutionizing numerous industry sectors through the integration of artificial intelligence, machine learning, and reinforcement learning, as well as advances in computer vision that empower robots to make complicated judgments.

Industrial automation in factories and warehouses has been the main emphasis of robotics for many years because of its efficiency and affordability. These settings are usually regulated, organized, and predictable. Consequently, industries like manufacturing, agriculture, warehouse operations, healthcare, and security have utilized robotics to automate mundane programmable tasks.

Robotics in those and many other industries are becoming more refined and capable with the contributions of new material sciences, and artificial intelligence tools. It now appears that with those advances, we are at the precipice of building functional, dexterous, and autonomous humanoid robots that were once the topic of futurist writing.

Novel Mechanical Metamaterials with Magnetically Controlled Properties

Researchers from Universidad Carlos III de Madrid (UC3M) and Harvard University have experimentally demonstrated that new artificial materials known as metamaterials, with magnetic properties, can have their mechanical and structural behavior reprogrammed without altering their composition. This breakthrough could drive innovations in fields such as soft robotics and biomedicine.

The study explains how flexible magnets embedded within the structure of mechanical metamaterials can be used to reprogram their behavior.

The integration of flexible magnets in metamaterials allows for reprogrammable structures, offering vast potential in robotics and biomedical engineering.

Amuse, a songwriting AI collaborator for music composers

Wouldn’t it be great if music creators had someone to brainstorm with, help them when they’re stuck, and explore different musical directions together? Researchers at KAIST and Carnegie Mellon University (CMU) have developed AI technology similar to a fellow songwriter who helps create music.

The work is published in Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems.

The system developed by Professor Sung-Ju Lee’s research team, Amuse, is an AI-based system that converts various forms of inspiration such as text, images, and audio into harmonic structures (chord progressions) to support composition.