Using their artificial wings made out of foam, the robots are able to stay afloat simply by mimicking the flapping motion of real birds.
Category: robotics/AI – Page 1,860
Clint Brauer’s farm outside of Cheney, Kansas, could be described as Old MacDonald’s Farm plus robots. Along with 5,500 square feet of vegetable-growing greenhouses, classes teaching local families to grow their food, a herd of 105 sheep, and Warren G—a banana-eating llama named after the rapper—is a fleet of ten, 140-pound, battery-operated robots.
Brauer, the co-founder of Greenfield Robotics, grew up a farm kid. He left for the big city tech and digital world, but eventually made his way back to the family farm. Now, it’s the R&D headquarters for the Greenfield Robotics team, plus a working farm.
When Brauer returned to his agricultural roots, he did so with a purpose: to prove that food could be grown without harmful chemicals and by embracing soil- and planet-friendly practices. He did just that, becoming one of the premier farmers growing vegetables in Kansas without pesticides, selling to local markets, grocery store chains, and chefs.
The best way to prevent this is by focusing on the basics. America needs a major all-of-society push to increase the number of U.S. students being trained in both the fundamentals of math and in the more advanced, rigorous, and creative mathematics. Leadership in implementing this effort will have to come from the U.S. government and leading technology companies, and through the funding of ambitious programs. A few ideas come to mind: talent-spotting schemes, the establishment of math centers, and a modern successor to the post-Sputnik National Defense Education Act, which would provide math scholarships to promising students along with guaranteed employment in either public or private enterprises.
Forget about “AI” itself: it’s all about the math, and America is failing to train enough citizens in the right kinds of mathematics to remain dominant.
THE WORLD first took notice of Beijing’s prowess in artificial intelligence (AI) in late 2017, when BBC reporter John Sudworth, hiding in a remote southwestern city, was located by China’s CCTV system in just seven minutes. At the time, it was a shocking demonstration of power. Today, companies like YITU Technology and Megvii, leaders in facial recognition technology, have compressed those seven minutes into mere seconds. What makes those companies so advanced, and what powers not only China’s surveillance state but also its broader economic development, is not simply its AI capability, but rather the math power underlying it.
A new study has explored whether AI can provide more attractive answers to humanity’s most profound questions than history’s most influential thinkers.
Researchers from the University of New South Wales first fed a series of moral questions to Salesforce’s CTRL system, a text generator trained on millions of documents and websites, including all of Wikipedia. They added its responses to a collection of reflections from the likes of Plato, Jesus Christ, and, err, Elon Musk.
The team then asked more than 1,000 people which musings they liked best — and whether they could identify the source of the quotes.
TuSimple, a trucking technology company, has announced a plan for the world’s first Autonomous Freight Network (AFN) – an ecosystem consisting of autonomous trucks, digital mapped routes, strategically placed terminals, and TuSimple Connect, a proprietary autonomous operations monitoring system.
Collectively, these components will work together to create the safest and most efficient way to bring self-driving trucks to market. Partnering with TuSimple in the launch of the Autonomous Freight Network are UPS, Penske Truck Leasing, U.S. Xpress (who operate one of the largest carrier fleets in the country) and McLane, a Berkshire Hathaway company and one of the largest supply chain services leaders in the United States.
“Our ultimate goal is to have a nationwide transportation network, consisting of mapped routes connecting hundreds of terminals to enable efficient, low-cost, long-haul autonomous freight operations,” said Cheng Lu, President of TuSimple. “By launching the AFN with our strategic partners, we will be able to quickly scale operations and expand autonomous shipping lanes to provide users access to autonomous capacity anywhere and 24/7 on-demand.”
Text is backward. Clocks run counterclockwise. Cars drive on the wrong side of the road. Right hands become left hands.
Intrigued by how reflection changes images in subtle and not-so-subtle ways, a team of Cornell researchers used artificial intelligence to investigate what sets originals apart from their reflections. Their algorithms learned to pick up on unexpected clues such as hair parts, gaze direction and, surprisingly, beards – findings with implications for training machine learning models and detecting faked images.
Researchers from the UK and Switzerland have found a mathematical means of helping regulators and business police Artificial Intelligence systems’ biases towards making unethical, and potentially very costly and damaging choices.
The collaborators from the University of Warwick, Imperial College London, and EPFL – Lausanne, along with the strategy firm Sciteb Ltd, believe that in an environment in which decisions are increasingly made without human intervention, there is a very strong incentive to know under what circumstances AI systems might adopt an unethical strategy—and to find and reduce that risk, or eliminate entirely, if possible.
Artificial intelligence (AI) is increasingly deployed in commercial situations. Consider for example using AI to set prices of insurance products to be sold to a particular customer. There are legitimate reasons for setting different prices for different people, but it may also be more profitable to make certain decisions that end up hurting the company.
Brain-inspired computing paradigms have led to substantial advances in the automation of visual and linguistic tasks by emulating the distributed information processing of biological systems. The similarity between artificial neural networks (ANNs) and biological systems has inspired ANN implementation in biomedical interfaces including prosthetics and brain-machine interfaces. While promising, these implementations rely on software to run ANN algorithms. Ultimately, it is desirable to build hardware ANNs that can both directly interface with living tissue and adapt based on biofeedback. The first essential step towards biologically integrated neuromorphic systems is to achieve synaptic conditioning based on biochemical signalling activity. Here, we directly couple an organic neuromorphic device with dopaminergic cells to constitute a biohybrid synapse with neurotransmitter-mediated synaptic plasticity. By mimicking the dopamine recycling machinery of the synaptic cleft, we demonstrate both long-term conditioning and recovery of the synaptic weight, paving the way towards combining artificial neuromorphic systems with biological neural networks.
FreeMove is a vision-based safety system. Source: Veo Robotics.
Vision systems have been employed in manufacturing for parts inspection, parts alignment, quality control, part identification, and part picking for many years. Now, new vision technology helps provide safety for industrial robots to work alongside humans.
Robotics standards outline four different methods of collaboration: safety-rated monitored stop, hand guiding, power and force limiting (PFL), and speed and separation monitoring (SSM). The most commonly understood form of collaborative robotics in manufacturing applications are PFL robots, often known as “collaborative robots” or “cobots.”
NASA’s newest spacecraft concept looks like it belongs in a steampunk convention more than a distant moon, but that’s exactly where it’s supposed to be headed.
Steam power sounds like a relic of the Victorian era only glamorized by steampunk culture, but NASA is developing SPARROW (Steam Propelled Autonomous Retrieval Robot for Ocaen Worlds), a new steam-powered robot concept that could potentially unearth life on moons like Enceladus or Europa. Sure, our space agency might be known for the most cutting-edge technology, but even that could face potential disaster on frozen moons whose surfaces could be perilous. This relatively simple contraption is capable of doing things more complex robots can’t.