Materials


Scientists develop Terminator-style stretchable liquid metal

Daily Mail

A new host of liquid metals that have applications towards soft robotics are making movies like'The Terminator' transcend make-believe. According to researchers, experimental liquid metals like gallium and other alloys, when supplemented with nickel or iron, are able to flex and mold into shapes with the use of magnets, much like the iconic movie villain, T-1000 from'The Terminator 2: Judgement Day.' While other such metals have been developed, they contended with two major drawbacks. A new host of liquid metals that have applications towards soft robotics are making movies like'The Terminator' transcend make-believe toward real life. Researchers say experimental liquid metals like gallium and other alloys, when supplemented with nickel or iron, are able to flex and mold into shapes with the use of magnets. A new material revealed by the American Chemical Society solves to major problems experienced by similar substances.


The Amazing Ways John Deere Uses AI And Machine Vision To Help Feed 10 Billion People

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In just 30 years' time, it is forecasted that the human population of our planet will be close to 10 billion. Producing enough food to feed these hungry mouths will be a challenge, and demographic trends such as urbanization, particularly in developing countries, will only add to that. To meet that challenge, agricultural businesses are pinning their hopes on technology, and that idea that increasingly sophisticated data and analytics tools will help to drive efficiencies and cut waste in agriculture and food production. Leading the way is John Deere – the 180-year-old manufacturer of farming and industrial machinery which has spent the past decade transforming itself into an artificial intelligence (AI) and data-driven business. I have covered John Deere before here.


Exercises in amazement: Discovering deep learning

MIT News

It was standing-room only in the Stata Center's Kirsch Auditorium when some 300 attendees showed up for opening lectures for MIT's intensive, student-designed course 6.S191 (Introduction to Deep Learning). Nathan Rebello, a first-year graduate student in chemical engineering, was among those who were excited about the class, coordinated by Alexander Amini '17 and Ava Soleimany '16 during MIT's Independent Activities Period (IAP) in January. "I hope to go into either industry or academia and to apply deep learning techniques for the design of new materials," Rebello says. He signed up for 6.S191 to learn more about deep learning with the intention of applying it to the design of bio-inspired polymeric materials, adding: "I also wanted to network with students and faculty to explore their ways of thinking on this topic." There were plenty of people available for networking.


This Robot Built a House in 3 Days

#artificialintelligence

HADRIAN X, a robot developed by Australian company FBR (formerly known as Fastbrick Robotics), has successfully completed its first full-scale test by building a 180 square metre house with three bedrooms and two bathrooms. Initially, Hadrian X was made to pass Factory Acceptance Testing (FAT), which focused on its ability to work with bricks of different sizes and cuts, building from a CAD model and building tall or "from slab to cap". Above: Hadrian X laying blocks to complete Factory Acceptance Testing (image courtesy of FBR). After completing the trial, Hadrian X completed its first full home structure in less than three days. The structure was verified by independent civil and structural engineers as having met the relevant building standards.


Deveron Receives AI for Earth Grant from Microsoft

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Toronto, Ontario--(Newsfile Corp. - March 11, 2019) - Deveron UAS Corp. ("Deveron" or the "Company") and Deveron's wholly owned data analytics subsidiary, Veritas Farm Management ()Veritas") have been awarded an AI for Earth grant from Microsoft to help further our efforts in artificial intelligence ()AI") and making recommendations and predictions using agricultural data. This new grant will provide Deveron with Microsoft Azure computing resources and AI tools to accelerate our work on utilizing in-season imagery and AI to apply nitrogen fertilizer to corn. Deveron will help growers more fully utilize the nitrogen credit produced when cover crops are introduced into crop rotation. Additional nitrogen can then be applied as needed using variable rate applications around these credits, insuring that the nitrogen needs of the crop is met in an efficient way across the field. "We are excited to be chosen by Microsoft to participate in this transformational opportunity" reported David Macmillan, President and CEO of Deveron.


This Cardboard Box Can Tell You What It Sees

#artificialintelligence

It wasn't that long ago that talking to computers was the preserve of movies and science fiction. Slowly, voice recognition improved, and these days it's getting to be pretty usable. The technology has moved beyond basic keywords, and can now parse sentences in natural language. The device is built around Google's AIY Voice Kit, which consists of a Raspberry Pi with some additional hardware and software to enable it to process voice queries. This allows WhatIsThat to respond to users asking questions by taking a photo, and then identifying what it sees in the frame.


Your Health Data Are a Gold Mine for Advertisers

The Atlantic

Hospitals across the nation are piloting voice-enabled smart speakers in patients' rooms, including Cedars-Sinai Medical Center in Los Angeles and Boston Children's Hospital. These institutions are hoping that smart speakers will make patients more comfortable, help staff stay organized, and, in some cases, keep people out of hospitals and emergency rooms altogether. Early results are promising, but health-care providers are still figuring how to protect privacy once smart speakers know our intimate medical details. Searching online for medical help, even for common ailments, already reveals much more than people realize. That data has proved valuable both to health officials and to big businesses.


Modeling muscle

Science

Adaptive behaviors ranging from self-assembly to self-healing showcase the ability of such systems to sense and adapt to dynamic environments based on signaling between living cells. This signaling takes on many forms--biochemical, mechanical, and electrical--and uncovering it has become as much the purview of regenerative medicine as of fundamental biology. We cannot reverse-engineer native tissues if we do not understand the fundamental design rules and principles that govern their assembly from the bottom up (1). Movement is fundamental to many living systems and driven primarily by skeletal muscle in human bodies. Disease or damage that limits the functionality of skeletal muscle severely affects human health, mobility, and quality of life.


Andreessen and Gates invest in an AI startup that's looking for ethical cobalt

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There's a good chance your smartphone contains tainted cobalt. The metal is a crucial ingredient in most of the lithium-ion batteries that power our devices, and 70% of it is mined in war-torn Democratic Republic of Congo (DRC), where children are often deployed to work in toxic environments. Though global brands like Apple and Samsung are keen to clean up their supply chain, DRC's dominance of the cobalt market makes the task difficult. These brands are also pressured by growing demand for cobalt, which Citigroup estimates will outstrip supply by 2023. That's because lithium-ion batteries also power electric cars, and every car battery needs as much as 1,000 times the amount of cobalt of a smartphone battery.


Synthesizing Chemical Plant Operation Procedures using Knowledge, Dynamic Simulation and Deep Reinforcement Learning

arXiv.org Artificial Intelligence

Chemical plants are complex and dynamical systems consisting of many components for manipulation and sensing, whose state transitions depend on various factors such as time, disturbance, and operation procedures. For the purpose of supporting human operators of chemical plants, we are developing an AI system that can semi-automatically synthesize operation procedures for efficient and stable operation. Our system can provide not only appropriate operation procedures but also reasons why the procedures are considered to be valid. This is achieved by integrating automated reasoning and deep reinforcement learning technologies with a chemical plant simulator and external knowledge. Our preliminary experimental results demonstrate that it can synthesize a procedure that achieves a much faster recovery from a malfunction compared to standard PID control.