Lifeboat Foundation

It’s hard to see more than a handful of stars from Princeton University, because the lights from New York City, Princeton, and Philadelphia prevent our sky from ever getting pitch black, but stargazers who get into more rural areas can see hundreds of naked-eye stars — and a few smudgy objects, too.

The biggest smudge is the Milky Way itself, the billions of stars that make up our spiral galaxy, which we see edge-on. The smaller smudges don’t mean that you need glasses, but that you’re seeing tightly packed groups of stars. One of the best-known of these “clouds” or “clusters” — groups of stars that travel together — is the Pleiades, also known as the Seven Sisters. Clusters are stellar nurseries where thousands of stars are born from clouds of gas and dust and then disperse across the Milky Way.

Continue reading “AI Detects Incredible Stream of Stars That Extends Thousands of Light-Years Across the Milky Way” »

A team of researchers working at Johannes Kepler University has developed an autonomous drone with a new type of technology to improve search-and-rescue efforts. In their paper published in the journal Science Robotics, the group describes their drone modifications. Andreas Birk with Jacobs University Bremen has published a Focus piece in the same journal issue outlining the work by the team in Austria.

Finding people lost (or hiding) in the forest is difficult because of the tree cover. People in planes and helicopters have difficulty seeing through the canopy to the ground below, where people might be walking or even laying down. The same problem exists for thermal applications—heat sensors cannot pick up readings adequately through the canopy. Efforts have been made to add drones to search-and–rescue operations, but they suffer from the same problems because they are remotely controlled by pilots using them to search the ground below. In this new effort, the researchers have added new technology that both helps to see through the tree canopy and to highlight people that might be under it.

Continue reading “An autonomous drone for search and rescue in forests using optical sectioning algorithm” »

1. Bigelow must be pissed.

2. A giant ring like that would make a hell of a spacecraft to get around the solar system.

Lawrence Klaes shared a link to the group: Space Settlement Alliance.

Continue reading “Dreams Come True: First-Ever Luxury Space Hotel Nears Launch” »

Over the past few decades, roboticists and computer scientists have developed artificial systems that replicate biological functions and human abilities in increasingly realistic ways. This includes artificial intelligence systems, as well as sensors that can capture various types of sensory data.

When trying to understand properties of objects and how to grasp them or handle them, humans often rely on their sense of touch. Artificial sensing systems that replicate human touch can thus be of great value, as they could enable the development of better performing and more responsive robots or prosthetic limbs.

Researchers at Sungkyunkwan University and Hanyang University in South Korea have recently created an artificial tactile sensing system that mimics the way in which humans recognize objects in their surroundings via their sense of touch. This system, presented in a paper published in Nature Electronics, uses sensors to capture data associated with the tactile properties of objects.

Without GPS, autonomous systems get lost easily. Now a new algorithm developed at Caltech allows autonomous systems to recognize where they are simply by looking at the terrain around them—and for the first time, the technology works regardless of seasonal changes to that terrain.

Details about the process were published on June 23 in the journal Science Robotics.

The general process, known as visual terrain-relative navigation (VTRN), was first developed in the 1960s. By comparing nearby terrain to high-resolution satellite images, autonomous systems can locate themselves.

Harness the power of AI to quickly turn simple brushstrokes into realistic landscape images for backgrounds, concept exploration, or creative inspiration. 🖌️

The NVIDIA Canvas app lets you create as quickly as you can imagine.

Continue reading “Introducing the NVIDIA Canvas App | NVIDIA Studio” »

Imagine clothing that can warm or cool you, depending on how you’re feeling. Or artificial skin that responds to touch, temperature, and wicks away moisture automatically. Or cyborg hands controlled with DNA motors that can adjust based on signals from the outside world.

Welcome to the era of intelligent matter—an unconventional AI computing idea directly woven into the fabric of synthetic matter. Powered by brain-based computing, these materials can weave the skins of soft robots or form microswarms of drug-delivering nanobots, all while reserving power as they learn and adapt.

Sound like sci-fi? It gets weirder. The crux that’ll guide us towards intelligent matter, said Dr. W.H.P. Pernice at the University of Munster and colleagues, is a distributed “brain” across the material’s “body”— far more alien than the structure of our own minds.

In 2020, DeepMind solved one of biology’s biggest challenges. Now it’s working on using its AI to find drugs to target neglected diseases.

If you walk down the street shouting out the names of every object you see — garbage truck! bicyclist! sycamore tree! — most people would not conclude you are smart. But if you go through an obstacle course, and you show them how to navigate a series of challenges to get to the end unscathed, they would.

Most machine learning algorithms are shouting names in the street. They perform perceptive tasks that a person can do in under a second. But another kind of AI — deep reinforcement learning — is strategic. It learns how to take a series of actions in order to reach a goal. That’s powerful and smart — and it’s going to change a lot of industries.

Two industries on the cusp of AI transformations are manufacturing and supply chain. The ways we make and ship stuff are heavily dependent on groups of machines working together, and the efficiency and resiliency of those machines are the foundation of our economy and society. Without them, we can’t buy the basics we need to live and work.