Lifeboat Foundation

Evolution, the process by which living organisms adapt to their surrounding environment over time, has been widely studied over the years. As first hypothesized by Darwin in the mid 1800s, research evidence suggests that most biological species, including humans, continuously adapt to new environmental circumstances and that this ultimately enables their survival.

In recent years, researchers have been developing advanced computational techniques based on artificial neural networks, which are architectures inspired by biological neural networks in the human brain. Models based on artificial neural networks are trained to optimize millions of synaptic weights over millions of observations in order to make accurate predictions or classify data.

Researchers at Princeton University have recently carried out a study investigating the similarities and differences between artificial and biological neural networks from an evolutionary standpoint. Their paper, published in Neuron, compares the evolution of biological neural networks with that of artificial ones using psychology theory.

A research group from Politecnico di Milano has developed a new computing circuit that can execute advanced operations, typical of neural networks for artificial intelligence, in one single operation.

The circuit performance in terms of speed and energy consumption paves the way for a new generation of artificial intelligence computing accelerators that are more energy efficient and more sustainable on a global scale. The study has been recently published in the prestigious Science Advances.

Recognizing a face or an object, or correctly interpreting a word or a musical tune are operations that are today possible on the most common electronic gadgets, such as smartphones and tablets, thanks to artificial intelligence. For this to happen, complicated neural networks needs to be appropriately trained, which is so energetically demanding that, according to some studies, the carbon footprint that derives from the training of a complex neural network can equal the emission of 5 cars throughout their whole life cycle.

Robin Murphy, a roboticist at Texas A&M University has published a Focus piece in the journal Science Robotics outlining her views on the robots portrayed in “Star Wars,” most particularly those featured in “The Mandalorian” and “The Book of Boba Fett.” In her article, she says she believes that the portrayals of robots in both movies are quite creative, but suggests they are not wild enough to compete with robots that are made and used in the real world today.

Murphy begins by noting that one robot in particular, IG-11 in the Mandalorian, makes for good viewing with a rotating head that allows for shooting at targets in any direction, but she also notes that such a robot would very likely be overly susceptible to joint failure and would be saddled with huge computational demands. She suggests a more practical design would involve the use of fixed-array sensors.

Murphy also notes that robots in “Star Wars” movies do fail on occasion, generally during suspenseful scenes, which she further notes might explain why the empire met with its demise. As just one example, she wonders why the stormtroopers so often miss their targets. She also notes that in some ways, droids in “Star Wars” movies tend to be far more advanced than droids in the real world, allowing them to hold human-like jobs such as bartending, teaching or translating. In so doing, she points out, producers of the movies have shied away from showing them doing more mundane work, like mining.

As transportation becomes autonomous, maritime navigation is also set for a major change. Systems like Orca AI will help in rapid transitions.

With drone-in-a-box (DiaB) solutions emerging as a growth segment within the drone industry, Norway-based Nordic Unmanned has entered into an acquisition agreement with DiaB specialist DroneMatrix.

This partnership will enable both companies to scale their commercial offerings through new services and solutions.

The steering wheel, gas, and brakes that safety drivers will use if they need to take over are separate from the system the buses use to navigate autonomously. During the initial two-week testing period, buses will run without passengers, but the companies involved are aiming to have riders on board by summer.

The self-driving software made by Fusion Processing, called CAVstar for “connected and autonomous vehicles,” isn’t limited to radar, lidar, or cameras, but rather integrates all three. The buses are clearly marked as autonomous so nearby drivers are aware that a computer’s running the show. The question is, how much will this impact drivers’ behavior and relevant driving decisions? Would you feel less rude cutting off a driverless bus? More obliged to let it pass you? Or just sort of confused by the whole situation?

Each bus can carry 36 passengers, and the number of planned trips per day mean the autonomous buses could move up to 10,000 passengers a week. The project’s leaders anticipate the self-driving buses reducing average trip time and improving schedule reliability of the route. This sounds like it’ll mostly be a good thing, but what will happen when, say, an elderly or disabled passenger needs some extra time to get on or off the bus?

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You are on the PRO Robots channel and today we present an issue dedicated to the future of mankind. What will the world be like in 2030, 2040 and 2050? What future technologies will become reality? What does the future hold as technology and artificial intelligence evolve? How will humans themselves change in the future? The answers to these questions are in our video. Watch to the end and write in the comments, how do you imagine the world in 2050?

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Machine intelligence and artificial intelligence. How it may impact the future of humanity — A discussion with award winning science fiction author Robert J. Sawyer.

The exponential growth in computing powers, machine intelligence and artificial intelligence suggests that within a few decades intelligent machines will have more capability than us. How will they interact with humanity and what are the risks?

Continue reading “Machine Intelligence — A conversation with Robert J. Sawyer, the award winning sci-fi author” »

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MIT researchers have developed a system that enables a robot to learn a new pick-and-place task based on only a handful of human examples. This could allow a human to reprogram a robot to grasp never-before-seen objects, presented in random poses, in about 15 minutes.