AI & Robotics News and Discussions

[wjfox]

[Yuli Ban]

Unitree’s Go1 Robot Dog Looks Pretty Great, Costs Just USD $2700, compared to $72K for Boston Dynamics’ Spot

In 2017, we first wrote about the Chinese startup Unitree Robotics, which had the goal of “making legged robots as popular and affordable as smartphones and drones.” Relative to the cost of other quadrupedal robots (like Boston Dynamics’ $74,000 Spot), Unitree’s quadrupeds are very affordable, with their A1 costing under $10,000 when it became available in 2020. This hasn’t quite reached the point of consumer electronics that Unitree is aiming for, but they’ve just gotten a lot closer: now available is the Unitree Go1, a totally decent looking small size quadruped that can be yours for an astonishingly low $2700.

[Yuli Ban]

Google says its artificial intelligence is faster and better than humans at laying out chips for artificial intelligence

Google claims not only has it made an AI that's faster and as good as if not better than humans at designing chips, the web giant is using it to design chips for faster and better AI.

By designing, we mean the drawing up of a chip's floorplan, which is the arrangement of its subsystems – such as its CPU and GPU cores, cache memory, RAM controllers, and so on – on its silicon die. The placement of the minute electronic circuits that make up these modules can affect the microchip's power consumption and processing speed: the wiring and signal routing needed to connect it all up matters a lot.

In a paper to be published this week in Nature, and seen by The Register ahead of publication, Googlers Azalia Mirhoseini and Anna Goldie, and their colleagues, describe a deep reinforcement-learning system that can create floorplans in under six hours whereas it can take human engineers and their automated tools months to come up with an optimal layout.

[Time_Traveller]

Training robots to manipulate soft and deformable objects

June 10, 2021



Robots can solve a Rubik's cube and navigate the rugged terrain of Mars, but they struggle with simple tasks like rolling out a piece of dough or handling a pair of chopsticks. Even with mountains of data, clear instructions, and extensive training, they have a difficult time with tasks easily picked up by a child.

A new simulation environment, PlasticineLab, is designed to make robot learning more intuitive. By building knowledge of the physical world into the simulator, the researchers hope to make it easier to train robots to manipulate real-world objects and materials that often bend and deform without returning to their original shape. Developed by researchers at MIT, the MIT-IBM Watson AI Lab, and University of California at San Diego, the simulator was launched at the International Conference on Learning Representations in May.

In PlasticineLab, the robot agent learns how to complete a range of given tasks by manipulating various soft objects in simulation. In RollingPin, the goal is to flatten a piece of dough by pressing on it or rolling over it with a pin; in Rope, to wind a rope around a pillar; and in Chopsticks, to pick up a rope and move it to a target location.

The researchers trained their agent to complete these and other tasks faster than agents trained under reinforcement-learning algorithms, they say, by embedding physical knowledge of the world into the simulator, which allowed them to leverage gradient descent-based optimization techniques to find the best solution.

"Programming a basic knowledge of physics into the simulator makes the learning process more efficient," says the study's lead author, Zhiao Huang, a former MIT-IBM Watson AI Lab intern who is now a Ph.D. student at the University of California at San Diego. "This gives the robot a more intuitive sense of the real world, which is full of living things and deformable objects."

https://techxplore.com/news/2021-06-rob ... mable.html

[Time_Traveller]

New processes for automated fabrication of fiber and silicone composite structures for soft robotics

June 9, 2021

Researchers from the Singapore University of Technology and Design (SUTD) have developed novel techniques, known as Automated Fiber Embedding (AFE), to produce complex fiber and silicone composite structures for soft robotics applications. Their work was published in IEEE Robotics and Automation Letters.

Many soft robot components, including sensors and actuators, utilize embedded continuous fibers within elastomeric substrates to achieve various functionalities. However, manual embedding of continuous fibers in soft substrates is challenging due to the complexities involved in handling precise layering, and retaining of the fibers in the patterned positions which are prone to inconsistencies.

In contrast, the AFE approaches developed by the research team led by Assistant Professor Pablo Valdivia y Alvarado, enabled high precision fabrication of complex layered composites without manual user intervention, thus significantly augmenting the range of fabrication possibilities while saving time and labor.

The techniques exploited seamless combinations of fiber embedding with elastomeric deposition via Direct Ink Writing in an automated manner and allowed precise control of depth and fiber spacing within composite structures. This process automation has great potential for the fabrication and tailoring of soft robot components which require complex geometries that cannot be easily achieved manually.

https://techxplore.com/news/2021-06-aut ... osite.html

[Time_Traveller]

A social robot that could help children to regulate their emotions

June 9, 2021



In recent years, roboticists have developed a broad variety of social robots, robots designed to communicate with humans, assist them and support them in several different ways. This includes robotic toys and other robots designed to be used by children.

Researchers at University of California- Santa Cruz (UCSC), King's College London, and a US-based company called Sproutel, and Committee for Children have recently developed a new socially assistive robot specifically designed to aid emotional regulation in children. This robot, presented in a paper pre-published on arXiv, resembles a small creature that a child might want to care for or cuddle.

"My research team at University of California Santa Cruz had been working on designing smart fidget devices and understanding use of fidget objects for a while and I met Petr Slovak (a key collaborator on the work in the paper) at a conference workshop," Katherine Isbister, one of the researchers who carried out the study, told TechXplore. "His interests were focused on social emotional learning and how to scaffold those skills."

Slovak, a lecturer and researcher at King's College London, thought that smart fidget devices could aid emotional learning and emotional regulation in children. He thus started collaborating with Isbister, as well as other students and researchers at UCSC, to develop a robot or device that could be used by children to regulate their emotions.

The robot developed by Isbister, Slovak and their colleagues looks a bit like a plush toy or stuffed animal. This 'robotic stuffed toy' responds to a child's touch, calming down and reducing its movements as a child gently caresses it or hugs it.

https://techxplore.com/news/2021-06-soc ... tions.html

[funkervogt]

Chip floorplanning is the engineering task of designing the physical layout of a computer chip. Despite five decades of research1, chip floorplanning has defied automation, requiring months of intense effort by physical design engineers to produce manufacturable layouts. Here we present a deep reinforcement learning approach to chip floorplanning. In under six hours, our method automatically generates chip floorplans that are superior or comparable to those produced by humans in all key metrics, including power consumption, performance and chip area.

https://www.nature.com/articles/s41586-021-03544-w.epdf

Reminds me of this:

[Yuli Ban]

U.S. Launches Task Force to Study Opening Government Data for AI Research

The Biden administration launched an initiative Thursday aiming to make more government data available to artificial intelligence researchers, part of a broader push to keep the U.S. on the cutting edge of the crucial new technology.

The National Artificial Intelligence Research Resource Task Force, a group of 12 members from academia, government, and industry led by officials from the White House Office of Science and Technology Policy and the National Science Foundation, will draft a strategy for creating an AI research resource that could, in part, give researchers secure access to stores of anonymous data about Americans, from demographics to health and driving habits.

They would also look to make available computing power to analyze the data, with the goal of allowing access to researchers across the country.

“This is a moment that is calling us to be strengthening our speed and scale” when it comes to advances in AI technology, said National Science Foundation Director Sethuraman Panchanathan in an interview. “It is also calling us to make sure that innovation is everywhere.”

Starspawn0's response to whether this would make a real difference:

Probably not much. What would have a HUGE economic impact would be if they poured $1 billion into constructing large robotics datasets -- say, hire teams of humans to remotely control a large number of robots in a large number of settings and tasks. We don't have that kind of data. If we had it, robotics would go through several quantum leaps in no time.

To be on the safe side (i.e. that they don't want the money to go to waste), they could do this in an incremental fashion -- say, begin by spending $50 million, and see how good the robots that result. Then, bump it up to another $100 million if the first round was successful. And if successful, again, keep bumping it up.

[weatheriscool]

Google Deploys AI to Build Better AI Hardware Accelerators
https://www.extremetech.com/extreme/323 ... celerators
By Joel Hruska on June 11, 2021 at 7:00 am

Google reports that it is now using AI to build its future Tensor Processing Units. The company has published some work in this area about a year ago, but today’s announcement indicates the technology has matured. Alexis Mirhoseini led the project.

The semiconductor industry has invested in various tools that automate parts of the design process for decades. Back when a CPU had 10,000 to 100,000 transistors, hand-drawn floor plans and circuit layouts were the only way to build a chip. Today, much of the design work is automated, though engineers may still be used in specific, critical paths.

Google is claiming it can adopt AI to help with floorplanning. The floorplan of a microprocessor — literally, its physical layout — has historically been a difficult task to automate. Even with the aid of modern software tools, laying out a new floorplan can take weeks. Over many decades, a great deal of work has gone into building software to better handle this complex problem, but humans are still integral to the process. Now, Google is claiming its new AI can do the job in a matter of hours.

[weatheriscool]

Study explores the potential of using a humanoid robot to entertain the elderly
https://techxplore.com/news/2021-06-exp ... derly.html
by Ingrid Fadelli , Tech Xplore

Humanoid robots have the potential of assisting humans in a variety of settings, ranging from home environments to malls, schools and healthcare facilities. Some roboticists have been specifically investigating the potential of social robots as tools to offer care and companionship to the elderly population.

Researchers at Nayang Technological University have recently carried out a study exploring the potential of a humanoid robot for entertaining residents of an elderly care home. Their paper, pre-published on arXiv, specifically examined the reactions of a group of elderly individuals as they played Bingo with a social robot called Nadine.

"The main goal of our paper was to investigate whether a robot with human appearance and gestures can support the elderly, particularly by entertaining them with games, such as Bingo," Nadia Magnenat Thalmann, one of the researchers who carried out the study, told TechXplore. "We wanted to find out whether these kinds of robots can help to decrease loneliness among the elderly, offering a presence and stimulus by playing games with them at any time of the day."