Lifeboat Foundation

Modern astrophysics has enabled scientists to observe the universe with unprecedented clarity, from exoplanets to entire galaxies.

Despite our galaxy blocking some views, advanced tools like the James Webb Space Telescope and upcoming projects such as the Square Kilometre Array are pushing the boundaries of our cosmic understanding. Visualization techniques help researchers explore the universe in both space and time, revealing phenomena like fast radio bursts. Looking ahead, scientists hope to capture images of distant exoplanets and unravel mysteries such as dark energy and the expansion of the universe.

Observing the universe: from exoplanets to galaxies.

Researchers have developed a hydrogel that can learn to play the game Pong, demonstrating that even simple materials can exhibit adaptive behaviors akin to those seen in living systems.

The study, led by Dr. Yoshikatsu Hayashi from the University of Reading, also revealed that similar hydrogels could mimic cardiac tissue, potentially offering new avenues for studying heart arrhythmias and reducing animal testing in medical research.

Continue reading “Pong Prodigy: ‘Hydrogel Brain’ Defies Expectations With Deep Learning” »

AI is shaking up industries — and software engineering is no exception.

In a leaked recording of a June fireside chat obtained by Business Insider, Amazon Web Services CEO Matt Garman reportedly told employees that AI is changing what being a software engineer means —and essentially changes the job description.

“If you go forward 24 months from now, or some amount of time — I can’t exactly predict where it is — it’s possible that most developers are not coding,” Garman said, adding later that the developer role would look different next year compared to 2020.

New technique lets robots detect force and interpret touch without extra sensors.

Researchers used internal sensors and machine learning to give robots an innate sense of touch, bypassing expensive external sensors.

Continue reading “German scientists give robots a human touch feel with AI, sensors” »

A new study involving an AI scientist that can run its own experiments is both fascinating and terrifying, changing science forever.

Robotic automation has become a game-changer in addressing labor shortages. While traditional rigid grippers have effectively automated various routine tasks, boosting efficiency and productivity in industries that deal with objects of well-defined specifications, they fall short in sectors like the food industry, where delicate objects of varying sizes and shapes need to be handled. In these cases, a more specialized type of gripper is required.

“Bioinspired soft robotics seeks to develop technologies that draw inspiration from nature and leverage advanced materials and fabrication processes,” said Dr. Pablo Valdivia y Alvarado, Associate Professor at the Singapore University of Technology and Design (SUTD).

Soft grippers inspired by the natural dexterity and control of human hands are particularly well-suited to the food industry. They can adapt to objects of varying sizes and shapes while distributing forces more evenly, making them ideal for handling delicate items.

According to a paper published by Nature Computational Science on Friday, the researchers developed a model that bridges the gap between big, externally complex AI networks and the small, internally complex workings of the brain.

Industry experts said the team’s findings could mark a pivotal shift in AI development, prompting further exploration of computing solutions that are not dependent on silicon chips.

Designed to mimic human decision-making and physical interaction, the Astribot S1 robot can handle tasks that would traditionally require human dexterity and judgment.

Launched by Stardust Intelligence, a Chinese company, the robot has a human-like upper body structure mounted on a wheeled base.

Continue reading “China’s new humanoid robot does it all — from Kung Fu to cooking” »

A recent study by UC San Diego researchers brings fresh insight into the ever-evolving capabilities of AI. The authors looked at the degree to which several prominent AI models, GPT-4, GPT-3.5, and the classic ELIZA could convincingly mimic human conversation, an application of the so-called Turing test for identifying when a computer program has reached human-level intelligence.

The results were telling: In a five-minute text-based conversation, GPT-4 was mistakenly identified as human 54 percent of the time, contrasted with ELIZA’s 22 percent. These findings not only highlight the strides AI has made but also underscore the nuanced challenges of distinguishing human intelligence from algorithmic mimicry.

Continue reading “Did AI Just Pass the Turing Test?” »