A new shortcut for quantum simulations could unlock new doors for technology

Two of the “maps” of quantum phase transitions generated by the technique. The different colors represent different phases or transitions between different phases.

By Louise Lerner

From water boiling into steam to ice cubes melting in a glass, we’ve all seen the phenomenon known as a phase transition in our everyday lives. But there’s another type of phase transition that’s much harder to see, but just as stark: quantum phase transitions.

When cooled to near absolute zero, certain materials can undergo these quantum phase transitions, which can make a physicist’s jaw drop. The material can flip from being magnetic to non-magnetic, or it can suddenly acquire the superpower to conduct electricity with zero energy lost as heat.

The mathematics behind these transitions is tough to handle even for supercomputers—but a new Physical Review A study from the University of Chicago suggests a new way to work with these complicated calculations, which could eventually yield technological breakthroughs. The shortcut pulls only the most important information into the equation, and creates a “map” of all possible phase transitions in the system being simulated.

“This is a potentially powerful way of looking at quantum phase transitions that can be used with either traditional or quantum computers,” said David Mazziotti, a theoretical chemist with the Department of Chemistry and the James Franck Institute at the University of Chicago and senior author of the study.

Continue reading… “A new shortcut for quantum simulations could unlock new doors for technology”

How AI is being used to improve 3D printing

By Adam Zewe

  • Scientists and engineers often manually use trial-and-error to find the optimum parameters to consistently 3D print new materials effectively.
  • But researchers have now streamlined the process by training a machine-learning model to monitor and adjust the 3D printing process to correct errors in real-time.
  • The system could help engineers easily incorporate novel materials into their prints and allow technicians to adjust the printing process if material or environmental conditions change unexpectedly.

Scientists and engineers are constantly developing new materials with unique properties that can be used for 3D printing, but figuring out howto print with these materials can be a complex, costly conundrum.

Often, an expert operator must use manual trial-and-error — possibly making thousands of prints — to determine ideal parameters that consistently print a new material effectively. These parameters include printing speed and how much material the printer deposits.

MIT researchers have now used artificial intelligence to streamline this procedure. They developed a machine-learning system that uses computer vision to watch the manufacturing process and then correct errors in how it handles the material in real-time.

Continue reading… “How AI is being used to improve 3D printing”

Should self-driving cars come with black box recorders?

Every commercial airplane carries a “black box” that preserves a second-by-second history of everything that happens in the aircraft’s systems as well as of the pilots’ actions, and those records have been priceless in figuring out the causes of crashes.

Why shouldn’t self-driving cars and robots have the same thing? It’s not a hypothetical question.

Federal transportation authorities are investigating a dozen crashes involving Tesla cars equipped with its “AutoPilot” system, which allows nearly hands-free driving. Eleven people died in those crashes, one of whom was hit by a Tesla while he was changing a tire on the side of a road. 

Yet, every car company is ramping up its automated driving technologies. For instance, even Walmart is partnering with Ford and Argo AI to test self-driving cars for home deliveries, and Lyft is teaming up with the same companies to test a fleet of robo-taxis.

But self-directing autonomous systems go well behind cars, trucks, and robot welders on factory floors. Japanese nursing homes use “care-bots” to deliver meals, monitor patients, and even provide companionship. Walmart and other stores use robots to mop floors. At least a half-dozen companies now sell robot lawnmowers.  (What could go wrong?)

Continue reading… “Should self-driving cars come with black box recorders?”

A radical vision for reinventing the suburbs

Nicknamed the Orbit, the plan would turn a rural suburb into a transit-oriented commuter city.

Outside Toronto, in a field surrounded by farmland, the seeds of a seemingly implausible high-density, transit-oriented community are taking root.

The community is the Orbit, a futuristic-sounding name for a new district on the edge of the town of Innisfil, Ontario, a commuter city about a half-hour drive north of Toronto. The plan for the Orbit is a grid of streets radiating around a dense central district, with proposed mid-rise towers, plentiful open spaces, and a mix of residential, commercial, and civic buildings. The center point of the plan is a commuter rail station that links Innisfil and other suburban communities to Toronto.

Continue reading… “A radical vision for reinventing the suburbs”

NASA Space Robotics Dive into Deep-Sea Work

What’s the difference between deep space and the deep sea? For a robot, the answer is: not much. Both environments are harsh and demanding, and, more importantly, both are far removed from the machine’s operator.

By Loura Hall

Nauticus Robotics’ Aquanaut robot can swim to a destination and carry out tasks with minimal supervision, saving money for offshore operations from oil wells and wind turbines to fish farms and more. Credits: Nauticus Robotics Inc.

What’s the difference between deep space and the deep sea? For a robot, the answer is: not much. Both environments are harsh and demanding, and, more importantly, both are far removed from the machine’s operator.

That’s why a team of roboticists from NASA’s Johnson Space Center in Houston decided to apply their expertise to designing a shape-changing submersible robot that will cut costs for maritime industries.

Continue reading… “NASA Space Robotics Dive into Deep-Sea Work”

Ottonomy.IO raises $3.3 million to expand network of autonomous robots for deliveries

By Jagmeet Singh

Ottonomy.IO, a startup working on solving delivery problems using autonomous robots, has raised $3.3 million in a seed funding round as it looks to expand its market and deploy robots to existing customers.

Led by Bengaluru-based Pi Ventures, the latest funding round included participation from Connetic Ventures and Branded Hospitality Ventures. Sangeet Kumar, founder and chief executive of Uttar Pradesh-based Addverb Technologies, also joined the round.

Founded in late 2020 by Ritukar Vijay along with Pradyot Korupolu, Ashish Gupta and Hardik Sharma, New York-headquartered Ottonomy.IO develops robots that feature sensors, including 3D lidar sensors and cameras. The company, which employs about 25 people in the U.S. and India, also writes software and AI algorithms to power the sensors.https://jac.yahoosandbox.com/1.2.0/safeframe.html

“One of the most important problems which we are trying to solve with these autonomous delivery robots is around labor shortages,” said Vijay, who serves as the chief executive of Ottonomy.IO, in an interaction with TechCrunch. He added that due to the labor shortages, there is a substantial increase in the hourly wages of laborers — to $18 to $45 per hour from $9 to $12 — in the U.S.

“So, that’s almost a 100% hike in hourly wages, making it very difficult for enterprise customers to provide the same services to the customers they were given earlier. And what happens at the end is that customers start paying more for deliveries.”

Continue reading… “Ottonomy.IO raises $3.3 million to expand network of autonomous robots for deliveries”

Robots from DNA? Researchers Developed a New Machine for Membrane Proteins

By Isaiah Richard

Researchers achieved a new development in their studies in this new publication focusing on nano-sized robots that came from a DNA’s design, now concentrate on doing wonders for biological advancements. The innovation will help bodily functions to improve and give the world more information regarding the diseases that occur in the body. 

According to SciTechDaily, researchers from Inserm, CNRS, and the University of Montpellier focused on developing new nanobots that came from a DNA for studying bodily functions and processes. The research took place at the Structural Biology Center in Montpellier, and its paper is now published in Nature Communication. 

The research entitled “A Modular Spring-Loaded Actuator for Mechanical Activation of Membrane Proteins” focus on conducting biological processes with these mechanical objects inside the body.

It may sound like it came from a science fiction show or content, but it is already a reality from the researchers that devised a way patterned from DNA. 

Continue reading… “Robots from DNA? Researchers Developed a New Machine for Membrane Proteins”

Google’s DeepMind AI Predicts 3D Structure of Nearly Every Protein Known to Science

This ribbon diagram shows the 3D protein structure of an antibody. Complex? It’s pretty simple for an AI.

By Monisha Ravisetti

At last, the decades-old protein folding problem may finally be put to rest.

It wasn’t until 1957 when scientists earned special access to the molecular third dimension. 

After 22 years of grueling experimentation, John Kendrew of Cambridge University finally uncovered the 3D structure of a protein. It was a twisted blueprint of myoglobin, the stringy chain of 154 amino acids that helps infuse our muscles with oxygen. As revolutionary as this discovery was, Kendrew didn’t quite open up the protein architecture floodgates. During the next decade, fewer than a dozen more would be identified. 

Fast-forward to today, 65 years since that Nobel Prize-winning breakthrough. 

On Thursday, Google’s sister company, DeepMind, announced it has successfully used artificial intelligence to predict the 3D structures of nearly every catalogued protein known to science. That’s over 200 million proteins found in plants, bacteria, animals, humans — almost anything you can imagine.

“Essentially, you can think of it as covering the entire protein universe,” Demis Hassabis, founder and CEO of DeepMind, told reporters this week.

It’s thanks to AlphaFold, DeepMind’s groundbreaking AI system, which has an open-source database so scientists worldwide can involve it in their research at will, and for free. Since AlphaFold’s official launch in July of last year — when it had only pinpointed some 350,000 3D proteins — the program has made a noticeable dent in the landscape of research. 

Continue reading… “Google’s DeepMind AI Predicts 3D Structure of Nearly Every Protein Known to Science”

Tesla big battery begins providing inertia grid services at scale in world first in Australia

The Hornsdale Power Reserve is located approximately 16 km north of Jamestown in South Australia.

By  BELLA PEACOCK

South Australia’s 150 MW / 193.5 Hornsdale Power Reserve, more commonly known as the Tesla Big Battery, will now provide inertia services to Australia’s National Electricity Market after securing approval from the Australian Energy Market Operator. Neoen says it is the first big battery in the world to deliver the service at such a scale.

After two years of extensive trials, Neoen’s Hornsdale Power Reserve now has the capacity to provide an estimated 2,000 megawatt seconds (MWs) of equivalent inertia to South Australia’s grid through Tesla’s Virtual Machine Mode technology.

Known as virtual synchronous machines or grid forming inverters, this technology gives batteries the capacity to help stabilize the grid by providing inertia. Along with frequency control services, inertia is necessary for operating a stable grid and is especially important after major disturbances. Until now, inertia services have only been provided by gas or coal-fired generators and their rapid retirement is causing inertia shortfalls or grid instability – especially in regions like South Australia, where renewable penetration has reached 64% over the last 12 months.

The Hornsdale Power Reserve will now be capable of providing around 15% of the state’s predicted inertia shortfall – a globally significant milestone. The use of the technology at Hornsdale has been approved by the Australian Energy Market Operator (AEMO), which has been working closely with Neoen, Tesla and ElectraNet, South Australia’s network operator, to trial the Virtual Machine Mode at Hornsdale following its expansion in 2020. 

The companies now completed all the necessary studies, testing and analysis to deploy the technology at scale, with that capacity available from today. “We are proving that our assets can replace fossil fuels not only in the production and storage of electricity, but also through providing all the essential services that a power system needs to function,” Neoen’s Chairman and CEO Xavier Barbaro said. “We are keen to build on this progress, continuing to innovate and to accelerate the transition to renewables in Australia and around the world.”

Continue reading… “Tesla big battery begins providing inertia grid services at scale in world first in Australia”