Lifeboat Foundation: Safeguarding Humanity
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Category: robotics/AI

Since the dawn of time, humankind has looked to the skies and sought to conquer them. For thousands of years we tried and failed until, at last, we could soar amongst the birds. We built biplanes that danced upon gusts of wind, strapped sails to our back and leapt off fog-drenched mountaintops, launched warplanes into the wild blue yonder to rain terror from above. The heavens were soon streaked with the vapor trails of jumbo jets; the oligarchy used its deep pockets for casual jaunts to the threshold of outer space. And then, with the skies at last firmly in our dominion, we once again turned our eyes upward and declared, “Know what would look great up there? Pizza.”

The technology to flood our skies with millions of pizza boxes does not exist just yet, but it’s taken a huge leap forward in Israel, where, The Wall Street Journal reports, Pizza Hut is launching the world’s first ever full-time drone delivery service. The pilot program is being heavily regulated by the government, and Pizza Hut’s human delivery drivers don’t need to worry about being replaced (yet), as the drones will not be making direct-to-customer drop-offs. Instead, the flying robots will bring multiple orders to designated landing zones outside of Pizza Hut’s normal delivery radius, where they’ll be picked up by a driver who will take the pizzas to their final destinations.

The drones’ home base will be a Pizza Hut located in Bnei Dror in Northern Israel, and will allow the restaurant to provide delivery service to an additional 7000 households. The Ministry of Transportation has limited the drones’ flight area to about 50 square miles, and each drone’s limited battery life means there’s little chance of one going rogue.

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There were the cleaners, with large padded feet, who were apparently polishing their way the whole length…’ — Arthur C. Clarke, 1972.

IceBot Antarctic (Planetary?) Robotic Explorers Made Of Ice ‘Some will combine in place to form more complicated structures, like excavators or centipedes.’ — Greg Bear, 2015.

Study: Robots Encourage Humans To Take Risks Not exactly Three Laws compliant.

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BladeBUG Robots Clean Massive Wind Turbine Blades ‘There were the cleaners, with large padded feet, who were apparently polishing their way the whole length…’ — Arthur C. Clarke, 1972.

IceBot Antarctic (Planetary?) Robotic Explorers Made Of Ice ‘Some will combine in place to form more complicated structures, like excavators or centipedes.’ — Greg Bear, 2015.

Study: Robots Encourage Humans To Take Risks Not exactly Three Laws compliant.

Read more | >

Researchers at Harvard University have recently devised a system based on Wi-Fi sensing that could enhance the collaboration between robots operating in unmapped environments. This system, presented in a paper pre-published on arXiv, can essentially emulate antenna arrays in the air as a robot moves freely in a 2-D or 3D environment.

“The main goal of our paper was to leverage arbitrary 3D trajectories for a (UAV or UGV) equipped with an on-board estimation sensor,” Ninad Jadhav, one of the researchers who carried out the study, told TechXplore. “This allows a Wi-Fi-signal-receiving robot to estimate the spatial direction (in azimuth and elevation) of other neighboring robots by capturing all the wireless signal paths traveling between the transmitting and receiving robot (which we call AOA profile). Additionally, we also characterized how the trajectory shape impacts the AOA profile using Cramer Rao bound.”

In their previous studies, Jadhav and his colleagues focused on robot collaboration scenarios in which the robots followed 2-D trajectories with a limited set of geometries (e.g., linear or curved). The new system they created, on the other hand, is applicable to scenarios where robots are moving freely, following a wider range of trajectories.

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This prompted a pair of neuroscientists to see if they could design an AI that could learn from few data points by borrowing principles from how we think the brain solves this problem. In a paper in Frontiers in Computational Neuroscience, they explained that the approach significantly boosts AI’s ability to learn new visual concepts from few examples.

“Our model provides a biologically plausible way for artificial neural networks to learn new visual concepts from a small number of examples,” Maximilian Riesenhuber, from Georgetown University Medical Center, said in a press release. “We can get computers to learn much better from few examples by leveraging prior learning in a way that we think mirrors what the brain is doing.”

Several decades of neuroscience research suggest that the brain’s ability to learn so quickly depends on its ability to use prior knowledge to understand new concepts based on little data. When it comes to visual understanding, this can rely on similarities of shape, structure, or color, but the brain can also leverage abstract visual concepts thought to be encoded in a brain region called the anterior temporal lobe (ATL).

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Weird, right?

The team’s critical insight was to construct a “viral language” of sorts, based purely on its genetic sequences. This language, if given sufficient examples, can then be analyzed using NLP techniques to predict how changes to its genome alter its interaction with our immune system. That is, using artificial language techniques, it may be possible to hunt down key areas in a viral genome that, when mutated, allow it to escape roaming antibodies.

It’s a seriously kooky idea. Yet when tested on some of our greatest viral foes, like influenza (the seasonal flu), HIV, and SARS-CoV-2, the algorithm was able to discern critical mutations that “transform” each virus just enough to escape the grasp of our immune surveillance system.

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Moscow has revealed a plan to spend $2.4 million on a giant database containing information about every single city resident, including passport numbers, insurance policies, salaries, car registrations – and even their pets.

It will also include work and tax details, school grades, and data from their ‘Troika’ care – Moscow’s unified transport payment system, used on the metro, busses and trains.

The new proposal will undoubtedly increase fears about ever-growing surveillance in the Russian capital, where the number of facial recognition cameras has recently been increased.

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