In a new paper, researchers at DeepMind propose using the game Diplomacy as an environment for training reinforcement learning agents.
Category: robotics/AI – Page 1696
A new machine learning program called MISIM can figure out what a snippet of code is meant to do and offer up new code to make it faster or more efficient.
Computer programmers may soon design the ultimate program: A program that designs programs.
Last week, a team led by Justin Gottschlich, director of the machine programming research group at Intel, announced the creation of a new machine learning system that designs its own code. They call the system MISIM, Machine Inferred Code Similarity.
Gottschlich explained, “Intel’s ultimate goal for machine programming is to democratize the creation of software. When fully realized, machine programming will enable everyone to create software by expressing their intention in whatever fashion that’s best for them, whether that’s code, natural language or something else. That’s an audacious goal, and while there’s much more work to be done, MISIM is a solid step toward it.”
Eyeing a launch in 2023, DARPA’s Robotic Servicing of Geosynchronous Satellites (RSGS) program will focus the remainder of this year on completing the elements of the robotic payload. The objective of RSGS is to create an operational dexterous robotic capability to repair satellites in geosynchronous Earth orbit (GEO), extending satellite life spans, enhancing resilience, and improving reliability for the current U.S. space infrastructure.
Earlier this year, DARPA partnered with Space Logistics LLC, a wholly owned subsidiary of Northrop Grumman, to provide the spacecraft bus, launch, and operations of the integrated spacecraft. DARPA will provide the payload that flies on the bus, including the robotic arms, through an agreement with the U.S. Naval Research Laboratory (NRL).
In 2021, NRL will integrate the robotic arms onto the payload structure, and then is expected to begin environmental tests by the end of same year. After launch in 2023, it will take approximately nine months to reach GEO, and the program anticipates servicing satellites in mid-2024.
Despite China’s considerable strides, industry analysts expect America to retain its current AI lead for another decade at least. But this is cold comfort: China is already developing powerful new surveillance tools, and exporting them to dozens of the world’s actual and would-be autocracies. Over the next few years, those technologies will be refined and integrated into all-encompassing surveillance systems that dictators can plug and play.
Xi Jinping is using artificial intelligence to enhance his government’s totalitarian control—and he’s exporting this technology to regimes around the globe.
Consumers are ending up increasingly responsive about sharing their data, as data integrity and security has turned into a developing concern. In any case, with the advent of nations teching up with facial recognition, even explorers need to truly begin thinking about what sort of data they could be reluctantly offering to nations, individuals and places.
Facial recognition innovation is a framework that is fit for identifying or confirming an individual from an advanced picture or a video frame. It works by comparing chosen facial highlights and faces inside a database. The technology is utilized in security frameworks and can be compared with different biometrics, for example, fingerprint or iris recognition frameworks. As of late, it has been grabbed and utilized as a business identification and advertising tool. The vast majority have a cell phone camera fit for recognizing features to perform exercises, for example, opening said a cell phone or making payments.
The worldwide market for facial recognition cameras and programming will be worth of an expected $7.8 billion, predicts Markets and Markets. Never again consigned to sci-fi films and books, the technology is being used in various vertical markets, from helping banks recognize clients to empowering governments to look out for criminals. Let’s look at some of the top countries adopting facial recognition technology.
Circa 2011
Gravity is no obstacle for this climbing robot. It scales vertical walls—even those made of smooth materials like glass. Jeff Krahn, an engineer from Simon Fraser University in British Columbia, created this gecko-inspired tank of a robot, which he detailed in a paper in the journal Smart Materials and Structures this week.
Like a gecko, which can hang on to sheer glass with just one toe, the climbing bot uses what physicists call Van der Waals forces to stick to the wall. Its tanklike tracks are covered in a dry adhesive, a polymer resembling silicon that allows adhesion without chemicals or added energy. The molecules that make up this substance are temporary dipoles; they have a positively charged side and a negatively charged side. The charged sides of the molecules are attracted to their corresponding opposites on the wall the robot is climbing: negative to positive, positive to negative. Given enough surface area for these attractions to take place, Van der Waals forces can keep a pretty substantial weight stuck to a vertical wall. The climbing bot, for example, weighs in at half a pound.
Researchers from the Institute of Industrial Science at The University of Tokyo designed and built specialized computer hardware consisting of stacks of memory modules arranged in a 3D-spiral for artificial intelligence (AI) applications. This research may open the way for the next generation of energy-efficient AI devices.
Machine learning is a type of AI that allows computers to be trained by example data to make predictions for new instances. For example, a smart speaker algorithm like Alexa can learn to understand your voice commands, so it can understand you even when you ask for something for the first time. However, AI tends to require a great deal of electrical energy to train, which raises concerns about adding to climate change.
Now, scientists from the Institute of Industrial Science at The University of Tokyo have developed a novel design for stacking resistive random-access memory modules with oxide semiconductor (IGZO) access transistor in a three-dimensional spiral. Having on-chip nonvolatile memory placed close to the processors makes the machine learning training process much faster and more energy-efficient. This is because electrical signals have a much shorter distance to travel compared with conventional computer hardware. Stacking multiple layers of circuits is a natural step, since training the algorithm often requires many operations to be run in parallel at the same time.
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Machine Learning offers important new capabilities for solving today’s complex problems, but it’s not a panacea. To get beyond the hype, engineers and scientists must discern how and where machine learning tools are the best option — and where they are not.
A drone has successfully inspected a 19.4 meter high oil tank onboard a Floating Production, Storage and Offloading vessel. The video shot by the drone was interpreted in real-time by an algorithm to detect cracks in the structure.
Scout Drone Inspection and class society DNV GL have been working together to develop an autonomous drone system to overcome the common challenges of tank inspections. For the customer, costs can run into hundreds of thousands of dollars as the tank is taken out of service for days to ventilate and construct scaffolding. The tanks are also tough work environments, with surveyors often having to climb or raft into hard to reach corners. Using a drone in combination with an algorithm to gather and analyse video footage can significantly reduce survey times and staging costs, while at the same time improving surveyor safety.
“We’ve been working with drone surveys since 2015,” said Geir Fuglerud, director of ofshore classification at DNV GL – Maritime. “This latest test showcases the next step in automation, using AI to analyse live video. As class we are always working to take advantage of advances in technology to make our surveys more efficient and safer for surveyors, delivering the same quality while minimising our operational downtime for our customers.”