From top-left to bottom right: Joel Reed, Tom Ryden, Andra Keay, Jeff Burnstein, Matt Johnson-Roberson and Ritch Ramey joined Congressman Mike Doyle for a robotics roundtable discussion. | Source: Carnegie Mellon University.
Carnegie Mellon University held a robotics caucus virtual roundtable last week with leaders from the U.S. robotics industry. The roundtable discussed the future of the industry and how the U.S. can keep up with the pace of the global industry.
The following speakers took part in the roundtable:
A US Robotics company is adding new artificial intelligence anomaly detection capabilities to its autonomous Scout System drone. A leading US provider of private wireless data, drone and automated data has announced that the new containment capabilities will enable oil and gas customers to minimize environmental risks, clean-up costs, fines, and litigation expenses.
Suasnews.com reports that the loss of containment analytics feature will accelerate early detection and location of crude oil leaks before they become critical to customers by providing frequent, autonomous inspections of oil and gas pumpjacks, heater treaters, tanks, pipes, pumps, and more via the autonomous Scout System. Autonomous drones have become a crucial component to ensuring safety and conducting regular inspections within the oil and gas industry.
A new type of technology has recently been developed. AI technology that mimics the human eye. Researchers at the University of Central Florida have created a device for AI that replicates the retina of the eye. This new discovery can lead to AI that can immediately identify objects, such as automated descriptions of photos captured with a camera or a phone. This technology can potentially be used in autonomous robots and self-driving cars as well.
Scidaily.com reports that this technology performs better than the eye in terms of the range of wavelengths it can perceive, from ultraviolet to visible light and on to the infrared spectrum. The technology expands upon previous work by the research team that created brain-like devices that can enable AI to work in remote regions and space.
You are on the PRO Robots channel and today we present you with some high-tech news. The first robot with self-awareness, a new breakthrough in the creation of general artificial intelligence, evolving robots, a Japanese home for a space colony, an unexpected turn in the fate of XPENG Robotics and other news from the world of high technology in one issue! Let’s roll!
0:00 In this video. 0:24 The first robot with self-awareness. 1:18 The first orbital flight of a prototype Starship. 1:56 PLATO algorithm. 3:00 New robot learning system. 3:53 Electronic skin for robots. 4:30 XPENG Robotics four-legged robot. 5:09 Artificial gravity architecture. 6:06 Project LINA — Lunar Outpost. 7:06 Electronic glove with suction cups. 7:52 Suspended system in a thermovacuum chamber. 8:28 Network of underground tunnels for unmanned cargo delivery. 9:29 Mass layoffs at Pudu Robotics. 10:12 Virtual organisms. 10:49 Engineers taught robotic arms to react unpredictably to dancers’ movements and music. 11:13 Quokka Robotics Cafe. #prorobots #robots #robot #futuretechnologies #robotics.
PRO Robots is not just a channel about robots and future technologies, we are interested in science, technology, new technologies and robotics in all its manifestations, science news, technology news today, science and technology news 2022, so that in the future it will be possible to expand future release topics. Today, our vlog just talks about complex things, follows the tech news, makes reviews of exhibitions, conferences and events, where the main characters are best robots in the world! Subscribe to the channel, like the video and join us!
You are on PRO Robots Channel, and today we present you with high-tech news. An exhibition of robot chefs in Japan and novelties from the robot exhibition Automate 2022 in the USA, new unusual robots for space, the unexpected discovery of a robot that visited the asteroid Bennu, and the first Italian humanoid robot. All the most interesting technology news in one issue!
PRO Robots is not just a channel about robots and future technologies, we are interested in science, technology, new technologies and robotics in all its manifestations, science news, technology news today, science and technology news 2022, so that in the future it will be possible to expand future release topics. Today, our vlog just talks about complex things, follows the tech news, makes reviews of exhibitions, conferences and events, where the main characters are best robots in the world! Subscribe to the channel, like the video and join us!
Humans are good at looking at images and finding patterns or making comparisons. Look at a collection of dog photos, for example, and you can sort them by color, by ear size, by face shape, and so on. But could you compare them quantitatively? And perhaps more intriguingly, could a machine extract meaningful information from images that humans can’t?
Now a team of Standford University’s Chan Zuckerberg Biohub scientists has developed a machine learning method to quantitatively analyze and compare images—in this case microscopy images of proteins—with no prior knowledge. As reported in Nature Methods, their algorithm, dubbed “cytoself,” provides rich, detailed information on protein location and function within a cell. This capability could quicken research time for cell biologists and eventually be used to accelerate the process of drug discovery and drug screening.
“This is very exciting—we’re applying AI to a new kind of problem and still recovering everything that humans know, plus more,” said Loic Royer, co-corresponding author of the study. “In the future we could do this for different kinds of images. It opens up a lot of possibilities.”
Researchers have been trying to build artificial synapses for years in the hope of getting close to the unrivaled computational performance of the human brain. A new approach has now managed to design ones that are 1,000 times smaller and 10,000 times faster than their biological counterparts.
Despite the runaway success of deep learning over the past decade, this brain-inspired approach to AI faces the challenge that it is running on hardware that bears little resemblance to real brains. This is a big part of the reason why a human brain weighing just three pounds can pick up new tasks in seconds using the same amount of power as a light bulb, while training the largest neural networks takes weeks, megawatt hours of electricity, and racks of specialized processors.
That’s prompting growing interest in efforts to redesign the underlying hardware AI runs on. The idea is that by building computer chips whose components act more like natural neurons and synapses, we might be able to approach the extreme space and energy efficiency of the human brain. The hope is that these so-called “neuromorphic” processors could be much better suited to running AI than today’s computer chips.
In medicine, a prosthesis, or a prosthetic implant, is an artificial device that replaces a missing body part, which may be lost through trauma, disease, or a condition present at birth. A pioneering project to develop advanced pressure sensors for use in robotic systems could transform prosthetics and robotic limbs. The innovative research project aspires to develop sensors that provide enhanced capabilities to robots, helping improve their motor skills and dexterity, through the use of highly accurate pressure sensors that provide haptic feedback and distributed touch.
It is led by the University of the West of Scotland (UWS), Integrated Graphene Ltd, and supported by the Scottish Research Partnership in Engineering (SRPe) and the National Manufacturing Institute for Scotland (NMIS) Industry Doctorate Programme in Advanced Manufacturing. This is not for the first time when the team of highly talented researchers have decided to bring the much needed transformative change in prosthetics and robotic limbs.
The human brain relies on a constant stream of tactile information to carry out basic tasks, like holding a cup of coffee. Yet some of the most advanced motorized limbs — including those controlled solely by a person’s thoughts — don’t provide this sort of feedback. As a result, even state-of-the-art prosthetics can often frustrate their users.
The greatest artistic tool ever built, or a harbinger of doom for entire creative industries? OpenAI’s second-generation DALL-E 2 system is slowly opening up to the public, and its text-based image generation and editing abilities are awe-inspiring.
The pace of progress in the field of AI-powered text-to-image generation is positively frightening. The generative adversarial network, or GAN, first emerged in 2014, putting forth the idea of two AIs in competition with one another, both “trained” by being shown a huge number of real images, labeled to help the algorithms learn what they’re looking at. A “generator” AI then starts to create images, and a “discriminator” AI tries to guess if they’re real images or AI creations.
At first, they’re evenly matched, both being absolutely terrible at their jobs. But they learn; the generator is rewarded if it fools the discriminator, and the discriminator is rewarded if it correctly picks the origin of an image. Over millions and billions of iterations – each taking a matter of seconds – they improve to the point where humans start struggling to tell the difference.
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