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#435159 This Week’s Awesome Stories From ...

Posted on June 2, 2019 by Android

ARTIFICIAL INTELLIGENCE
DeepMind Can Now Beat Us at Multiplayer Games Too
Cade Metz | The New York Times
“DeepMind’s project is part of a broad effort to build artificial intelligence that can play enormously complex, three-dimensional video games, including Quake III, Dota 2 and StarCraft II. Many researchers believe that success in the virtual arena will eventually lead to automated systems with improved abilities in the real world.”

ROBOTICS
Tiny Robots Carry Stem Cells Through a Mouse
Emily Waltz | IEEE Spectrum
“Engineers have built microrobots to perform all sorts of tasks in the body, and can now add to that list another key skill: delivering stem cells. In a paper, published [May 29] in Science Robotics, researchers describe propelling a magnetically-controlled, stem-cell-carrying bot through a live mouse.” [Video shows microbots navigating a microfluidic chip. MRI could not be used to image the mouse as the bots navigate magnetically.]

COMPUTING
How a Quantum Computer Could Break 2048-Bit RSA Encryption in 8 Hours
Emerging Technology From the arXiv | MIT Technology Review
“[Two researchers] have found a more efficient way for quantum computers to perform the code-breaking calculations, reducing the resources they require by orders of magnitude. Consequently, these machines are significantly closer to reality than anyone suspected.” [The arXiv is a pre-print server for research that has not yet been peer reviewed.]

AUTOMATION
Lyft Has Completed 55,000 Self Driving Rides in Las Vegas
Christine Fisher | Engadget
“One year ago, Lyft launched its self-driving ride service in Las Vegas. Today, the company announced its 30-vehicle fleet has made 55,000 trips. That makes it the largest commercial program of its kind in the US.”

TRANSPORTATION
Flying Car Startup Alaka’i Bets Hydrogen Can Outdo Batteries
Eric Adams | Wired
“Alaka’i says the final product will be able to fly for up to four hours and cover 400 miles on a single load of fuel, which can be replenished in 10 minutes at a hydrogen fueling station. It has built a functional, full-scale prototype that will make its first flight ‘imminently,’ a spokesperson says.”

ETHICS
The World Economic Forum Wants to Develop Global Rules for AI
Will Knight | MIT Technology Review
“This week, AI experts, politicians, and CEOs will gather to ask an important question: Can the United States, China, or anyone else agree on how artificial intelligence should be used and controlled?”

SPACE
Building a Rocket in a Garage to Take on SpaceX and Blue Origin
Jackson Ryan | CNET
“While billionaire entrepreneurs like SpaceX’s Elon Musk and Blue Origin’s Jeff Bezos push the boundaries of human spaceflight and exploration, a legion of smaller private startups around the world have been developing their own rocket technology to launch lighter payloads into orbit.”

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#435140 This Week’s Awesome Stories From ...

Posted on May 26, 2019 by Android

GENETICS
Gene Therapy Might Have Its First Blockbuster
Antonio Regalado | MIT Technology Review
“…drug giant Novartis expects to win approval to launch what it says will be the first ‘blockbuster’ gene-replacement treatment. A blockbuster is any drug with more than $1 billion in sales each year. The treatment, called Zolgensma, is able to save infants born with spinal muscular atrophy (SMA) type 1, a degenerative disease that usually kills within two years.”

ARTIFICIAL INTELLIGENCE
AI Took a Test to Detect Lung Cancer. It Got an A.
Denise Grady | The New York Times
“Computers were as good or better than doctors at detecting tiny lung cancers on CT scans, in a study by researchers from Google and several medical centers. The technology is a work in progress, not ready for widespread use, but the new report, published Monday in the journal Nature Medicine, offers a glimpse of the future of artificial intelligence in medicine.”

ROBOTICS
The Rise and Reign of Starship, the World’s First Robotic Delivery Provider
Luke Dormehl | Digital Trends
“[Starship’s] delivery robots have travelled a combined 200,000 miles, carried out 50,000 deliveries, and been tested in over 100 cities in 20 countries. It is a regular fixture not just in multiple neighborhoods but also university campuses.”

SPACE
Elon Musk Just Ignited the Race to Build the Space Internet
Jonathan O’Callaghan | Wired
“It’s estimated that about 3.3 billion people lack access to the internet, but Elon Musk is trying to change that. On Thursday, May 23—after two cancelled launches the week before—SpaceX launched 60 Starlink satellites on a Falcon 9 rocket from Cape Canaveral, in Florida, as part of the firm’s mission to bring low-cost, high-speed internet to the world.”

VIRTUAL REALITY
The iPod of VR Is Here, and You Should Try It
Mark Wilson | Fast Company
“In nearly 15 years of writing about cutting-edge technology, I’ve never seen a single product line get so much better so fast. With [the Oculus] Quest, there are no PCs required. There are no wires to run. All you do is grab the cloth headset and pull it around your head.”

FUTURE OF FOOD
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.”

LONGEVITY
Can We Live Longer but Stay Younger?
Adam Gopnik | The New Yorker
“With greater longevity, the quest to avoid the infirmities of aging is more urgent than ever.”

PRIVACY
Facial Recognition Has Already Reached Its Breaking Point
Lily Hay Newman | Wired
“As facial recognition technologies have evolved from fledgling projects into powerful software platforms, researchers and civil liberties advocates have been issuing warnings about the potential for privacy erosions. Those mounting fears came to a head Wednesday in Congress.”

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#434508 The Top Biotech and Medicine Advances to ...

Posted on January 22, 2019 by Android

2018 was bonkers for science.

From a woman who gave birth using a transplanted uterus, to the infamous CRISPR baby scandal, to forensics adopting consumer-based genealogy test kits to track down criminals, last year was a factory churning out scientific “whoa” stories with consequences for years to come.

With CRISPR still in the headlines, Britain ready to bid Europe au revoir, and multiple scientific endeavors taking off, 2019 is shaping up to be just as tumultuous.

Here are the science and health stories that may blow up in the new year. But first, a note of caveat: predicting the future is tough. Forecasting is the lovechild between statistics and (a good deal of) intuition, and entire disciplines have been dedicated to the endeavor. But January is the perfect time to gaze into the crystal ball for wisps of insight into the year to come. Last year we predicted the widespread approval of gene therapy products—on the most part, we nailed it. This year we’re hedging our bets with multiple predictions.

Gene Drives Used in the Wild
The concept of gene drives scares many, for good reason. Gene drives are a step up in severity (and consequences) from CRISPR and other gene-editing tools. Even with germline editing, in which the sperm, egg, or embryos are altered, gene editing affects just one genetic line—one family—at least at the beginning, before they reproduce with the general population.

Gene drives, on the other hand, have the power to wipe out entire species.

In a nutshell, they’re little bits of DNA code that help a gene transfer from parent to child with almost 100 percent perfect probability. The “half of your DNA comes from dad, the other comes from mom” dogma? Gene drives smash that to bits.

In other words, the only time one would consider using a gene drive is to change the genetic makeup of an entire population. It sounds like the plot of a supervillain movie, but scientists have been toying around with the idea of deploying the technology—first in mosquitoes, then (potentially) in rodents.

By releasing just a handful of mutant mosquitoes that carry gene drives for infertility, for example, scientists could potentially wipe out entire populations that carry infectious scourges like malaria, dengue, or Zika. The technology is so potent—and dangerous—the US Defense Advances Research Projects Agency is shelling out $65 million to suss out how to deploy, control, counter, or even reverse the effects of tampering with ecology.

Last year, the U.N. gave a cautious go-ahead for the technology to be deployed in the wild in limited terms. Now, the first release of a genetically modified mosquito is set for testing in Burkina Faso in Africa—the first-ever field experiment involving gene drives.

The experiment will only release mosquitoes in the Anopheles genus, which are the main culprits transferring disease. As a first step, over 10,000 male mosquitoes are set for release into the wild. These dudes are genetically sterile but do not cause infertility, and will help scientists examine how they survive and disperse as a preparation for deploying gene-drive-carrying mosquitoes.

Hot on the project’s heels, the nonprofit consortium Target Malaria, backed by the Bill and Melinda Gates foundation, is engineering a gene drive called Mosq that will spread infertility across the population or kill out all female insects. Their attempt to hack the rules of inheritance—and save millions in the process—is slated for 2024.

A Universal Flu Vaccine
People often brush off flu as a mere annoyance, but the infection kills hundreds of thousands each year based on the CDC’s statistical estimates.

The flu virus is actually as difficult of a nemesis as HIV—it mutates at an extremely rapid rate, making effective vaccines almost impossible to engineer on time. Scientists currently use data to forecast the strains that will likely explode into an epidemic and urge the public to vaccinate against those predictions. That’s partly why, on average, flu vaccines only have a success rate of roughly 50 percent—not much better than a coin toss.

Tired of relying on educated guesses, scientists have been chipping away at a universal flu vaccine that targets all strains—perhaps even those we haven’t yet identified. Often referred to as the “holy grail” in epidemiology, these vaccines try to alert our immune systems to parts of a flu virus that are least variable from strain to strain.

Last November, a first universal flu vaccine developed by BiondVax entered Phase 3 clinical trials, which means it’s already been proven safe and effective in a small numbers and is now being tested in a broader population. The vaccine doesn’t rely on dead viruses, which is a common technique. Rather, it uses a small chain of amino acids—the chemical components that make up proteins—to stimulate the immune system into high alert.

With the government pouring $160 million into the research and several other universal candidates entering clinical trials, universal flu vaccines may finally experience a breakthrough this year.

In-Body Gene Editing Shows Further Promise
CRISPR and other gene editing tools headed the news last year, including both downers suggesting we already have immunity to the technology and hopeful news of it getting ready for treating inherited muscle-wasting diseases.

But what wasn’t widely broadcasted was the in-body gene editing experiments that have been rolling out with gusto. Last September, Sangamo Therapeutics in Richmond, California revealed that they had injected gene-editing enzymes into a patient in an effort to correct a genetic deficit that prevents him from breaking down complex sugars.

The effort is markedly different than the better-known CAR-T therapy, which extracts cells from the body for genetic engineering before returning them to the hosts. Rather, Sangamo’s treatment directly injects viruses carrying the edited genes into the body. So far, the procedure looks to be safe, though at the time of reporting it was too early to determine effectiveness.

This year the company hopes to finally answer whether it really worked.

If successful, it means that devastating genetic disorders could potentially be treated with just a few injections. With a gamut of new and more precise CRISPR and other gene-editing tools in the works, the list of treatable inherited diseases is likely to grow. And with the CRISPR baby scandal potentially dampening efforts at germline editing via regulations, in-body gene editing will likely receive more attention if Sangamo’s results return positive.

Neuralink and Other Brain-Machine Interfaces
Neuralink is the stuff of sci fi: tiny implanted particles into the brain could link up your biological wetware with silicon hardware and the internet.

But that’s exactly what Elon Musk’s company, founded in 2016, seeks to develop: brain-machine interfaces that could tinker with your neural circuits in an effort to treat diseases or even enhance your abilities.

Last November, Musk broke his silence on the secretive company, suggesting that he may announce something “interesting” in a few months, that’s “better than anyone thinks is possible.”

Musk’s aspiration for achieving symbiosis with artificial intelligence isn’t the driving force for all brain-machine interfaces (BMIs). In the clinics, the main push is to rehabilitate patients—those who suffer from paralysis, memory loss, or other nerve damage.

2019 may be the year that BMIs and neuromodulators cut the cord in the clinics. These devices may finally work autonomously within a malfunctioning brain, applying electrical stimulation only when necessary to reduce side effects without requiring external monitoring. Or they could allow scientists to control brains with light without needing bulky optical fibers.

Cutting the cord is just the first step to fine-tuning neurological treatments—or enhancements—to the tune of your own brain, and 2019 will keep on bringing the music.

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#433895 Sci-Fi Movies Are the Secret Weapon That ...

Posted on November 17, 2018 by Android

If there’s one line that stands the test of time in Steven Spielberg’s 1993 classic Jurassic Park, it’s probably Jeff Goldblum’s exclamation, “Your scientists were so preoccupied with whether or not they could, they didn’t stop to think if they should.”

Goldblum’s character, Dr. Ian Malcolm, was warning against the hubris of naively tinkering with dinosaur DNA in an effort to bring these extinct creatures back to life. Twenty-five years on, his words are taking on new relevance as a growing number of scientists and companies are grappling with how to tread the line between “could” and “should” in areas ranging from gene editing and real-world “de-extinction” to human augmentation, artificial intelligence and many others.

Despite growing concerns that powerful emerging technologies could lead to unexpected and wide-ranging consequences, innovators are struggling with how to develop beneficial new products while being socially responsible. Part of the answer could lie in watching more science fiction movies like Jurassic Park.

Hollywood Lessons in Societal Risks
I’ve long been interested in how innovators and others can better understand the increasingly complex landscape around the social risks and benefits associated with emerging technologies. Growing concerns over the impacts of tech on jobs, privacy, security and even the ability of people to live their lives without undue interference highlight the need for new thinking around how to innovate responsibly.

New ideas require creativity and imagination, and a willingness to see the world differently. And this is where science fiction movies can help.

Sci-fi flicks are, of course, notoriously unreliable when it comes to accurately depicting science and technology. But because their plots are often driven by the intertwined relationships between people and technology, they can be remarkably insightful in revealing social factors that affect successful and responsible innovation.

This is clearly seen in Jurassic Park. The movie provides a surprisingly good starting point for thinking about the pros and cons of modern-day genetic engineering and the growing interest in bringing extinct species back from the dead. But it also opens up conversations around the nature of complex systems that involve both people and technology, and the potential dangers of “permissionless” innovation that’s driven by power, wealth and a lack of accountability.

Similar insights emerge from a number of other movies, including Spielberg’s 2002 film “Minority Report”—which presaged a growing capacity for AI-enabled crime prediction and the ethical conundrums it’s raising—as well as the 2014 film Ex Machina.

As with Jurassic Park, Ex Machina centers around a wealthy and unaccountable entrepreneur who is supremely confident in his own abilities. In this case, the technology in question is artificial intelligence.

The movie tells a tale of an egotistical genius who creates a remarkable intelligent machine—but he lacks the awareness to recognize his limitations and the risks of what he’s doing. It also provides a chilling insight into potential dangers of creating machines that know us better than we know ourselves, while not being bound by human norms or values.

The result is a sobering reminder of how, without humility and a good dose of humanity, our innovations can come back to bite us.

The technologies in Jurassic Park, Minority Report, and Ex Machina lie beyond what is currently possible. Yet these films are often close enough to emerging trends that they help reveal the dangers of irresponsible, or simply naive, innovation. This is where these and other science fiction movies can help innovators better understand the social challenges they face and how to navigate them.

Real-World Problems Worked Out On-Screen
In a recent op-ed in the New York Times, journalist Kara Swisher asked, “Who will teach Silicon Valley to be ethical?” Prompted by a growing litany of socially questionable decisions amongst tech companies, Swisher suggests that many of them need to grow up and get serious about ethics. But ethics alone are rarely enough. It’s easy for good intentions to get swamped by fiscal pressures and mired in social realities.

Elon Musk has shown that brilliant tech innovators can take ethical missteps along the way. Image Credit:AP Photo/Chris Carlson
Technology companies increasingly need to find some way to break from business as usual if they are to become more responsible. High-profile cases involving companies like Facebook and Uber as well as Tesla’s Elon Musk have highlighted the social as well as the business dangers of operating without fully understanding the consequences of people-oriented actions.

Many more companies are struggling to create socially beneficial technologies and discovering that, without the necessary insights and tools, they risk blundering about in the dark.

For instance, earlier this year, researchers from Google and DeepMind published details of an artificial intelligence-enabled system that can lip-read far better than people. According to the paper’s authors, the technology has enormous potential to improve the lives of people who have trouble speaking aloud. Yet it doesn’t take much to imagine how this same technology could threaten the privacy and security of millions—especially when coupled with long-range surveillance cameras.

Developing technologies like this in socially responsible ways requires more than good intentions or simply establishing an ethics board. People need a sophisticated understanding of the often complex dynamic between technology and society. And while, as Mozilla’s Mitchell Baker suggests, scientists and technologists engaging with the humanities can be helpful, it’s not enough.

An Easy Way into a Serious Discipline
The “new formulation” of complementary skills Baker says innovators desperately need already exists in a thriving interdisciplinary community focused on socially responsible innovation. My home institution, the School for the Future of Innovation in Society at Arizona State University, is just one part of this.

Experts within this global community are actively exploring ways to translate good ideas into responsible practices. And this includes the need for creative insights into the social landscape around technology innovation, and the imagination to develop novel ways to navigate it.

People love to come together as a movie audience.Image credit: The National Archives UK, CC BY 4.0
Here is where science fiction movies become a powerful tool for guiding innovators, technology leaders and the companies where they work. Their fictional scenarios can reveal potential pitfalls and opportunities that can help steer real-world decisions toward socially beneficial and responsible outcomes, while avoiding unnecessary risks.

And science fiction movies bring people together. By their very nature, these films are social and educational levelers. Look at who’s watching and discussing the latest sci-fi blockbuster, and you’ll often find a diverse cross-section of society. The genre can help build bridges between people who know how science and technology work, and those who know what’s needed to ensure they work for the good of society.

This is the underlying theme in my new book Films from the Future: The Technology and Morality of Sci-Fi Movies. It’s written for anyone who’s curious about emerging trends in technology innovation and how they might potentially affect society. But it’s also written for innovators who want to do the right thing and just don’t know where to start.

Of course, science fiction films alone aren’t enough to ensure socially responsible innovation. But they can help reveal some profound societal challenges facing technology innovators and possible ways to navigate them. And what better way to learn how to innovate responsibly than to invite some friends round, open the popcorn and put on a movie?

It certainly beats being blindsided by risks that, with hindsight, could have been avoided.

Andrew Maynard, Director, Risk Innovation Lab, Arizona State University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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#433758 DeepMind’s New Research Plan to Make ...

Posted on October 15, 2018 by Android

Making sure artificial intelligence does what we want and behaves in predictable ways will be crucial as the technology becomes increasingly ubiquitous. It’s an area frequently neglected in the race to develop products, but DeepMind has now outlined its research agenda to tackle the problem.

AI safety, as the field is known, has been gaining prominence in recent years. That’s probably at least partly down to the overzealous warnings of a coming AI apocalypse from well-meaning, but underqualified pundits like Elon Musk and Stephen Hawking. But it’s also recognition of the fact that AI technology is quickly pervading all aspects of our lives, making decisions on everything from what movies we watch to whether we get a mortgage.

That’s why DeepMind hired a bevy of researchers who specialize in foreseeing the unforeseen consequences of the way we built AI back in 2016. And now the team has spelled out the three key domains they think require research if we’re going to build autonomous machines that do what we want.

In a new blog designed to provide updates on the team’s work, they introduce the ideas of specification, robustness, and assurance, which they say will act as the cornerstones of their future research. Specification involves making sure AI systems do what their operator intends; robustness means a system can cope with changes to its environment and attempts to throw it off course; and assurance involves our ability to understand what systems are doing and how to control them.

A classic thought experiment designed to illustrate how we could lose control of an AI system can help illustrate the problem of specification. Philosopher Nick Bostrom’s posited a hypothetical machine charged with making as many paperclips as possible. Because the creators fail to add what they might assume are obvious additional goals like not harming people, the AI wipes out humanity so we can’t switch it off before turning all matter in the universe into paperclips.

Obviously the example is extreme, but it shows how a poorly-specified goal can lead to unexpected and disastrous outcomes. Properly codifying the desires of the designer is no easy feat, though; often there are not neat ways to encompass both the explicit and implicit goals in ways that are understandable to the machine and don’t leave room for ambiguities, meaning we often rely on incomplete approximations.

The researchers note recent research by OpenAI in which an AI was trained to play a boat-racing game called CoastRunners. The game rewards players for hitting targets laid out along the race route. The AI worked out that it could get a higher score by repeatedly knocking over regenerating targets rather than actually completing the course. The blog post includes a link to a spreadsheet detailing scores of such examples.

Another key concern for AI designers is making their creation robust to the unpredictability of the real world. Despite their superhuman abilities on certain tasks, most cutting-edge AI systems are remarkably brittle. They tend to be trained on highly-curated datasets and so can fail when faced with unfamiliar input. This can happen by accident or by design—researchers have come up with numerous ways to trick image recognition algorithms into misclassifying things, including thinking a 3D printed tortoise was actually a gun.

Building systems that can deal with every possible encounter may not be feasible, so a big part of making AIs more robust may be getting them to avoid risks and ensuring they can recover from errors, or that they have failsafes to ensure errors don’t lead to catastrophic failure.

And finally, we need to have ways to make sure we can tell whether an AI is performing the way we expect it to. A key part of assurance is being able to effectively monitor systems and interpret what they’re doing—if we’re basing medical treatments or sentencing decisions on the output of an AI, we’d like to see the reasoning. That’s a major outstanding problem for popular deep learning approaches, which are largely indecipherable black boxes.

The other half of assurance is the ability to intervene if a machine isn’t behaving the way we’d like. But designing a reliable off switch is tough, because most learning systems have a strong incentive to prevent anyone from interfering with their goals.

The authors don’t pretend to have all the answers, but they hope the framework they’ve come up with can help guide others working on AI safety. While it may be some time before AI is truly in a position to do us harm, hopefully early efforts like these will mean it’s built on a solid foundation that ensures it is aligned with our goals.

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