NASA's Artemis program will eventually need robots to help live off the lunar soil, and it's enlisting help from the public to make those robots viable. The space agency has picked winners from a design challenge that tasked people with improving the bucket drums RASSOR (Regolith Advanced Surface Systems Operations Robot) will use to dig on the Moon. The victors all had clever designs that should capture lunar regolith with little effort -- important when any long-term presence might depend on bots like this. The winner was a trap from Caleb Clausing that uses a passive door to grab large amounts of soil while remaining dust-tolerant. Others included a simple-yet-effective drum from Michael R, another from Kyle St. Thomas that uses narrow drums, an efficient double-helix design from Stephan Weiβenböck and a model from Clix that uses both gravity and weight to help movement.

Our Innovation Analysts recently looked into emerging technologies and up-and-coming startups. As there is a large number of startups working on a wide variety of solutions, we want to share our insights with you. This time, we are taking a look at 5 promising behavioral algorithms startups. For our 5 top picks, we used a data-driven startup scouting approach to identify the most relevant solutions globally. The Global Startup Heat Map below highlights 5 interesting examples out of 126 relevant solutions.

Albert Einstein famously postulated that "the only real valuable thing is intuition," arguably one of the most important keys to understanding intention and communication. But intuitiveness is hard to teach -- especially to a machine. Looking to improve this, a team from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) came up with a method that dials us closer to more seamless human-robot collaboration. The system, called "Conduct-A-Bot," uses human muscle signals from wearable sensors to pilot a robot's movement. "We envision a world in which machines help people with cognitive and physical work, and to do so, they adapt to people rather than the other way around," says Professor Daniela Rus, director of CSAIL, deputy dean of research for the MIT Stephen A. Schwarzman College of Computing, and co-author on a paper about the system.

While current artificial intelligence (AI) technology holds strategic and transformative potential, it isn't always environmentally-friendly due to high energy consumption. To the rescue are researchers from Massachusetts Institute of Technology (MIT), who have devised a solution that not only lowers costs but, more importantly, reduces the AI model training's carbon footprint. Back in June 2019, the University of Massachusetts at Amherst revealed that the amount of energy utilized in AI model training equaled 626,000 pounds of carbon dioxide. Contemporary AI isn't just run on a personal laptop or simple server. Rather, deep neural networks are deployed on diverse arrays of specialized hardware platforms. The level of energy consumption required to power such AI technologies is approximately five times the lifetime carbon emissions from an average American car, including its manufacturing.

Like crystal balls for the universe's deeper mysteries, galaxies and other massive space objects can serve as lenses to more distant objects and phenomena along the same path, bending light in revelatory ways. Gravitational lensing was first theorized by Albert Einstein more than 100 years ago to describe how light bends when it travels past massive objects like galaxies and galaxy clusters. These lensing effects are typically described as weak or strong, and the strength of a lens relates to an object's position and mass and distance from the light source that is lensed. Strong lenses can have 100 billion times more mass than our sun, causing light from more distant objects in the same path to magnify and split, for example, into multiple images, or to appear as dramatic arcs or rings. The major limitation of strong gravitational lenses has been their scarcity, with only several hundred confirmed since the first observation in 1979, but that's changing, and fast.

Limarc is a Tokyo-based writer of all things pop culture, travel, and tech. Subscribe to get your daily round-up of top tech stories!

As Japan's second female astronaut to fly up in the Space Shuttle Discovery, Naoko Yamazaki didn't expect to spend a quarter of her time dusting, feeding mice and doing other menial jobs. It can cost more than $430 million a year to keep an astronaut in orbit, according to three-year-old startup called Gitai Inc. It's only possible to keep humans alive in outer space because of the money and effort poured into ensuring their safety. One way to bring down the cost and risks is to send an avatar -- a remotely controlled robot. "There's a need for robots that can help us," Yamazaki, 49, said.

The aim of this Foresight Brief is therefore merely to initiate a debate.

Chris Gannatti, head of research at ETF specialist WisdomTree, explains how artificial intelligence is being used to tackle Covid-19. Artificial Intelligence (AI) is proliferating more widely than ever before, having the potential to influence many aspects of daily life. Crisis periods, like we have seen with the Covid-19 pandemic, are often catalysts for the deployment of new innovations and technologies more quickly. The power of AI is being harnessed to tackle the Covid-19 pandemic, whether that be to better understand the rate of infection or by tracing and quickly identifying infections. While AI has been associated with the'future' and ideas such as the development of driverless cars, its legacy could be how it has impacted the world during this crisis.

Let's say you live in a country where there's been reports of massive outbreaks of a highly contagious viral infection. Hypothetically, let's call this infection "coronavirus." To avoid spreading this "coronavirus," many people have taken to wearing medical face masks when going about their everyday life. These masks don't do much, medically speaking, but it's considered the polite thing to do. Now, let's also say that the government there is notorious for widespread and unregulated use of facial-recognition technology as a way to both fight crime and to identify and silence political dissidents.