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#437182 MIT’s Tiny New Brain Chip Aims for AI ...

The human brain operates on roughly 20 watts of power (a third of a 60-watt light bulb) in a space the size of, well, a human head. The biggest machine learning algorithms use closer to a nuclear power plant’s worth of electricity and racks of chips to learn.

That’s not to slander machine learning, but nature may have a tip or two to improve the situation. Luckily, there’s a branch of computer chip design heeding that call. By mimicking the brain, super-efficient neuromorphic chips aim to take AI off the cloud and put it in your pocket.

The latest such chip is smaller than a piece of confetti and has tens of thousands of artificial synapses made out of memristors—chip components that can mimic their natural counterparts in the brain.

In a recent paper in Nature Nanotechnology, a team of MIT scientists say their tiny new neuromorphic chip was used to store, retrieve, and manipulate images of Captain America’s Shield and MIT’s Killian Court. Whereas images stored with existing methods tended to lose fidelity over time, the new chip’s images remained crystal clear.

“So far, artificial synapse networks exist as software. We’re trying to build real neural network hardware for portable artificial intelligence systems,” Jeehwan Kim, associate professor of mechanical engineering at MIT said in a press release. “Imagine connecting a neuromorphic device to a camera on your car, and having it recognize lights and objects and make a decision immediately, without having to connect to the internet. We hope to use energy-efficient memristors to do those tasks on-site, in real-time.”

A Brain in Your Pocket
Whereas the computers in our phones and laptops use separate digital components for processing and memory—and therefore need to shuttle information between the two—the MIT chip uses analog components called memristors that process and store information in the same place. This is similar to the way the brain works and makes memristors far more efficient. To date, however, they’ve struggled with reliability and scalability.

To overcome these challenges, the MIT team designed a new kind of silicon-based, alloyed memristor. Ions flowing in memristors made from unalloyed materials tend to scatter as the components get smaller, meaning the signal loses fidelity and the resulting computations are less reliable. The team found an alloy of silver and copper helped stabilize the flow of silver ions between electrodes, allowing them to scale the number of memristors on the chip without sacrificing functionality.

While MIT’s new chip is promising, there’s likely a ways to go before memristor-based neuromorphic chips go mainstream. Between now and then, engineers like Kim have their work cut out for them to further scale and demonstrate their designs. But if successful, they could make for smarter smartphones and other even smaller devices.

“We would like to develop this technology further to have larger-scale arrays to do image recognition tasks,” Kim said. “And some day, you might be able to carry around artificial brains to do these kinds of tasks, without connecting to supercomputers, the internet, or the cloud.”

Special Chips for AI
The MIT work is part of a larger trend in computing and machine learning. As progress in classical chips has flagged in recent years, there’s been an increasing focus on more efficient software and specialized chips to continue pushing the pace.

Neuromorphic chips, for example, aren’t new. IBM and Intel are developing their own designs. So far, their chips have been based on groups of standard computing components, such as transistors (as opposed to memristors), arranged to imitate neurons in the brain. These chips are, however, still in the research phase.

Graphics processing units (GPUs)—chips originally developed for graphics-heavy work like video games—are the best practical example of specialized hardware for AI and were heavily used in this generation of machine learning early on. In the years since, Google, NVIDIA, and others have developed even more specialized chips that cater more specifically to machine learning.

The gains from such specialized chips are already being felt.

In a recent cost analysis of machine learning, research and investment firm ARK Invest said cost declines have far outpaced Moore’s Law. In a particular example, they found the cost to train an image recognition algorithm (ResNet-50) went from around $1,000 in 2017 to roughly $10 in 2019. The fall in cost to actually run such an algorithm was even more dramatic. It took $10,000 to classify a billion images in 2017 and just $0.03 in 2019.

Some of these declines can be traced to better software, but according to ARK, specialized chips have improved performance by nearly 16 times in the last three years.

As neuromorphic chips—and other tailored designs—advance further in the years to come, these trends in cost and performance may continue. Eventually, if all goes to plan, we might all carry a pocket brain that can do the work of today’s best AI.

Image credit: Peng Lin Continue reading

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#437157 A Human-Centric World of Work: Why It ...

Long before coronavirus appeared and shattered our pre-existing “normal,” the future of work was a widely discussed and debated topic. We’ve watched automation slowly but surely expand its capabilities and take over more jobs, and we’ve wondered what artificial intelligence will eventually be capable of.

The pandemic swiftly turned the working world on its head, putting millions of people out of a job and forcing millions more to work remotely. But essential questions remain largely unchanged: we still want to make sure we’re not replaced, we want to add value, and we want an equitable society where different types of work are valued fairly.

To address these issues—as well as how the pandemic has impacted them—this week Singularity University held a digital summit on the future of work. Forty-three speakers from multiple backgrounds, countries, and sectors of the economy shared their expertise on everything from work in developing markets to why we shouldn’t want to go back to the old normal.

Gary Bolles, SU’s chair for the Future of Work, kicked off the discussion with his thoughts on a future of work that’s human-centric, including why it matters and how to build it.

What Is Work?
“Work” seems like a straightforward concept to define, but since it’s constantly shifting shape over time, let’s make sure we’re on the same page. Bolles defined work, very basically, as human skills applied to problems.

“It doesn’t matter if it’s a dirty floor or a complex market entry strategy or a major challenge in the world,” he said. “We as humans create value by applying our skills to solve problems in the world.” You can think of the problems that need solving as the demand and human skills as the supply, and the two are in constant oscillation, including, every few decades or centuries, a massive shift.

We’re in the midst of one of those shifts right now (and we already were, long before the pandemic). Skills that have long been in demand are declining. The World Economic Forum’s 2018 Future of Jobs report listed things like manual dexterity, management of financial and material resources, and quality control and safety awareness as declining skills. Meanwhile, skills the next generation will need include analytical thinking and innovation, emotional intelligence, creativity, and systems analysis.

Along Came a Pandemic
With the outbreak of coronavirus and its spread around the world, the demand side of work shrunk; all the problems that needed solving gave way to the much bigger, more immediate problem of keeping people alive. But as a result, tens of millions of people around the world are out of work—and those are just the ones that are being counted, and they’re a fraction of the true total. There are additional millions in seasonal or gig jobs or who work in informal economies now without work, too.

“This is our opportunity to focus,” Bolles said. “How do we help people re-engage with work? And make it better work, a better economy, and a better set of design heuristics for a world that we all want?”

Bolles posed five key questions—some spurred by impact of the pandemic—on which future of work conversations should focus to make sure it’s a human-centric future.

1. What does an inclusive world of work look like? Rather than seeing our current systems of work as immutable, we need to actually understand those systems and how we want to change them.

2. How can we increase the value of human work? We know that robots and software are going to be fine in the future—but for humans to be fine, we need to design for that very intentionally.

3. How can entrepreneurship help create a better world of work? In many economies the new value that’s created often comes from younger companies; how do we nurture entrepreneurship?

4. What will the intersection of workplace and geography look like? A large percentage of the global workforce is now working from home; what could some of the outcomes of that be? How does gig work fit in?

5. How can we ensure a healthy evolution of work and life? The health and the protection of those at risk is why we shut down our economies, but we need to find a balance that allows people to work while keeping them safe.

Problem-Solving Doesn’t End
The end result these questions are driving towards, and our overarching goal, is maximizing human potential. “If we come up with ways we can continue to do that, we’ll have a much more beneficial future of work,” Bolles said. “We should all be talking about where we can have an impact.”

One small silver lining? We had plenty of problems to solve in the world before ever hearing about coronavirus, and now we have even more. Is the pace of automation accelerating due to the virus? Yes. Are companies finding more ways to automate their processes in order to keep people from getting sick? They are.

But we have a slew of new problems on our hands, and we’re not going to stop needing human skills to solve them (not to mention the new problems that will surely emerge as second- and third-order effects of the shutdowns). If Bolles’ definition of work holds up, we’ve got ours cut out for us.

In an article from April titled The Great Reset, Bolles outlined three phases of the unemployment slump (we’re currently still in the first phase) and what we should be doing to minimize the damage. “The evolution of work is not about what will happen 10 to 20 years from now,” he said. “It’s about what we could be doing differently today.”

Watch Bolles’ talk and those of dozens of other experts for more insights into building a human-centric future of work here.

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#437109 This Week’s Awesome Tech Stories From ...

FUTURE
Why the Coronavirus Is So Confusing
Ed Yong | The Atlantic
“…beyond its vast scope and sui generis nature, there are other reasons the pandemic continues to be so befuddling—a slew of forces scientific and societal, epidemiological and epistemological. What follows is an analysis of those forces, and a guide to making sense of a problem that is now too big for any one person to fully comprehend.”

ARTIFICIAL INTELLIGENCE
Common Sense Comes Closer to Computers
John Pavlus | Quanta Magazine
“The problem of common-sense reasoning has plagued the field of artificial intelligence for over 50 years. Now a new approach, borrowing from two disparate lines of thinking, has made important progress.”

BIOTECH
Scientists Create Glowing Plants Using Bioluminescent Mushroom DNA
George Dvorsky | Gizmodo
“New research published today in Nature Biotechnology describes a new technique, in which the DNA from bioluminescent mushrooms was used to create plants that glow 10 times brighter than their bacteria-powered precursors. Botanists could eventually use this technique to study the inner workings of plants, but it also introduces the possibility of glowing ornamental plants for our homes.”

HEALTH
Old Drugs May Find a New Purpose: Fighting the Coronavirus
Carl Zimmer | The New York Times
“Driven by the pandemic’s spread, research teams have been screening thousands of drugs to see if they have this unexpected potential to fight the coronavirus. They’ve tested the drugs on dishes of cells, and a few dozen candidates have made the first cut.”

MACHINE LEARNING
OpenAI’s New Experiments in Music Generation Create an Uncanny Valley Elvis
Devin Coldewey | TechCrunch
“AI-generated music is a fascinating new field, and deep-pocketed research outfit OpenAI has hit new heights in it, creating recreations of songs in the style of Elvis, 2Pac and others. The results are convincing, but fall squarely in the unnerving ‘uncanny valley’ of audio, sounding rather like good, but drunk, karaoke heard through a haze of drugs.”

CULTURE
Neural Net-Generated Memes Are One of the Best Uses of AI on the Internet
Jay Peters | The Verge
“I’ve spent a good chunk of my workday so far creating memes thanks to this amazing website from Imgflip that automatically generates captions for memes using a neural network. …You can pick from 48 classic meme templates, including distracted boyfriend, Drake in ‘Hotline Bling,’ mocking Spongebob, surprised Pikachu, and Oprah giving things away.”

GENETICS
Can Genetic Engineering Bring Back the American Chestnut?
Gabriel Popkin | The New York Times Magazine
“The geneticists’ research forces conservationists to confront, in a new and sometimes discomfiting way, the prospect that repairing the natural world does not necessarily mean returning to an unblemished Eden. It may instead mean embracing a role that we’ve already assumed: engineers of everything, including nature.”

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#436784 This Week’s Awesome Tech Stories From ...

COMPUTING
Inside the Race to Build the Best Quantum Computer on Earth
Gideon Lichfield | MIT Technology Review
“Regardless of whether you agree with Google’s position [on ‘quantum supremacy’] or IBM’s, the next goal is clear, Oliver says: to build a quantum computer that can do something useful. …The trouble is that it’s nearly impossible to predict what the first useful task will be, or how big a computer will be needed to perform it.”

FUTURE
We’re Not Prepared for the End of Moore’s Law
David Rotman | MIT Technology Review
“Quantum computing, carbon nanotube transistors, even spintronics, are enticing possibilities—but none are obvious replacements for the promise that Gordon Moore first saw in a simple integrated circuit. We need the research investments now to find out, though. Because one prediction is pretty much certain to come true: we’re always going to want more computing power.”

ROBOTICS
Flippy the Burger-Flipping Robot Is Changing the Face of Fast Food as We Know It
Luke Dormehl | Digital Trends
“Flippy is the result of the Miso team’s robotics expertise, coupled with that industry-specific knowledge. It’s a burger-flipping robot arm that’s equipped with both thermal and regular vision, which grills burgers to order while also advising human collaborators in the kitchen when they need to add cheese or prep buns for serving.”

BIOTECHNOLOGY
The Next Generation of Batteries Could Be Built by Viruses
Daniel Oberhaus | Wired
“[MIT bioengineering professor Angela Belcher has] made viruses that can work with over 150 different materials and demonstrated that her technique can be used to manufacture other materials like solar cells. Belcher’s dream of zipping around in a ‘virus-powered car’ still hasn’t come true, but after years of work she and her colleagues at MIT are on the cusp of taking the technology out of the lab and into the real world.”

SPACE
Biggest Cosmic Explosion Ever Detected Left Huge Dent in Space
Hannah Devlin | The Guardian
“The biggest cosmic explosion on record has been detected—an event so powerful that it punched a dent the size of 15 Milky Ways in the surrounding space. The eruption is thought to have originated at a supermassive black hole in the Ophiuchus galaxy cluster, which is about 390 million light years from Earth.”

SCIENCE FICTION
Star Trek’s Warp Speed Would Have Tragic Consequences
Cassidy Ward | SyFy
“The various crews of Trek‘s slate of television shows and movies can get from here to there without much fanfare. Seeking out new worlds and new civilizations is no more difficult than gassing up the car and packing a cooler full of junk food. And they don’t even need to do that! The replicators will crank out a bologna sandwich just like mom used to make. All that’s left is to go, but what happens then?”

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#436507 The Weird, the Wacky, the Just Plain ...

As you know if you’ve ever been to, heard of, or read about the annual Consumer Electronics Show in Vegas, there’s no shortage of tech in any form: gadgets, gizmos, and concepts abound. You probably couldn’t see them all in a month even if you spent all day every day trying.

Given the sheer scale of the show, the number of exhibitors, and the inherent subjectivity of bestowing superlatives, it’s hard to pick out the coolest tech from CES. But I’m going to do it anyway; in no particular order, here are some of the products and concepts that I personally found most intriguing at this year’s event.

e-Novia’s Haptic Gloves
Italian startup e-Novia’s Weart glove uses a ‘sensing core’ to record tactile sensations and an ‘actuation core’ to reproduce those sensations onto the wearer’s skin. Haptic gloves will bring touch to VR and AR experiences, making them that much more life-like. The tech could also be applied to digitization of materials and in gaming and entertainment.

e-Novia’s modular haptic glove
I expected a full glove, but in fact there were two rings that attached to my fingers. Weart co-founder Giovanni Spagnoletti explained that they’re taking a modular approach, so as to better tailor the technology to different experiences. He then walked me through a virtual reality experience that was a sort of simulated science experiment: I had to lift a glass beaker, place it on a stove, pour in an ingredient, open a safe to access some dry ice, add that, and so on. As I went through the steps, I felt the beaker heat up and cool off at the expected times, and felt the liquid moving inside, as well as the pressure of my fingertips against the numbered buttons on the safe.

A virtual (but tactile) science experiment
There was a slight delay between my taking an action and feeling the corresponding tactile sensation, but on the whole, the haptic glove definitely made the experience more realistic—and more fun. Slightly less fun but definitely more significant, Spagnoletti told me Weart is working with a medical group to bring tactile sensations to VR training for surgeons.

Sarcos Robotics’ Exoskeleton
That tire may as well be a feather
Sarcos Robotics unveiled its Guardian XO full-body exoskeleton, which it says can safely lift up to 200 pounds across an extended work session. What’s cool about this particular exoskeleton is that it’s not just a prototype; the company announced a partnership with Delta airlines, which will be trialing the technology for aircraft maintenance, engine repair, and luggage handling. In a demo, I watched a petite female volunteer strap into the exoskeleton and easily lift a 50-pound weight with one hand, and a Sarcos employee lift and attach a heavy component of a propeller; she explained that the strength-augmenting function of the exoskeleton can easily be switched on or off—and the wearer’s hands released—to facilitate multi-step tasks.

Hyundai’s Flying Taxi
Where to?
Hyundai and Uber partnered to unveil an air taxi concept. With a 49-foot wingspan, 4 lift rotors, and 4 tilt rotors, the aircraft would be manned by a pilot and could carry 4 passengers at speeds up to 180 miles per hour. The companies say you’ll be able to ride across your city in one of these by 2030—we’ll see if the regulatory environment, public opinion, and other factors outside of technological capability let that happen.

Mercedes’ Avatar Concept Car
Welcome to the future
As evident from its name, Mercedes’ sweet new Vision AVTR concept car was inspired by the movie Avatar; director James Cameron helped design it. The all-electric car has no steering wheel, transparent doors, seats made of vegan leather, and 33 reptilian-scale-like flaps on the back; its design is meant to connect the driver with both the car and the surrounding environment in a natural, seamless way.

Next-generation scrolling
Offered the chance to ‘drive’ the car, I jumped on it. Placing my hand on the center console started the engine, and within seconds it had synced to my heartbeat, which reverberated through the car. The whole dashboard, from driver door to passenger door, is one big LED display. It showed a virtual landscape I could select by holding up my hand: as I moved my hand from left to right, different images were projected onto my open palm. Closing my hand on an image selected it, and suddenly it looked like I was in the middle of a lush green mountain range. Applying slight forward pressure on the center console made the car advance in the virtual landscape; it was essentially like playing a really cool video game.

Mercedes is aiming to have a carbon-neutral production fleet by 2039, and to reduce the amount of energy it uses during production by 40 percent by 2030. It’s unclear when—or whether—the man-machine-nature connecting features of the Vision AVTR will start showing up in production, but I for one will be on the lookout.

Waverly Labs’ In-Ear Translator
Waverly Labs unveiled its Ambassador translator earlier this year and has it on display at the show. It’s worn on the ear and uses a far-field microphone array with speech recognition to translate real-time conversations in 20 different languages. Besides in-ear audio, translations can also appear as text on an app or be broadcast live in a conference environment.

It’s kind of like a giant talking earring
I stopped by the booth and tested out the translator with Waverly senior software engineer Georgiy Konovalov. We each hooked on an earpiece, and first, he spoke to me in Russian. After a delay of a couple seconds, I heard his words in—slightly robotic, but fully comprehensible—English. Then we switched: I spoke to him in Spanish, my words popped up on his phone screen in Cyrillic, and he translated them back to English for me out loud.

On the whole, the demo was pretty cool. If you’ve ever been lost in a foreign country whose language you don’t speak, imagine how handy a gadget like this would come in. Let’s just hope that once they’re more widespread, these products don’t end up discouraging people from learning languages.

Not to be outdone, Google also announced updates to its Translate product, which is being deployed at information desks in JFK airport’s international terminal, in sports stadiums in Qatar, and by some large hotel chains.

Stratuscent’s Digital Nose
AI is making steady progress towards achieving human-like vision and hearing—but there’s been less work done on mimicking our sense of smell (maybe because it’s less useful in everyday applications). Stratuscent’s digital nose, which it says is based on NASA patents, uses chemical receptors and AI to identify both simple chemicals and complex scents. The company is aiming to create the world’s first comprehensive database of everyday scents, which it says it will use to make “intelligent decisions” for customers. What kind of decisions remains to be seen—and smelled.

Banner Image Credit: The Mercedes Vision AVTR concept car. Photo by Vanessa Bates Ramirez Continue reading

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