Thursday, April 19, 2018

Friday Thinking 20 April 2018

Hello all – Friday Thinking is a humble curation of my foraging in the digital environment. My purpose is to pick interesting pieces, based on my own curiosity (and the curiosity of the many interesting people I follow), about developments in some key domains (work, organization, social-economy, intelligence, domestication of DNA, energy, etc.)  that suggest we are in the midst of a change in the conditions of change - a phase-transition. That tomorrow will be radically unlike yesterday.

Many thanks to those who enjoy this.
In the 21st Century curiosity will SKILL the cat.
Jobs are dying - work is just beginning.

“Be careful what you ‘insta-google-tweet-face’”
Woody Harrelson - Triple 9



There exists a holographic duality in nature that may likely also translate to the workings of Deep Learning networks. The greater the generalization of a network, the more entangled its neurons and as a consequence the network becomes less interpretable. The uncertainty principle as applied to Deep Learning can be stated as:
Networks with greater generalization are less interpretable. Networks that are interpretable don’t generalize well.

Which led me to my conjecture in 2016 that “The only way to make Deep Learning interpretable is to have it explain itself.” If you think about it from the perspective of holographic duality, then it is futile to look at the internal weights of a neural network to understand its behavior. Rather, we best examine its surface to find a simpler (and less turbulent) explanation.

This leads me to the inevitable reality that the best we can do is to have machines render very intuitive ‘fake explanations’. Fake explanations are not false explanations, but rather incomplete explanations with a goal toward eliciting an intuitive understanding. This is what good teachers do, this is what Richard Feynman did when he explained quantum mechanics to his students.

Deep Learning’s Uncertainty Principle

“what if websites borrowed compute resources from their visitor’s devices while they browsed as a means of distributed computing?”

Because of the way the web was designed, visiting a website requires your web browser to download and run code served from that website on your device. When you browse Facebook, their JavaScript code runs in your web browser on your machine. The code that gets executed in your browser is, of course, assumed to be code related to the functionality of the site you are browsing. Netflix serves code that allows your browser to access their movie database and stream video content, Twitter serves codes that allows you to post, view, and comment on tweets, etc…

Technically, however, there is nothing stopping a website from serving arbitrary code that has nothing to do with your browsing experience. Your web browser will blindly execute whatever JavaScript code it receives from the website you are browsing. What’s to stop high-traffic sites like Facebook and Google from abusing this feature of the web, harvesting massive compute resources from their hundreds of thousands of concurrently connected users for free? Was this idea really feasible in practice? If so, was it being used in the wild?

Browser as Botnet, or the Coming War on Your Web Browser

Unlike traditional antibiotics, phages are both a self-sustaining and self-limiting treatment
This is what Chan and Turner have been trying to do for the past five years. Their strategy is to find phages that can do more than simply kill offending bacteria, the way antibiotics do; they want phages that can push the right evolutionary buttons, rendering the patient’s bacteria more vulnerable to antibiotics, less virulent, or even harmless. Chan and Turner call this wizardry ‘evolutionary engineering’.

Phages exploit what are known as receptors: a bit of protein or other biomolecule protruding from the bacterial cell’s surface. When a phage enters the bloodstream or slips into a layer of mucus, it tumbles about until it bumps into a strain of bacteria that possesses a receptor that matches its own particular needs, even if the bug is sheltering within a biofilm: unlike many antibiotics, phages can penetrate the sticky protective layer. Upon gaining access, the virus then hijacks the bacterial cell to make copies of itself, and these new phages go about infecting more bacterial cells, until there are no more left to infect. This makes phages, unlike traditional antibiotics, both a self-sustaining and self-limiting treatment.

Viral rescue

It only took five minutes for Gavin Schmidt to out-speculate me.

Schmidt is the director of nasa’s Goddard Institute for Space Studies (a.k.a. GISS) a world-class climate-science facility. One day last year, I came to GISS with a far-out proposal. In my work as an astrophysicist, I’d begun researching global warming from an “astrobiological perspective.” That meant asking whether any industrial civilization that rises on any planet will, through their own activity, trigger their own version of a climate shift. I was visiting GISS that day hoping to gain some climate science insights and, perhaps, collaborators. That’s how I ended up in Gavin’s office.

Just as I was revving up my pitch, Gavin stopped me in my tracks.

“Wait a second,” he said. “How do you know we’re the only time there’s been a civilization on our own planet?”

Was There a Civilization On Earth Before Humans?

This is a must read short blog post - that summarizes and links to some very important ideas about the potential role of the emerging social media platforms.

Information Fiduciaries

On Sunday morning I was reading the Times opinion section and ran into an idea that felt new. Here it is from Jonathan Zittrain’s op-ed “Mark Zuckerberg Can Still Fix This Mess”:

On the policy front, we should look to how the law treats professionals with specialized skills who get to know clients’ troubles and secrets intimately. For example, doctors and lawyers draw lots of sensitive information from, and wield a lot of power over, their patients and clients. There’s not only an ethical trust relationship there but also a legal one: that of a “fiduciary,” which at its core means that the professionals are obliged to place their clients’ interests ahead of their own.

The legal scholar Jack Balkin has convincingly argued that companies like Facebook and Twitter are in a similar relationship of knowledge about, and power over, their users — and thus should be considered “information fiduciaries.”

Information fiduciary is one of the first things I’ve read in all the morass of Facebook think-pieces that felt both new and useful. The basic idea is that Facebook (and other similar platforms) have a special relationship with users that resembles the kind of fiduciary responsibilities doctors and lawyers have with our data (critically, Balkin makes a distinction between the responsibility for data and advice, the latter of which Facebook obviously doesn’t have).

In his much longer and surprisingly readable paper on the idea he lays out an argument for why we should take the concept seriously. The paper starts by replaying a question Zittrain posed in 2014 New Statesman article after Facebook ran a get out the vote experiment that drove impressive numbers:

This is a strong signal related to the emerging orientation toward the inevitable developments of AI.

UK Government Proposes Five Basic Principles to Keep Humans Safe From AI

A new report by the Lords Select Committee in the UK claims that Britain is in a strong position to be a world leader in the development of artificial intelligence. But to get there—and to keep AI safe and ethical—tech firms should follow the Committee’s newly proposed “AI Code.”

The new report was penned by the House of Lords Artificial Intelligence Committee, and it’s titled “AI in the UK: Ready, Willing and Able?.” The AI Committee is proposing a path for both the British government and UK-based businesses to move forward as AI increasingly expands in power and scope. The report is particularly timely given the recent scandal surrounding Cambridge Analytica’s use of Facebook data and growing concerns that tech companies aren’t working in the public’s best interests. In recognition of both current and future risks, the Committee says technology, and AI in particular, needs to be used for the common good.

The 181-page report is wide ranging in its recommendations, but the Committee suggests five overarching principles for a basic AI code:
-  Artificial intelligence should be developed for the common good and benefit of humanity.
-  Artificial intelligence should operate on principles of intelligibility and fairness.
-  Artificial intelligence should not be used to diminish the data rights or privacy of individuals, families or communities.
-  All citizens have the right to be educated to enable them to flourish mentally, emotionally and economically alongside artificial intelligence.
-  The autonomous power to hurt, destroy or deceive human beings should never be vested in artificial intelligence.

The Committee also recognizes that existing legislation may be inadequate or ill-prepared to deal with situations in which AI systems malfunction, underperform, or make erroneous decisions which cause harm.

This is a very important signal about the need to consider increasing research funding for medical and health advances to universities - because ‘cures’ aren’t as profitable as ‘treatments’ - and research into the non-patentable benefits of nutrition and plant based medicines are not profitable either.

When curing a disease with gene therapy is bad business

A drug giant turns over its pipeline of miracle drugs to a startup.
An analyst at Goldman Sachs asked a troubling question this week about gene therapy.
“Is curing patients a sustainable business model?”
In social media, reactions were quick and sharp. “Cold and immoral.” “Capitalism at its finest.”
But the Goldman analyst has a point. It’s tricky to make a sustained profit from one-shot cures.

For at least one big drug maker, the answer to Goldman’s question is no.
Just today, we saw GlaxoSmithKline sell off its pipeline of gene therapies for rare disease to a London startup called Orchard Therapeutics for a 20 percent stake in the young company.

The treatments Glaxo didn’t want were bona fide miracles: one-and-done cures that replace a broken gene and save a life.

This is a great signal about the need not just to renew our infrastructure but to re-imagine what it can provide before we simply renew what’s already in place.

China’s Built a Road So Smart It Will Be Able to Charge Your Car

The road of the future is likely to become the brain and nerve center of an autonomous-driving revolution.
The road to China’s autonomous-driving future is paved with solar panels, mapping sensors and electric-battery rechargers as the nation tests an “intelligent highway” that could speed the transformation of the global transportation industry.

The technologies will be embedded underneath transparent concrete used to build a 1,080-meter-long (3,540-foot-long) stretch of road in the eastern city of Jinan. About 45,000 vehicles barrel over the section every day, and the solar panels inside generate enough electricity to power highway lights and 800 homes, according to builder Qilu Transportation Development Group Co.

And another good signal of the trajectory of the digital environment.
The work Pan and other scientists are doing now is part of what some call “the second quantum revolution”. The first quantum revolution began in the early decades of the 20th century with the discovery of the bizarre laws of the subatomic realm – in which an object can be both a wave and a particle – by pioneering scientists like Heisenberg, Schr√∂dinger and Einstein. Applied to technology, these ideas ushered in the era of modern electronics with devices such as the transistor, the laser and the solar cell.

In the second quantum revolution, scientists are applying the quantum rules to the basic ideas of information technology.

The quantum internet is already being built

A quantum internet could revolutionise communication, computing and basic science, and it may be only 10 years away. But what is it?
For a few minutes each night in certain parts of China, the brightest light in the sky is the lurid glow of the Micius satellite, shooting a green laser down to Earth as it swings through space 500 kilometres above. When conditions are right, you might also see a red beam lancing back through the darkness from one of the ground stations that send signals in reply.

Micius is not your average telecommunications satellite. On 29 September 2017, it made history by accomplishing an astonishing feat, harnessing the mysterious qualities of quantum entanglement – what Einstein called ‘spooky action at a distance’ – to ‘teleport’ information into space and back again. In doing so, it enabled the first intercontinental phone call – a video call, in fact, between Beijing and Vienna – that was completely unhackable.

The weird science of quantum physics that powers Micius is at the heart of a technology arms race. On one side are quantum computers, still in their infancy but with enormous potential once they grow in power. Among their most prized, and feared, applications is the capacity to cut through the complex mathematical locks that now secure computer encryption systems – the ones that mean you can confidently conduct financial transactions over the internet. On the other side is the only sure defence – encryption techniques that also rely on the laws of quantum physics.

This is a great signal of the emerging power of blockchain technologies as the 21st century institution of records.
Started in early 2017, Building Blocks, as the program is known, helps the WFP distribute cash-for-food aid to over 100,000 Syrian refugees in Jordan. By the end of this year, the program will cover all 500,000 refugees in the country. If the project succeeds, it could eventually speed the adoption of blockchain technologies at sister UN agencies and beyond.
Blockchain systems are also more secure than conventional identity records because they cut out third-party intermediaries. They can be easier to use, and they can survive disasters that might wipe out more centralized record-keeping systems.

Inside the Jordan refugee camp that runs on blockchain

Syrian refugees could regain legal identities that were lost when they fled their homes.
A few times a month, Bassam pushes a shopping cart through the aisles of a grocery store stocked with bags of rice, a small selection of fresh vegetables, and other staples. Today he’s wearing a black sweater tucked into denim jeans, which are themselves tucked into calf-high boots caked in mud. The Tazweed Supermarket, where he’s shopping, is on the periphery of a 75,000-person refugee camp in the semi-arid Jordanian steppe, six and a half miles from the Syrian border.

At the checkout counter, a cashier tallies the total, but Bassam doesn’t pay with cash or a credit card. Instead he lifts his head to a black box and gazes into the mirror and camera at its center. A moment later, an image of Bassam’s eye flashes on the cashier’s screen. Bassam collects his receipt—which reads “EyePay” and “World Food Programme Building Blocks” across the top—and walks out into the noonday chaos of the Zaatari refugee camp.

Though Bassam may not know it, his visit to the supermarket involves one of the first uses of blockchain for humanitarian aid. By letting a machine scan his iris, he confirmed his identity on a traditional United Nations database, queried a family account kept on a variant of the Ethereum blockchain by the World Food Programme (WFP), and settled his bill without opening his wallet.

I’m not convinced that this is the best way to enable the accounting of creative value and use of creations - ultimately though blockchain could both disrupt current Intellectual Property approaches by creating secure accounting of use and also unleash the capacity to share and combine creations for better innovation and adoption.

Search Giant Baidu Unveils Blockchain Photo Platform

Chinese internet search giant Baidu has launched a blockchain-based stock photo service in bid to protect image intellectual property in China.
The service, called Totem, went online Wednesday and uses a blockchain to timestamp submissions of each original photograph from a user with a real-name identity and store data associated with the images on a distributed network.

With Baidu's existing capacity in internet data scraping and artificial intelligence, the platform says that, by comparing images that are circulated over the internet with data stored in a traceable blockchain, it would be able to substantiate allegations of intellectual property infringement.

Currently, according to the new site, several traditional stock photo services have also moved onto the platform, including notable services such as Visual China Group, a local partner of the stock photo giant Getty Images.

This is an interesting approach to using AI to do research on text. There is a link to the original paper (but there’s a paywall).

Artificial intelligence reveals how U.S. stereotypes about women and minorities have changed in the past 100 years

How do you measure the stereotypes of the past after the past is gone? You could read what people wrote and tally up the slurs, but bias is often subtler than a single word. Researchers are now developing artificial intelligence (AI) to help out. A new study has analyzed which stereotypes are still holding fast—and which are going the way of the floppy disk.

To quantify bias, one team turned to a type of AI known as machine learning, which allows computers to analyze large quantities of data and find patterns automatically. They designed their program to use word embeddings, strings of numbers that represent a word’s meaning based on its appearance next to other words in large bodies of text. If people tend to describe women as emotional, for example, “emotional” will appear alongside “woman” more frequently than “man,” and word embeddings will pick that up: The embedding for “emotional” will be closer numerically to that for “woman” than “man.” It will have a female bias.

The researchers first wanted to see whether embeddings were a good measure of stereotypes. Looking at published English text from various decades, they found that their program’s embeddings clearly lined up with the results of surveys on gender and ethnic stereotypes from the same times. Then they analyzed sentiments that had not been surveyed, using 200 million words taken from U.S. newspapers, books, and magazines from the 1910s to the 1990s.

Going decade by decade, they found that words related to competence—such as “resourceful” and “clever”—were slowly becoming less masculine. But words related to physical appearance—such as “alluring” and ”homely”—were stuck in time. Over the decades, their embeddings were still distinctly “female.” Other findings focused on race and religion: Asian names became less tightly linked to terms for outsiders (including “devious”) and in a separate data set—gathered from The New York Times from 1988 to 2005—words related to terrorism became more closely associated with words related to Islam after the 1993 and 2001 attacks on the World Trade Center in New York City. People from other times and places might not be able to tell you their biases, but they can’t hide them either. The work appears in the Proceedings of the National Academy of Sciences.

And another emerging AI accelerator in scientific and materials research and production.
“What we have seen here is that this kind of artificial intelligence can capture this expert knowledge,” says Pablo Carbonell, who designs synthesis-predicting tools at the University of Manchester, UK, and was not involved in the work. He describes the effort as “a landmark paper”.

Need to make a molecule? Ask this AI for instructions

Artificial-intelligence tool that has digested nearly every reaction ever performed could transform chemistry.
Chemists have a new lab assistant: artificial intelligence. Researchers have developed a ‘deep learning’ computer program that produces blueprints for the sequences of reactions needed to create small organic molecules, such as drug compounds. The pathways that the tool suggests look just as good on paper as those devised by human chemists.

The tool, described in Nature on 28 March, is not the first software to wield artificial intelligence (AI) instead of human skill and intuition. Yet chemists hail the development as a milestone, saying that it could speed up the process of drug discovery and make organic chemistry more efficient.

The new AI tool, developed by Marwin Segler, an organic chemist and artificial-intelligence researcher at the University of M√ľnster in Germany, and his colleagues, uses deep-learning neural networks to imbibe essentially all known single-step organic-chemistry reactions — about 12.4 million of them. This enables it to predict the chemical reactions that can be used in any single step. The tool repeatedly applies these neural networks in planning a multi-step synthesis, deconstructing the desired molecule until it ends up with the available starting reagents.

From molecules, to material, to new metabolisms for production of new materials - AI is emerging as an accelerator of scientific discovery.
"It typically takes a decade or two to get a material from discovery to commercial use," said Northwestern Professor Chris Wolverton, an early pioneer in using computation and AI to predict new materials and a co-author of the paper. "This is a big step in trying to squeeze that time down. You could start out with nothing more than a list of properties you want in a material and, using AI, quickly narrow the huge field of potential materials to a few good candidates."

Over the past half century, scientists have investigated about 6,000 combinations of ingredients that form metallic glass, added paper co-author Apurva Mehta, a staff scientist at SSRL: "We were able to make and screen 20,000 in a single year."

Artificial intelligence accelerates discovery of metallic glass

Blend two or three metals together and you get an alloy that usually looks and acts like a metal, with its atoms arranged in rigid geometric patterns.

But once in a while, under just the right conditions, you get something entirely new: a futuristic alloy called metallic glass that's amorphous, with its atoms arranged every which way, much like the atoms of the glass in a window. Its glassy nature makes it stronger and lighter than today's best steel, plus it stands up better to corrosion and wear.
Even though metallic glass shows a lot of promise as a protective coating and alternative to steel, only a few thousand of the millions of possible combinations of ingredients have been evaluated over the past 50 years, and only a handful developed to the point that they may become useful.

Now a group led by scientists at the Department of Energy's SLAC National Accelerator Laboratory, the National Institute of Standards and Technology (NIST) and Northwestern University has reported a shortcut for discovering and improving metallic glass—and, by extension, other elusive materials—at a fraction of the time and cost.

The research group took advantage of a system at SLAC's Stanford Synchrotron Radiation Lightsource (SSRL) that combines machine learning—a form of artificial intelligence where computer algorithms glean knowledge from enormous amounts of data—with experiments that quickly make and screen hundreds of sample materials at a time. This allowed the team to discover three new blends of ingredients that form metallic glass, and to do this 200 times faster than it could be done before, they reported today in Science Advances.

This is a good signal to new ways to help keep certain environments clean and reduce the prevalence of harmful bacteria - that said we have a long way to go before we fully understand our microbial ecologies and how best to nurture them.
In lab tests, the material killed 99.97 percent of MRSA, the strain of Staphylococcus aureus that is resistant to methicillin and other antibiotics, and 99.85 percent of a multidrug-resistant strain of E. coli. For both experiments, the researchers used much higher concentrations of microbes than those typically found on hospital surfaces,

This material uses energy from ambient light to kill hospital superbugs

In lab tests, the quantum dot polymer nearly eliminated two drug-resistant strains of bacteria
About 1 in 10 patients worldwide get an infection while receiving treatment at a hospital or other health care facility, according to the World Health Organization. “Contaminated hospital surfaces play a key role in spreading those infections,” said Ethel Koranteng, a chemist at University College London on April 5 at the Materials Research Society spring meeting.

Koranteng and colleagues developed a material to make hospital surfaces self-disinfecting. Naturally antimicrobial metals such as copper and steel are difficult to sculpt around uneven surfaces. But the new polymer-based material could be fashioned into a flexible film that covers computer keyboards, or molded into rigid, plasticlike casings that enclose phone handles, bedrails and other surfaces especially prone to contamination.

The covering is made of polyurethane embedded with tiny semiconductor nanoparticles called quantum dots and particles of a purple dye called crystal violet. When the quantum dots absorb ambient light, they transfer some of that energy to nearby dye particles, causing the crystal violet to release a kind of high-energy oxygen molecule that kills microbes.

Another signal of the advance in domesticating DNA - this time through deeper access to proteomics (proteins). This signal builds on the 2017 Nobel.
"The last 50 years of structural biology has been about trying to get detailed pictures of all the parts of the cell to understand them thoroughly," Yeates said. "A picture is worth 1,000 words, and very often, getting a first three-dimensional view of a component of the cell gives you valuable insight—often surprising and unexpected—that you could not anticipate. When you see it, you frequently think, now I see how it does what it does."

'Scaffolding' method allows biochemists to see proteins in remarkable detail

UCLA biochemists have achieved a first in biology: viewing at near-atomic detail the smallest protein ever seen by the technique whose development won its creators the 2017 Nobel Prize in chemistry. That technique, called cryo-electron microscopy, enables scientists to see large biomolecules, such as viruses, in extraordinary detail.

Until now, this method has not worked with the thousands of much smaller proteins, which can cause diseases if defective, that are inside cells. A team led by Todd Yeates, a UCLA professor of chemistry and biochemistry, reports results that hold the promise of using cryo-electron microscopy to better understand many important proteins. The research is published in the journal Proceedings of the National Academy of Sciences.

This is a great signal about the transition of global energy geopolitics. The 4 min video by PM Jacinda Ardern is well worth the watch.

New Zealand bans all new offshore oil exploration as part of 'carbon-neutral future'

Prime minister Jacinda Ardern says move ‘will essentially take effect in 30 or more years’ time’
The New Zealand government will grant no new offshore oil exploration permits in a move that is being hailed by conservation and environmental groups as a historic victory in the battle against climate change.

The ban will apply to new permits and won’t affect the existing 22, some of which have decades left on their exploration rights and cover an area of 100,000 sq km.
The prime minister, Jacinda Ardern, said her government “has a plan to transition towards a carbon-neutral future, one that looks 30 years in advance”.

“Transitions have to start somewhere and unless we make decisions today that will essentially take effect in 30 or more years’ time, we run the risk of acting too late and causing abrupt shocks to communities and our country.”

This is a great signal about the future of the city and of agriculture. The image gallery is very inspiring.
"Paris not only intends to produce fruit and vegetables but also (plans to) invent a new urban model ... Citizens want new ways to get involved in the city's invention and be the gardeners," says Penelope Komites, deputy mayor of Paris, who is in charge of the city's parks and green spaces.
"Three years ago, people laughed at my plan. Today, citizens are producing (produce) on roofs and in basements. We are also asked by numerous cities around the world to present the Parisian approach."

Paris to turn a third of its green space into urban farms

France's famously beautiful capital is not a place you'd expect to find chickens, beehives and rows of neatly planted cabbages -- but urban farming is flourishing in Paris.

It all started when the city's mayor, Anne Hidalgo, who was elected in 2014, declared her intention to make Paris a greener city. The Paris government responded to her call in 2016 by launching Parisculteurs, a project which aims to cover the city's rooftops and walls with 100 hectares (247 acres) of vegetation by 2020. One third of the green space, according to its plan, should be dedicated to urban farming.

So far, 74 companies and public institutions have signed a charter to partner with the city in developing urban agriculture.

This is a great signal of the accelerating transformation of energy geopolitics. The report is downloadable for free.

Global Trends in Renewable Energy Investment Report 2018

Banking on sunshine: World added fare more solar than fossil fuel power generating capacity in 2017
The Global Trends in Renewable Energy Investment 2018 report, published on April 5th by UN Environment, the Frankfurt School-UNEP Collaborating Centre, and Bloomberg New Energy Finance, finds that falling costs for solar electricity, and to some extent wind power, is continuing to drive deployment. Last year was the eighth in a row in which global investment in renewables exceeded $200 billion – and since 2004, the world has invested $2.9 trillion in these green energy sources. Overall, China was by far the world’s largest investing country in renewables, at a record $126.6 billion, up 31 per cent on 2016.

Solar energy dominated global investment in new power generation like never before in 2017. The world installed a record 98 gigawatts of new solar capacity, far more than the net additions of any other technology – renewable, fossil fuel or nuclear and solar power attracted far more investment, at $160.8 billion, up 18 per cent, than any other technology.

In total $279.8 billion was invested in renewables excluding large hydro and  a record 157 gigawatts of renewable power were commissioned last year, up from 143 gigawatts in 2016 and far out-stripping the net 70 gigawatts of fossil-fuel generating capacity added (after adjusting for the closure of some existing plants) over the same period.

Thinking about the world of ubiquitous sensors - for regulating environments and/or surveillance - or participatory sousveillance.

Self-Powered Image Sensor Could Watch You Forever

New technology puts the equivalent of a solar cell under each pixel
Solar cells convert light to electricity. Image sensors also convert light to electricity. If you could do them both at the same time in the same chip, you’d have the makings of a self-powered camera. Engineers at University of Michigan have recently come up with just that, an image sensor that does both things well enough to capture 15 images per second powered only by the daylight falling on it.

With such an energy harvesting imager integrated with and powering a tiny processor and wireless transceiver you could “put a small camera, almost invisible, anywhere,” says Euisik Yoon, the professor of electrical engineering and computer science at University of Michigan who led its development. They reported their results this week in IEEE Electron Device Letters.

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