Lifeboat Foundation

Ban Killer Robots

“Robotic weapons that target and destroy without human supervision are poised to start a revolution in warfare comparable to the invention of gunpowder or the atomic bomb. The prospect poses a dire threat to civilians—and could lead to some of the bleakest scenarios in which artificial intelligence runs amok. A prohibition on killer robots, akin to bans on chemical and biological weapons, is badly needed. But some major military powers oppose it.”

Weapons that kill enemies on their own threaten civilians and soldiers alike.

Diving into the autonomous submarine race, DARPA has awarded contracts to three companies as part of its Manta Ray Program. Intended to support a new generation of long-duration, long-range Unmanned Underwater Vehicles (UUVs), the end goal is to produce robotic vehicles that can operate for months without maintenance or human logistics support.

UUVs have advanced so far and so fast in the past 20 years that today major navies like those of the US and the UK are developing vehicles that are so large and so long-range that they are essentially unmanned versions of conventional submarines with the crew spaces removed.

The problem is that sailors are aboard their boats for a reason, which means that future UUVs need to be able to maintain themselves and do without humans to provide logistical support like refueling. This would mean that commanders would have more capabilities at their disposal without being hampered by the UUVs being dependent on manned vessels and ports that would reduce the hosts’ flexibility and availability.

A side-by-side comparison shows just how much Boston Dynamics’ bipedal robots improved in 10 years. The progress is astounding.

Over the past decade or so, researchers worldwide have developed increasingly advanced techniques to enable robot navigation in a variety of environments, including on land, in the air, underwater or on particularly rough terrains. To be effective, these techniques should allow robots to move around in their surroundings both safely and efficiently, saving as much energy as possible.

Researchers at the Indian Institute of Technology Kharagpur in India have recently developed a new approach to achieve efficient path planning in mobile robots. Their method, presented in a paper published in Springer Link’s Nature-Inspired Computation in Navigation and Routine Problems, is based on the use of a flower pollination algorithm (FPA), a soft computing-based tool that can identify ideal solutions to a given problem by considering a number of factors and criteria.

“Flower pollination algorithms (FPAs) have shown their potential in various engineering fields,” Atul Mishra, one of the researchers who carried out the study, told TechXplore. “In our study, we used the algorithm to solve the problem of path planning for mobile robots. Our prime objective was to plan, in the least time possible, the most optimal path in terms of minimum path length and energy consumption, with maximum safety.”

But lockdowns and forced quarantines on this scale or the nature of some methods — like the collection of mobile phone location data and facial recognition technology to track people’s movements — cannot readily be replicated in other countries, especially democratic ones with institutional protections for individual rights.

And so Singapore, Taiwan and Hong Kong might be more instructive examples. All three places were especially vulnerable to the spread of the infection because of close links with mainland China — especially in early January, as they were prime destinations for Chinese travelers during the upcoming Lunar New Year holiday. And yet, after all three experienced outbreaks of their own, the situation seems to have stabilized.

As of midday Friday, Singapore had 187 cases confirmed and no deaths (for a total population of about 5.7 million), Taiwan had 50 confirmed cases including 1 death (for a total population of about 23.6 million) and Hong Kong had 131 confirmed cases including 4 deaths (for a total population of about 7.5 million).

“In the case of the Industrial Revolution, people’s lives didn’t improve for seven decades,” Frey says. “That’s two generations. I think we need to be very concerned about some of these short-term effects on people.”

Frey says for seven decades wages were stagnant, food consumption decreased and “people’s living standards deteriorated.” The economy was doing quite well, but most of the workers weren’t seeing the benefits of that economy.

“Because people’s living standards deteriorated, people rioted against mechanized factories. The Luddites are often portrayed as these irrational enemies of progress, and to some extent, that’s right if you take a very long term view,””

Continue reading “If this era of automation mirrors the past, we’re in trouble” »

Scientific and medical communities worldwide are using AI to understand and contain Covid-19, treat infected patients, and ultimately develop vaccines that prevent future outbreaks.

Google announced Monday that it is making available an open-source library for quantum machine-learning applications.

TensorFlow Quantum, a free library of applications, is an add-on to the widely-used TensorFlow toolkit, which has helped to bring the world of machine learning to developers across the globe.

“We hope this framework provides the necessary tools for the quantum computing and machine learning research communities to explore models of both natural and artificial quantum systems, and ultimately discover new quantum algorithms which could potentially yield a quantum advantage,” a report posted by members of Google’s X unit on the AI Blog states.

Universal Basic Income usually creates a confusion and heated debates when people get divided between doomsday and Utopian scenarios. With faster than expected development of AI, we might be faced with no choice. In such case, what will UBI mean for most of us and how will it be implemented?