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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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#437139 SILVER2 aquatic robot walks around on ...

A team of Italian researchers from the BioRobotics Institute, Scuola Superiore Sant'Anna and Stazione Zoologica Anton Dohrn has developed a new and improved version of its Seabed Interaction Legged Vehicle for Exploration and Research (SILVER) with the SILVER2—a robot that can walk around on the seafloor taking video as it goes. In their paper published in the journal Science Robotics, the group describes the robot, its capabilities and how it might be used in research efforts. Continue reading

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#436946 Coronavirus May Mean Automation Is ...

We’re in the midst of a public health emergency, and life as we know it has ground to a halt. The places we usually go are closed, the events we were looking forward to are canceled, and some of us have lost our jobs or fear losing them soon.

But although it may not seem like it, there are some silver linings; this crisis is bringing out the worst in some (I’m looking at you, toilet paper hoarders), but the best in many. Italians on lockdown are singing together, Spaniards on lockdown are exercising together, this entrepreneur made a DIY ventilator and put it on YouTube, and volunteers in Italy 3D printed medical valves for virus treatment at a fraction of their usual cost.

Indeed, if you want to feel like there’s still hope for humanity instead of feeling like we’re about to snowball into terribleness as a species, just look at these examples—and I’m sure there are many more out there. There’s plenty of hope and opportunity to be found in this crisis.

Peter Xing, a keynote speaker and writer on emerging technologies and associate director in technology and growth initiatives at KPMG, would agree. Xing believes the coronavirus epidemic is presenting us with ample opportunities for increased automation and remote delivery of goods and services. “The upside right now is the burgeoning platform of the digital transformation ecosystem,” he said.

In a thought-provoking talk at Singularity University’s COVID-19 virtual summit this week, Xing explained how the outbreak is accelerating our transition to a highly-automated society—and painted a picture of what the future may look like.

Confronting Scarcity
You’ve probably seen them by now—the barren shelves at your local grocery store. Whether you were in the paper goods aisle, the frozen food section, or the fresh produce area, it was clear something was amiss; the shelves were empty. One of the most inexplicable items people have been panic-bulk-buying is toilet paper.

Xing described this toilet paper scarcity as a prisoner’s dilemma, pointing out that we have a scarcity problem right now in terms of our mindset, not in terms of actual supply shortages. “It’s a prisoner’s dilemma in that we’re all prisoners in our homes right now, and we can either hoard or not hoard, and the outcomes depend on how we collaborate with each other,” he said. “But it’s not a zero-sum game.”

Xing referenced a CNN article about why toilet paper, of all things, is one of the items people have been panic-buying most (I, too, have been utterly baffled by this phenomenon). But maybe there’d be less panic if we knew more about the production methods and supply chain involved in manufacturing toilet paper. It turns out it’s a highly automated process (you can learn more about it in this documentary by National Geographic) and requires very few people (though it does require about 27,000 trees a day—so stop bulk-buying it! Just stop!).

The supply chain limitation here is in the raw material; we certainly can’t keep cutting down this many trees a day forever. But—somewhat ironically, given the Costco cartloads of TP people have been stuffing into their trunks and backseats—thanks to automation, toilet paper isn’t something stores are going to stop receiving anytime soon.

Automation For All
Now we have a reason to apply this level of automation to, well, pretty much everything.

Though our current situation may force us into using more robots and automated systems sooner than we’d planned, it will end up saving us money and creating opportunity, Xing believes. He cited “fast-casual” restaurants (Chipotle, Panera, etc.) as a prime example.

Currently, people in the US spend much more to eat at home than we do to eat in fast-casual restaurants if you take into account the cost of the food we’re preparing plus the value of the time we’re spending on cooking, grocery shopping, and cleaning up after meals. According to research from investment management firm ARK Invest, taking all these costs into account makes for about $12 per meal for food cooked at home.

That’s the same as or more than the cost of grabbing a burrito or a sandwich at the joint around the corner. As more of the repetitive, low-skill tasks involved in preparing fast casual meals are automated, their cost will drop even more, giving us more incentive to forego home cooking. (But, it’s worth noting that these figures don’t take into account that eating at home is, in most cases, better for you since you’re less likely to fill your food with sugar, oil, or various other taste-enhancing but health-destroying ingredients—plus, there are those of us who get a nearly incomparable amount of joy from laboring over then savoring a homemade meal).

Now that we’re not supposed to be touching each other or touching anything anyone else has touched, but we still need to eat, automating food preparation sounds appealing (and maybe necessary). Multiple food delivery services have already implemented a contactless delivery option, where customers can choose to have their food left on their doorstep.

Besides the opportunities for in-restaurant automation, “This is an opportunity for automation to happen at the last mile,” said Xing. Delivery drones, robots, and autonomous trucks and vans could all play a part. In fact, use of delivery drones has ramped up in China since the outbreak.

Speaking of deliveries, service robots have steadily increased in numbers at Amazon; as of late 2019, the company employed around 650,000 humans and 200,000 robots—and costs have gone down as robots have gone up.

ARK Invest’s research predicts automation could add $800 billion to US GDP over the next 5 years and $12 trillion during the next 15 years. On this trajectory, GDP would end up being 40 percent higher with automation than without it.

Automating Ourselves?
This is all well and good, but what do these numbers and percentages mean for the average consumer, worker, or citizen?

“The benefits of automation aren’t being passed on to the average citizen,” said Xing. “They’re going to the shareholders of the companies creating the automation.” This is where policies like universal basic income and universal healthcare come in; in the not-too-distant future, we may see more movement toward measures like these (depending how the election goes) that spread the benefit of automation out rather than concentrating it in a few wealthy hands.

In the meantime, though, some people are benefiting from automation in ways that maybe weren’t expected. We’re in the midst of what’s probably the biggest remote-work experiment in US history, not to mention remote learning. Tools that let us digitally communicate and collaborate, like Slack, Zoom, Dropbox, and Gsuite, are enabling remote work in a way that wouldn’t have been possible 20 or even 10 years ago.

In addition, Xing said, tools like DataRobot and H2O.ai are democratizing artificial intelligence by allowing almost anyone, not just data scientists or computer engineers, to run machine learning algorithms. People are codifying the steps in their own repetitive work processes and having their computers take over tasks for them.

As 3D printing gets cheaper and more accessible, it’s also being more widely adopted, and people are finding more applications (case in point: the Italians mentioned above who figured out how to cheaply print a medical valve for coronavirus treatment).

The Mother of Invention
This movement towards a more automated society has some positives: it will help us stay healthy during times like the present, it will drive down the cost of goods and services, and it will grow our GDP in the long run. But by leaning into automation, will we be enabling a future that keeps us more physically, psychologically, and emotionally distant from each other?

We’re in a crisis, and desperate times call for desperate measures. We’re sheltering in place, practicing social distancing, and trying not to touch each other. And for most of us, this is really unpleasant and difficult. We can’t wait for it to be over.

For better or worse, this pandemic will likely make us pick up the pace on our path to automation, across many sectors and processes. The solutions people implement during this crisis won’t disappear when things go back to normal (and, depending who you talk to, they may never really do so).

But let’s make sure to remember something. Even once robots are making our food and drones are delivering it, and our computers are doing data entry and email replies on our behalf, and we all have 3D printers to make anything we want at home—we’re still going to be human. And humans like being around each other. We like seeing one another’s faces, hearing one another’s voices, and feeling one another’s touch—in person, not on a screen or in an app.

No amount of automation is going to change that, and beyond lowering costs or increasing GDP, our greatest and most crucial responsibility will always be to take care of each other.

Image Credit: Gritt Zheng on Unsplash Continue reading

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#436491 The Year’s Most Fascinating Tech ...

Last Saturday we took a look at some of the most-read Singularity Hub articles from 2019. This week, we’re featuring some of our favorite articles from the last year. As opposed to short pieces about what’s happening, these are long reads about why it matters and what’s coming next. Some of them make the news while others frame the news, go deep on big ideas, go behind the scenes, or explore the human side of technological progress.

We hope you find them as fascinating, inspiring, and illuminating as we did.

DeepMind and Google: The Battle to Control Artificial Intelligence
Hal Hodson | 1843
“[DeepMind cofounder and CEO Demis] Hassabis thought DeepMind would be a hybrid: it would have the drive of a startup, the brains of the greatest universities, and the deep pockets of one of the world’s most valuable companies. Every element was in place to hasten the arrival of [artificial general intelligence] and solve the causes of human misery.”

The Most Powerful Person in Silicon Valley
Katrina Brooker | Fast Company
“Billionaire Masayoshi Son—not Elon Musk, Jeff Bezos, or Mark Zuckerberg—has the most audacious vision for an AI-powered utopia where machines control how we live. And he’s spending hundreds of billions of dollars to realize it. Are you ready to live in Masa World?”

AR Will Spark the Next Big Tech Platform—Call It Mirrorworld
Kevin Kelly | Wired
“Eventually this melded world will be the size of our planet. It will be humanity’s greatest achievement, creating new levels of wealth, new social problems, and uncountable opportunities for billions of people. There are no experts yet to make this world; you are not late.”

Behind the Scenes of a Radical New Cancer Cure
Ilana Yurkiewicz | Undark
“I remember the first time I watched a patient get his Day 0 infusion. It felt anti-climactic. The entire process took about 15 minutes. The CAR-T cells are invisible to the naked eye, housed in a small plastic bag containing clear liquid. ‘That’s it?’ my patient asked when the nurse said it was over. The infusion part is easy. The hard part is everything that comes next.”

The Promise and Price of Cellular Therapies
Siddhartha Mukherjee | The New Yorker
“We like to imagine medical revolutions as, well, revolutionary—propelled forward through leaps of genius and technological innovation. But they are also evolutionary, nudged forward through the optimization of design and manufacture.”

Impossible Foods’ Rising Empire of Almost Meat
Chris Ip | Engadget
“Impossible says it wants to ultimately create a parallel universe of ersatz animal products from steak to eggs. …Yet as Impossible ventures deeper into the culinary uncanny valley, it also needs society to discard a fundamental cultural idea that dates back millennia and accept a new truth: Meat doesn’t have to come from animals.”

Inside the Amazon Warehouse Where Humans and Machines Become One
Matt Simon | Wired
“Seen from above, the scale of the system is dizzying. My robot, a little orange slab known as a ‘drive’ (or more formally and mythically, Pegasus), is just one of hundreds of its kind swarming a 125,000-square-foot ‘field’ pockmarked with chutes. It’s a symphony of electric whirring, with robots pausing for one another at intersections and delivering their packages to the slides.”

Boston Dynamics’ Robots Are Preparing to Leave the Lab—Is the World Ready?
James Vincent | The Verge
“After decades of kicking machines in parking lots, the company is set to launch its first ever commercial bot later this year: the quadrupedal Spot. It’s a crucial test for a company that’s spent decades pursuing long-sighted R&D. And more importantly, the success—or failure—of Spot will tell us a lot about our own robot future. Are we ready for machines to walk among us?”

I Cut the ‘Big Five’ Tech Giants From My Life. It Was Hell
Kashmir Hill | Gizmodo
“Critics of the big tech companies are often told, ‘If you don’t like the company, don’t use its products.’ I did this experiment to find out if that is possible, and I found out that it’s not—with the exception of Apple. …These companies are unavoidable because they control internet infrastructure, online commerce, and information flows.”

Why I (Still) Love Tech: In Defense of a Difficult Industry
Paul Ford | Wired
“The mysteries of software caught my eye when I was a boy, and I still see it with the same wonder, even though I’m now an adult. Proudshamed, yes, but I still love it, the mess of it, the code and toolkits, down to the pixels and the processors, and up to the buses and bridges. I love the whole made world. But I can’t deny that the miracle is over, and that there is an unbelievable amount of work left for us to do.”

The Peculiar Blindness of Experts
David Epstein | The Atlantic
“In business, esteemed (and lavishly compensated) forecasters routinely are wildly wrong in their predictions of everything from the next stock-market correction to the next housing boom. Reliable insight into the future is possible, however. It just requires a style of thinking that’s uncommon among experts who are certain that their deep knowledge has granted them a special grasp of what is to come.”

The Most Controversial Tree in the World
Rowan Jacobson | Pacific Standard
“…we are all GMOs, the beneficiaries of freakishly unlikely genetic mash-ups, and the real Island of Dr. Moreau is that blue-green botanical garden positioned third from the sun. Rather than changing the nature of nature, as I once thought, this might just be the very nature of nature.”

How an Augmented Reality Game Escalated Into Real-World Spy Warfare
Elizabeth Ballou | Vice
“In Ingress, players accept that every park and train station could be the site of an epic showdown, but that’s only the first step. The magic happens when other people accept that, too. When players feel like that magic is real, there are few limits to what they’ll do or where they’ll go for the sake of the game. ”

The Shady Cryptocurrency Boom on the Post-Soviet Frontier
Hannah Lucinda Smith | Wired
“…although the tourists won’t guess it as they stand at Kuchurgan’s gates, admiring how the evening light reflects off the silver plaque of Lenin, this plant is pumping out juice to a modern-day gold rush: a cryptocurrency boom that is underway all across the former Soviet Union, from the battlefields of eastern Ukraine to time-warp enclaves like Transnistria and freshly annexed Crimea.”

Scientists Are Totally Rethinking Animal Cognition
Ross Andersen | The Atlantic
“This idea that animals are conscious was long unpopular in the West, but it has lately found favor among scientists who study animal cognition. …For many scientists, the resonant mystery is no longer which animals are conscious, but which are not.”

I Wrote This on a 30-Year-Old Computer
Ian Bogost | The Atlantic
“[Back then] computing was an accompaniment to life, rather than the sieve through which all ideas and activities must filter. That makes using this 30-year-old device a surprising joy, one worth longing for on behalf of what it was at the time, rather than for the future it inaugurated.”

Image Credit: Wes Hicks / Unsplash Continue reading

Posted in Human Robots