Lifeboat Foundation

As capable as robots are, the original animals after which they tend to be designed are always much, much better. That’s partly because it’s difficult to learn how to walk like a dog directly from a dog — but this research from Google’s AI labs make it considerably easier.

The goal of this research, a collaboration with UC Berkeley, was to find a way to efficiently and automatically transfer “agile behaviors” like a light-footed trot or spin from their source (a good dog) to a quadrupedal robot. This sort of thing has been done before, but as the researchers’ blog post points out, the established training process can often “require a great deal of expert insight, and often involves a lengthy reward tuning process for each desired skill.”

That doesn’t scale well, naturally, but that manual tuning is necessary to make sure the animal’s movements are approximated well by the robot. Even a very doglike robot isn’t actually a dog, and the way a dog moves may not be exactly the way the robot should, leading the latter to fall down, lock up or otherwise fail.

A new programme from the US Defense Advanced Research Projects Agency (DARPA) aims to address a key weakness of autonomous and semi-autonomous land systems: the need for active illumination to navigate in low-light conditions.

Unmanned systems rely on active illumination — anything that emits light or electromagnetic radiation, such as light detection and ranging (LIDAR) systems — to navigate at night or underground.

However, according to Joe Altepeter, programme manager in DARPA’s Defense Sciences Office, this approach creates significant security concerns, as such emissions could be detected by potential adversaries.

Tech entrepreneur Roya Mahboob founded the trail-blazing programme in the Afghani city of Herat, selecting young girls from high schools across the country, usually aged 14 or 15, for the programme.

It was a passion project for Ms Mahboob, a serial entrepreneur who became one of Afghanistan’s first female chief executives at 23, established a non-profit organisation to help young women to build digital literacy, and has since been named one of Time Magazine’s 100 most influential people.

Participants are selected for the Dreamers based on their entrance exam for the 9th and 10th grades, and the very best of them then get to join the national team – the Afghan Girls Robotics Team – for international competitions. There are about 50 participants in the Dreamers, and they stay in the programme for about two years.

Is a low-cost Israeli #ventilator the key to saving #coronavirus patients in #Iran, Africa and more?

“We are not talking about a website for the general public, we are talking about engineers and other experts, and we know the groups who are working on it because they are in touch with us via WhatsApp and emails, to ask questions and understand how to proceed,” he said.

“AmboVent” is a device inspired by the bag-valve mask ventilators that paramedics use when they’re manually ventilating patients in an ambulance, which also offers controls for respiration rate, volume, and maximum peak pressure. Organizations involved in its development include the Magen David Adom, Israeli Air Force 108 Electronics Depot; physicians from Hadassah and Tel Aviv Sourasky medical centers; Microsoft; Rafael, an Israeli defense contractor; Israeli Aerospace Industries; and mentors and students from FIRST Israel, a student robotics organization.

Continue reading “Coronavirus: Israeli researchers design low-cost open-source ventilator” »

Welcome to the twilight zone.

TOKYO (Reuters) — Spring graduation ceremonies in Japan have been cancelled because of the coronavirus pandemic, but students at one school were able to attend remotely by controlling avatar robots while logged on at home.

The robots, dubbed “Newme” by developer ANA Holdings, were dressed in graduation caps and gowns for the ceremony at the Business Breakthrough University in Tokyo.

Continue reading “Robots replace Japanese students at graduation amid coronavirus” »

AI has revealed that mice have a range of facial expressions that show they feel — offering fresh clues about how emotional responses arise in human brains.

Scientists at the Max Planck Institute of Neurobiology in Germany made the discovery by recording the faces of lab mice when they were exposed to different stimuli, such as sweet flavors and electric shocks. The researchers then used machine learning algorithms to analyze how the rodents’ faces changed when they experienced different feelings.

Circa 2017

The era of merging our minds with technology has begun. Already, we can hack the brain to treat diseases such as Parkinson’s or help paralyzed people move again. But what if you could install a chip in your head that would not only fix any health issues, but could amp up your brainpower — would you remember every word said during a meeting, finish crossword puzzles faster, drive better thanks to enhanced senses, or pick up a new language before your next trip?

That’s the future envisioned by Elon Musk, the Tesla and SpaceX CEO who recently announced Neuralink, a new company dedicated to blending human brains with computers. In Musk’s view, we’ll have to keep pace with ever-smarter artificial intelligence by implanting a “neural lace,” or sci-fi inspired machine interface that will make us smarter.

Continue reading “These brain-boosting devices could give us intelligence superpowers” »

That vision may have come a step closer after researchers at the University of California, San Francisco demonstrated that they could translate brain signals into complete sentences with error rates as low as three percent, which is below the threshold for professional speech transcription.

While we’ve been able to decode parts of speech from brain signals for around a decade, so far most of the solutions have been a long way from consistently translating intelligible sentences. Last year, researchers used a novel approach that achieved some of the best results so far by using brain signals to animate a simulated vocal tract, but only 70 percent of the words were intelligible.

The key to the improved performance achieved by the authors of the new paper in Nature Neuroscience was their realization that there were strong parallels between translating brain signals to text and machine translation between languages using neural networks, which is now highly accurate for many languages.

Social roboticist, Heather Knight, sees robots and entertainment a research-rich coupling. So she programmed a charming humanoid robot named DATA with jokes, and equipped it with sensors and algorithmic capabilities to help with timing and gauging a crowd. Then Knight and DATA hit the road on an international robot stand-up comedy tour. Their act landed stage time at a TED conference and Knight was profiled in Forbes 30 Under 30. Watching Data perform is much like watching an amateur stand-up comedian cutting her/his chops at an open mic night doing light comedy with a sweet but wooden delivery.

Knight’s goal is specific: