AI & Robotics News and Discussions

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Yuli Ban
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Watch Robots Make Pizzas From Start to Finish at an Automated Pizzeria
The “show” starts with a robot grabbing a handful of dough and depositing it on a pan, where another bot flattens it, a third applies tomato sauce, etc. From dough-grabbing to inserting in the oven, preparing a pizza takes just 45 seconds. The oven can bake 6 pizzas at a time, yielding about 80 pizzas per hour. Once a pizza is baked to gooey perfection, a robot slices it and places it in a box, and it’s then transferred (by a robot, of course) to a numbered cubby from which the customer can retrieve it.

It’s a shame the pizzeria didn’t open during the height of the pandemic, as its revenues likely would have gone through the roof given that there’s zero person-to-person contact required for you to get a fresh, custom-made pizza in your hands (and more importantly, your belly!).

Pazzi’s creators spent eight years researching and developing the pizza bots, and they say the hardest part was getting the bots to work effectively with the raw dough. Since it’s made with yeast, the dough is sensitive to changes in temperature, humidity, and other factors, and for optimal results it needs to be rolled out and baked with very precise timing.
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Yuli Ban
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Amazon Patented a New Delivery System That Could Have Your Block Crawling With Robots
Amazon’s taking over the world. Or, at least, the US. Even as Jeff Bezos steps down as CEO and hands the reins over to former AWS head Andy Jassy (and Bezos himself gets ready to go to space), the e-commerce giant is projected to account for more than 40 percent of all online sales in the country by the end of this year.
Not surprisingly, the company is continuously exploring new ways to streamline its operations and cut costs. Last week a patent application that Amazon filed earlier this year became public. It’s for a delivery system that, if it comes to pass, would bring a new technology to neighborhoods where Amazon is popular (which, as implied above, is most of them).
What if, instead of the delivery people in Amazon uniforms you see frantically dashing from one home to the next, their trucks double-parked with the blinkers on, you saw this: an Amazon truck pulls up near your home and, most likely, still double-parks and puts the blinkers on (I mean, some things don’t change, and traffic congestion in cities isn’t going away anytime soon). But rather than the driver’s door opening and a person jumping out to start getting boxes where they need to be, the rear of the truck opens and a ramp is lowered to the pavement.
Down that ramp roll several smaller vehicles, maybe similar to the Kiwi delivery robots seen ferrying food to students in Berkeley a couple years ago. These small vehicles disperse, each one making its way to a different house or building within a one-to-two-block radius. They roll up to peoples’ doorsteps, deposit a package, then faithfully return to the mothership.
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Yuli Ban
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Advanced New Artificial Intelligence Software Can Compute Protein Structures in 10 Minutes
Accurate protein structure prediction now accessible to all.

Scientists have waited months for access to highly accurate protein structure prediction since DeepMind presented remarkable progress in this area at the 2020 Critical Assessment of Structure Prediction, or CASP14, conference. The wait is now over.

Researchers at the Institute for Protein Design at the University of Washington School of Medicine in Seattle have largely recreated the performance achieved by DeepMind on this important task. These results were published online by the journal Science on July 15, 2021.

Unlike DeepMind, the UW Medicine team’s method, which they dubbed RoseTTAFold, is freely available. Scientists from around the world are now using it to build protein models to accelerate their own research. Since July, the program has been downloaded from GitHub by over 140 independent research teams.

Proteins consist of strings of amino acids that fold up into intricate microscopic shapes. These unique shapes in turn give rise to nearly every chemical process inside living organisms. By better understanding protein shapes, scientists can speed up the development of new treatments for cancer, COVID-19, and thousands of other health disorders.
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Yuli Ban
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AI Is Learning To Understand How Vegetables Taste
With the global demand for food escalating, vertical farms are becoming a critical component of agriculture's future. They use robotics, machine learning and artificial intelligence (AI) to automate farming and perfect the growing of greens and vegetables. With steady growth, the vertical farming market was had an estimated value of $4.4 billion in 2019 and is expected to reach $15.7 billion by 2025.
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raklian
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To know is essentially the same as to not to know. The only thing that occurs is entropy.
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Yuli Ban
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AI Models to Help Photovoltaic Systems Find Their Place
With the looming threat of climate change, it is high time we embrace renewable energy sources on a larger scale. Photovoltaic systems, which generate electricity from the nearly limitless supply of sunlight energy, are one of the most promising ways of generating clean energy. However, integrating photovoltaic systems into existing power grids is not a straightforward process. Because the power output of photovoltaic systems depends heavily on environmental conditions, power plant and grid managers need estimations of how much power will be injected by photovoltaic systems so as to plan optimal generation and maintenance schedules, among other important operational aspects.

In line with modern trends, if something needs predicting, you can safely bet that artificial intelligence will make an appearance. To date, there are many algorithms that can estimate the power produced by photovoltaic systems several hours ahead by learning from previous data and analyzing current variables. One of them, called adaptive neuro-fuzzy inference system (ANFIS), has been widely applied for forecasting the performance of complex renewable energy systems. Since its inception, many researchers have combined ANFIS with a variety of machine learning algorithms to improve its performance even further.
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Yuli Ban
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Google parent Alphabet launches Intrinsic: a new company to build software for industrial robots
Google’s parent-company Alphabet has a birth to announce: a new company called Intrinsic which will focus on building software for industrial robots. The subsidiary will be one of Alphabet’s “other bets” — relatively speculative firms focusing on new technology like Waymo (self-driving cars), Wing (delivery drones), and Verily (healthcare and biotech).

Details on what exactly Intrinsic is building or who its customers will be are unclear. A blog post from the company’s new CEO, Wendy Tan White, discusses Intrinsic’s ambitions in broad terms, saying it will “unlock the creative and economic potential of industrial robotics for millions more businesses, entrepreneurs, and developers” by creating software that will make industrial robots “easier to use, less costly and more flexible.”

Robotics have been an obsession at Google for years, but the company’s efforts have been unfocused and have yet to produce any commercial hits.
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Yuli Ban
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weatheriscool
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Nimble robotic arms that perform delicate surgery may be one step closer to reality
https://techxplore.com/news/2021-07-nim ... rgery.html
by Peter Ramjug, Northeastern University

Researchers at Northeastern are working to eliminate the stiff, herky-jerky motions in robotic arms to make them graceful and deft enough to gently pick up an egg or sturdy enough to stack dinner plates. The findings could one day allow doctors to remotely perform surgery on a distant battlefield or help bomb disposal experts safely remove an explosive device.

A video demonstration of a university project involving a researcher wearing a C-shaped gripping claw attached to his right hand while a nearby robotic arm mimicked his exact movements showed the promise of hydraulic technology designed to be low friction.

The researcher in the video lowered and raised his arm, swept it left and right, and bent it at the wrist, smooth actions that were copied in tandem by the robotic arm. What was not readily apparent was how the human operator was
able to feel the same forces as the mechanical arm when it closed on an object, allowing the user to get a sense of textured surfaces.
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Yuli Ban
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Bipedal robot developed at Oregon State makes history by learning to run, completing 5K
Cassie the robot, invented at Oregon State University and produced by OSU spinout company Agility Robotics, has made history by traversing 5 kilometers, completing the route in just over 53 minutes.

Cassie was developed under the direction of robotics professor Jonathan Hurst with a 16-month, $1 million grant from the Advanced Research Projects Agency of the U.S. Department of Defense.

Since Cassie’s introduction in 2017, OSU students funded by the National Science Foundation have been exploring machine learning options for the robot.

Cassie, the first bipedal robot to use machine learning to control a running gait on outdoor terrain, completed the 5K on Oregon State’s campus untethered and on a single battery charge.
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