Computer Science

DNA Robots Target Cancer

May 17, 2018

DNA nanorobots that travel the bloodstream, find tumors, and dispense a protein that causes blood clotting trigger the death of cancer cells in mice, according to a study published today (February 12) in Nature Biotechnology.

The authors have “demonstrated that it’s indeed possible to do site-specific drug delivery using biocompatible, biodegradable, DNA-based bionanorobots for cancer therapeutics,” says Suresh Neethirajan, a bioengineer at the University of Guelph in Ontario, Canada, who did not participate in the study. “It’s a combination of diagnosing the biomarkers on the surface of the cancer itself and also, upon recognizing that, delivering the specific drug to be able to treat it.”

The international team of researchers started with the goal of “finding a path to design nanorobots that can be applied to treatment of cancer in human[s],” writes coauthor Hao Yan of Arizona State University in an email to The Scientist.

Yan and colleagues first generated a self-assembling, rectangular, DNA-origami sheet to which they linked thrombin, an enzyme responsible for blood clotting. Then, they used DNA fasteners to join the long edges of the rectangle, resulting in a tubular nanorobot with thrombin on the inside. The authors designed the fasteners to dissociate when they bind nucleolin—a protein specific to the surface of tumor blood-vessel cells—at which point, the tube opens and exposes its cargo.

Nanorobot design. Thrombin is represented in pink and nucleolin in blue.S. LI ET AL., NATURE BIOTECHNOLOGY, 2018

The scientists next injected the nanorobots intravenously into nude mice with human breast cancer tumors. The robots grabbed onto vascular cells at tumor sites and caused extensive blood clots in the tumors’ vessels within 48 hours, but did not cause clotting elsewhere in the animals’ bodies. These blood clots led to tumor-cell necrosis, resulting in smaller tumors and a better chance for survival compared to control mice. Yan’s team also found that nanorobot treatment increased survival and led to smaller tumors in a mouse model of melanoma, and in mice with xenografts of human ovarian cancer cells.

The authors are “looking at specific binding to tumor cells, which is basically the holy grail for . . . cancer therapy,” says the University of Tennessee’s Scott Lenaghan, who was not involved in the work. The next step is to investigate any damage—such as undetected clots or immune-system responses—in the host organism, he says, as well as to determine how much thrombin is actually delivered at the tumor sites.

The authors showed in the study that the nanorobots didn’t cause clotting in major tissues in miniature pigs, which satisfies some safety concerns, but Yan agrees that more work is needed. “We are interested in looking further into the practicalities of this work in mouse models,” he writes.

Going from “a mouse model to humans is a huge step,” says Mauro Ferrari, a biomedical engineer at Houston Methodist Hospital and Weill Cornell Medical College who did not participate in the study. It’s not yet clear whether targeting nucleolin and delivering thrombin will be clinically relevant, he says, “but the breakthrough aspect is [that] this is a platform. They can use a similar approach for other things, which is really exciting. It’s got big implications.”

S. Li et al., “A DNA nanorobot functions as a cancer therapeutic in response to a molecular trigger in vivo,” Nature Biotechnology, doi:10.1038/nbt.4071, 2018.

This article was originally published by: https://www.the-scientist.com/?articles.view/articleNo/51717/title/DNA-Robots-Target-Cancer/

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Google’s AI Wizard Unveils a New Twist on Neural Networks

November 18, 2017

If you want to blame someone for the hoopla around artificial intelligence, 69-year-old Google researcher Geoff Hinton is a good candidate.

The droll University of Toronto professor jolted the field onto a new trajectory in October 2012. With two grad students, Hinton showed that an unfashionable technology he’d championed for decades called artificial neural networks permitted a huge leap in machines’ ability to understand images. Within six months, all three researchers were on Google’s payroll. Today neural networks transcribe our speech, recognize our pets, and fight our trolls.

But Hinton now belittles the technology he helped bring to the world. “I think the way we’re doing computer vision is just wrong,” he says. “It works better than anything else at present but that doesn’t mean it’s right.”

In its place, Hinton has unveiled another “old” idea that might transform how computers see—and reshape AI. That’s important because computer vision is crucial to ideas such as self-driving cars, and having software that plays doctor.

Late last week, Hinton released two research papers that he says prove out an idea he’s been mulling for almost 40 years. “It’s made a lot of intuitive sense to me for a very long time, it just hasn’t worked well,” Hinton says. “We’ve finally got something that works well.”

Hinton’s new approach, known as capsule networks, is a twist on neural networks intended to make machines better able to understand the world through images or video. In one of the papers posted last week, Hinton’s capsule networks matched the accuracy of the best previous techniques on a standard test of how well software can learn to recognize handwritten digits.

In the second, capsule networks almost halved the best previous error rate on a test that challenges software to recognize toys such as trucks and cars from different angles. Hinton has been working on his new technique with colleagues Sara Sabour and Nicholas Frosst at Google’s Toronto office.

Capsule networks aim to remedy a weakness of today’s machine-learning systems that limits their effectiveness. Image-recognition software in use today by Google and others needs a large number of example photos to learn to reliably recognize objects in all kinds of situations. That’s because the software isn’t very good at generalizing what it learns to new scenarios, for example understanding that an object is the same when seen from a new viewpoint.

To teach a computer to recognize a cat from many angles, for example, could require thousands of photos covering a variety of perspectives. Human children don’t need such explicit and extensive training to learn to recognize a household pet.

Hinton’s idea for narrowing the gulf between the best AI systems and ordinary toddlers is to build a little more knowledge of the world into computer-vision software. Capsules—small groups of crude virtual neurons—are designed to track different parts of an object, such as a cat’s nose and ears, and their relative positions in space. A network of many capsules can use that awareness to understand when a new scene is in fact a different view of something it has seen before.

Hinton formed his intuition that vision systems need such an inbuilt sense of geometry in 1979, when he was trying to figure out how humans use mental imagery. He first laid out a preliminary design for capsule networks in 2011. The fuller picture released last week was long anticipated by researchers in the field. “Everyone has been waiting for it and looking for the next great leap from Geoff,” says Kyunghyun Cho, a professor at NYU who works on image recognition.

It’s too early to say how big a leap Hinton has made—and he knows it. The AI veteran segues from quietly celebrating that his intuition is now supported by evidence, to explaining that capsule networks still need to be proven on large image collections, and that the current implementation is slow compared to existing image-recognition software.

Hinton is optimistic he can address those shortcomings. Others in the field are also hopeful about his long-maturing idea.

Roland Memisevic, cofounder of image-recognition startup Twenty Billion Neurons, and a professor at University of Montreal, says Hinton’s basic design should be capable of extracting more understanding from a given amount of data than existing systems. If proven out at scale, that could be helpful in domains such as healthcare, where image data to train AI systems is much scarcer than the large volume of selfies available around the internet.

In some ways, capsule networks are a departure from a recent trend in AI research. One interpretation of the recent success of neural networks is that humans should encode as little knowledge as possible into AI software, and instead make them figure things out for themselves from scratch. Gary Marcus, a professor of psychology at NYU who sold an AI startup to Uber last year, says Hinton’s latest work represents a welcome breath of fresh air. Marcus argues that AI researchers should be doing more to mimic how the brain has built-in, innate machinery for learning crucial skills like vision and language. “It’s too early to tell how far this particular architecture will go, but it’s great to see Hinton breaking out of the rut that the field has seemed fixated on,” Marcus says.

UPDATED, Nov. 2, 12:55 PM: This article has been updated to include the names of Geoff Hinton’s co-authors.

This article was originally published by:
https://www.wired.com/story/googles-ai-wizard-unveils-a-new-twist-on-neural-networks/

Deus ex machina: former Google engineer is developing an AI god

October 18, 2017

Intranet service? Check. Autonomous motorcycle? Check. Driverless car technology? Check. Obviously the next logical project for a successful Silicon Valley engineer is to set up an AI-worshipping religious organization.

Anthony Levandowski, who is at the center of a legal battle between Uber and Google’s Waymo, has established a nonprofit religious corporation called Way of the Future, according to state filings first uncovered by Wired’s Backchannel. Way of the Future’s startling mission: “To develop and promote the realization of a Godhead based on artificial intelligence and through understanding and worship of the Godhead contribute to the betterment of society.”

Levandowski was co-founder of autonomous trucking company Otto, which Uber bought in 2016. He was fired from Uber in May amid allegations that he had stolen trade secrets from Google to develop Otto’s self-driving technology. He must be grateful for this religious fall-back project, first registered in 2015.

The Way of the Future team did not respond to requests for more information about their proposed benevolent AI overlord, but history tells us that new technologies and scientific discoveries have continually shaped religion, killing old gods and giving birth to new ones.

As author Yuval Noah Harari notes: “That is why agricultural deities were different from hunter-gatherer spirits, why factory hands and peasants fantasised about different paradises, and why the revolutionary technologies of the 21st century are far more likely to spawn unprecedented religious movements than to revive medieval creeds.”

Religions, Harari argues, must keep up with the technological advancements of the day or they become irrelevant, unable to answer or understand the quandaries facing their disciples.

“The church does a terrible job of reaching out to Silicon Valley types,” acknowledges Christopher Benek a pastor in Florida and founding chair of the Christian Transhumanist Association.

Silicon Valley, meanwhile, has sought solace in technology and has developed quasi-religious concepts including the “singularity”, the hypothesis that machines will eventually be so smart that they will outperform all human capabilities, leading to a superhuman intelligence that will be so sophisticated it will be incomprehensible to our tiny fleshy, rational brains.

Anthony Levandowski, the former head of Uber’s self-driving program, with one of the company’s driverless cars in San Francisco. Photograph: Eric Risberg/AP

For futurists like Ray Kurzweil, this means we’ll be able to upload copies of our brains to these machines, leading to digital immortality. Others like Elon Musk and Stephen Hawking warn that such systems pose an existential threat to humanity.

“With artificial intelligence we are summoning the demon,” Musk said at a conference in 2014. “In all those stories where there’s the guy with the pentagram and the holy water, it’s like – yeah, he’s sure he can control the demon. Doesn’t work out.”

Benek argues that advanced AI is compatible with Christianity – it’s just another technology that humans have created under guidance from God that can be used for good or evil.

“I totally think that AI can participate in Christ’s redemptive purposes,” he said, by ensuring it is imbued with Christian values.

“Even if people don’t buy organized religion, they can buy into ‘do unto others’.”

For transhumanist and “recovering Catholic” Zoltan Istvan, religion and science converge conceptually in the singularity.

“God, if it exists as the most powerful of all singularities, has certainly already become pure organized intelligence,” he said, referring to an intelligence that “spans the universe through subatomic manipulation of physics”.

“And perhaps, there are other forms of intelligence more complicated than that which already exist and which already permeate our entire existence. Talk about ghost in the machine,” he added.

For Istvan, an AI-based God is likely to be more rational and more attractive than current concepts (“the Bible is a sadistic book”) and, he added, “this God will actually exist and hopefully will do things for us.”

We don’t know whether Levandowski’s Godhead ties into any existing theologies or is a manmade alternative, but it’s clear that advancements in technologies including AI and bioengineering kick up the kinds of ethical and moral dilemmas that make humans seek the advice and comfort from a higher power: what will humans do once artificial intelligence outperforms us in most tasks? How will society be affected by the ability to create super-smart, athletic “designer babies” that only the rich can afford? Should a driverless car kill five pedestrians or swerve to the side to kill the owner?

If traditional religions don’t have the answer, AI – or at least the promise of AI – might be alluring.

Original source: https://www.theguardian.com/technology/2017/sep/28/artificial-intelligence-god-anthony-levandowski

Supersapiens, the Rise of the Mind

July 23, 2017

In the new film Supersapiens, writer-director Markus Mooslechner raises a core question: As artificial intelligence rapidly blurs the boundaries between man and machine, are we witnessing the rise of a new human species?

The film features scientists, philosophers, and neurohackers Nick Bostrom, Richard Dawkins, Hugo De Garis, Adam Gazzaley, Ben Goertzel, Sam Harris, Randal Koene, Alma Mendez, Tim Mullen, Joel Murphy, David Putrino, Conor Russomanno, Anders Sandberg, Susan Schneider, Mikey Siegel, Hannes Sjoblad, and Andy Walshe.

“Humanity is facing a turning point — the next evolution of the human mind,” notes Mooslechner. “Will this evolution be a hybrid of man and machine, where artificial intelligence forces the emergence of a new human species? Or will a wave of new technologists, who frame themselves as ‘consciousness-hackers,’ become the future torch-bearers, using technology not to replace the human mind, but rather awaken within it powers we have always possessed — enlightenment at the push of a button?”

“It’s not obvious to me that a replacement of our species by our own technological creation would necessarily be a bad thing,” says ethologist-evolutionary biologist-author Dawkins in the film.

Supersapiens in a Terra Mater Factual Studios production. Executive Producers are Joanne Reay and Walter Koehler. Distribution is to be announced.


Markus Mooslechner | Supersapiens teaser

http://www.kurzweilai.net/supersapiens-the-rise-of-the-mind

The Fourth Industrial Revolution Is Here

February 25, 2017

The Fourth Industrial Revolution is upon us and now is the time to act.

Everything is changing each day and humans are making decisions that affect life in the future for generations to come.

We have gone from Steam Engines to Steel Mills, to computers to the Fourth Industrial Revolution that involves a digital economy, artificial intelligence, big data and a new system that introduces a new story of our future to enable different economic and human models.

Will the Fourth Industrial Revolution put humans first and empower technologies to give humans a better quality of life with cleaner air, water, food, health, a positive mindset and happiness? HOPE…

http://www.huffingtonpost.com/craig-zamary/the-fourth-industrial-rev_3_b_12423658.html

Intel Bets It Can Turn Everyday Silicon into Quantum Computing’s Wonder Material

December 18, 2016

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Sometimes the solution to a problem is staring you in the face all along. Chip maker Intel is betting that will be true in the race to build quantum computers—machines that should offer immense processing power by exploiting the oddities of quantum mechanics.

Competitors IBM, Microsoft, and Google are all developing quantum components that are different from the ones crunching data in today’s computers. But Intel is trying to adapt the workhorse of existing computers, the silicon transistor, for the task.

Intel has a team of quantum hardware engineers in Portland, Oregon, who collaborate with researchers in the Netherlands, at TU Delft’s QuTech quantum research institute, under a $50 million grant established last year. Earlier this month Intel’s group reported that they can now layer the ultra-pure silicon needed for a quantum computer onto the standard wafers used in chip factories.

This strategy makes Intel an outlier among industry and academic groups working on qubits, as the basic components needed for quantum computers are known. Other companies can run code on prototype chips with several qubits made from superconducting circuits (see “Google’s Quantum Dream Machine”). No one has yet advanced silicon qubits that far.

A quantum computer would need to have thousands or millions of qubits to be broadly useful, though. And Jim Clarke, who leads Intel’s project as director of quantum hardware, argues that silicon qubits are more likely to get to that point (although Intel is also doing some research on superconducting qubits). One thing in silicon’s favor, he says: the expertise and equipment used to make conventional chips with billions of identical transistors should allow work on perfecting and scaling up silicon qubits to progress quickly.

Intel’s silicon qubits represent data in a quantum property called the “spin” of a single electron trapped inside a modified version of the transistors in its existing commercial chips. “The hope is that if we make the best transistors, then with a few material and design changes we can make the best qubits,” says Clarke.

Another reason to work on silicon qubits is that they should be more reliable than the superconducting equivalents. Still, all qubits are error prone because they work on data using very weak quantum effects (see “Google Researchers Make Quantum Components More Reliable”).

The new process that helps Intel experiment with silicon qubits on standard chip wafers, developed with the materials companies Urenco and Air Liquide, should help speed up its research, says Andrew Dzurak, who works on silicon qubits at the University of New South Wales in Australia. “To get to hundreds of thousands of qubits, we will need incredible engineering reliability, and that is the hallmark of the semiconductor industry,” he says.

Companies developing superconducting qubits also make them using existing chip fabrication methods. But the resulting devices are larger than transistors, and there is no template for how to manufacture and package them up in large numbers, says Dzurak.

Chad Rigetti, founder and CEO of Rigetti Computing, a startup working on superconducting qubits similar to those Google and IBM are developing, agrees that this presents a challenge. But he argues that his chosen technology’s head start will afford ample time and resources to tackle the problem.

Google and Rigetti have both said that in just a few years they could build a quantum chip with tens or hundreds of qubits that dramatically outperforms conventional computers on certain problems, even doing useful work on problems in chemistry or machine learning.

From: https://www.technologyreview.com/s/603165/intel-bets-it-can-turn-everyday-silicon-into-quantum-computings-wonder-material/

We might live in a computer program, but it may not matter

December 18, 2016

grow-your-business-in-the-opportunity-matrix

By Philip Ball

Are you real? What about me?

These used to be questions that only philosophers worried about. Scientists just got on with figuring out how the world is, and why. But some of the current best guesses about how the world is seem to leave the question hanging over science too.

Several physicists, cosmologists and technologists are now happy to entertain the idea that we are all living inside a gigantic computer simulation, experiencing a Matrix-style virtual world that we mistakenly think is real.

Our instincts rebel, of course. It all feels too real to be a simulation. The weight of the cup in my hand, the rich aroma of the coffee it contains, the sounds all around me – how can such richness of experience be faked?

But then consider the extraordinary progress in computer and information technologies over the past few decades. Computers have given us games of uncanny realism – with autonomous characters responding to our choices – as well as virtual-reality simulators of tremendous persuasive power.

It is enough to make you paranoid.

The Matrix formulated the narrative with unprecedented clarity. In that story, humans are locked by a malignant power into a virtual world that they accept unquestioningly as “real”. But the science-fiction nightmare of being trapped in a universe manufactured within our minds can be traced back further, for instance to David Cronenberg’s Videodrome (1983) and Terry Gilliam’s Brazil (1985).

Over all these dystopian visions, there loom two questions. How would we know? And would it matter anyway?

Elon Musk, CEO of Tesla and SpaceX (Credit: Kristoffer Tripplaar/Alamy)

Elon Musk, CEO of Tesla and SpaceX (Credit: Kristoffer Tripplaar/Alamy)

The idea that we live in a simulation has some high-profile advocates.

In June 2016, technology entrepreneur Elon Musk asserted that the odds are “a billion to one” against us living in “base reality”.

Similarly, Google’s machine-intelligence guru Ray Kurzweil has suggested that “maybe our whole universe is a science experiment of some junior high-school student in another universe”

What’s more, some physicists are willing to entertain the possibility. In April 2016, several of them debated the issue at the American Museum of Natural History in New York, US.

None of these people are proposing that we are physical beings held in some gloopy vat and wired up to believe in the world around us, as in The Matrix.

Instead, there are at least two other ways that the Universe around us might not be the real one.

Cosmologist Alan Guth of the Massachusetts Institute of Technology, US has suggested that our entire Universe might be real yet still a kind of lab experiment. The idea is that our Universe was created by some super-intelligence, much as biologists breed colonies of micro-organisms.

More at: http://www.bbc.com/earth/story/20160901-we-might-live-in-a-computer-program-but-it-may-not-matter

Microsoft will ‘solve’ cancer within 10 years by ‘reprogramming’ diseased cells

November 14, 2016

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Microsoft has vowed to “solve the problem of cancer” within a decade by using ground-breaking computer science to crack the code of diseased cells so they can be reprogrammed back to a healthy state.

In a dramatic change of direction for the technology giant, the company has assembled a “small army” of the world’s best biologists, programmers and engineers who are tackling cancer as if it were a bug in a computer system.

This summer Microsoft opened its first wet laboratory where it will test out the findings of its computer scientists who are creating huge maps of the internal workings of cell networks.

Microsoft opened its first wet laboratory this summer
Microsoft opened its first ‘wet’ laboratory this summer

The researchers are even working on a computer made from DNA which could live inside cells and look for faults in bodily networks, like cancer. If it spotted cancerous chances it would reboot the system and clear out the diseased cells.

Chris Bishop, laboratory director at Microsoft Research, said: “I think it’s a very natural thing for Microsoft to be looking at because we have tremendous expertise in computer science and what is going on in cancer is a computational problem.

“It’s not just an analogy, it’s a deep mathematical insight. Biology and computing are disciplines which seem like chalk and cheese but which have very deep connections on the most fundamental level.”

The biological computation group at Microsoft are developing molecular computers built from DNA which act like a doctor to spot cancer cells and destroy them.

Andrew Philips, head of the group, said: “It’s long term, but… I think it will be technically possible in five to 10 years time to put in a smart molecular system that can detect disease.”

Andrew Philips, head of the group
Andrew Philips, head of the group Credit: Ed Miller

The programming principles and tools group has already developed software that mimics the healthy behavior of a cell, so that it can be compared to that of a diseased cell, to work out where the problem occurred and how it can be fixed.

The Bio Model Analyser software is already being used to help researchers understand how to treat leukemia more effectively.

Dr Jasmin Fisher
Dr Jasmin Fisher believes scientists may be able to control and regulate cancer ‘within a decade’

Dr Jasmin Fisher, senior researcher and an associate professor at Cambridge University, said: “If we are able to control and regulate cancer then it becomes like any chronic disease and then the problem is solved.”

“I think for some of the cancers five years, but definitely within a decade. Then we will probably have a century free of cancer.”

https://cf-particle-html.eip.telegraph.co.uk/d491ac71-4550-4634-a584-f9c03ead3f81.html?ref=http://www.telegraph.co.uk/science/2016/09/20/microsoft-will-solve-cancer-within-10-years-by-reprogramming-dis/&title=Microsoft%20will%20%27solve%27%20cancer%20within%2010%20years%20by%20%27reprogramming%27%20diseased%20cells

She believes that in the future smart devices will monitor health continually and compare it to how the human body should be operating, so that it can quickly detect problems.

“My own personal vision is that in the morning you wake up, you check your email and at the same time all of our genetic data, our pulse, our sleep patterns, how much we exercised, will be fed into a computer which will check your state of well-being and tell you how prone you are to getting flu, or some other horrible thing,” she added.

“In order to get there we need these kind of computer models which mimic and model the fundamental processes that are happening in our bodies.

“Under normal development cells divide and they die and there is a certain balance, the problems start when that balance is broken and that’s how we had uncontrolled proliferation and tumours.

“If we could have all of that sitting on your personal computer and monitoring your health state then it will alert us when something is coming.”

Improved scanning technology offers hope

Patients undergoing radiotherapy could see treatment slashed from hours to just minutes with a new innovation to quickly map the size of a tumour.

 consultant studying a mammogram showing a womans breast in order check for breast cancer, as experienced radiologists can spot subtle signs of breast cancer in mammogram images in just half a second, a study has found
Experienced radiologists can spot subtle signs of breast cancer in mammogram images in just half a second, a study has found Credit: PA

Currently radiologists must scan a tumour and then painstakingly draw the outline of the cancer on dozens of sections by hand to create a 3D map before treatment, a process which can take up to four hours.

They also must outline nearby important organs to make sure they are protected from the blast of radiation.

But Microsoft engineers have developed a programme which can delineate a tumour within minutes, meaning treatment can happen immediately.

The programme can also show doctors how effective each treatment has been, so the dose can be altered depending on how much the tumour has been shrunk.

“Eyeballing works very well for diagnosing,” said Antonio Criminisi, a machine learning and computer vision expert who heads radiomics research in Microsoft’s Cambridge, UK, lab.

“Expert radiologists can look at an image – say a scan of someone’s brain – and be able to say in two seconds, ‘Yes, there’s a tumor. No, there isn’t a tumor. But delineating a tumour by hand is not very accurate.”

The system could eventually evaluate 3D scans pixel by pixel to tell the radiologist exactly how much the tumor has grown, shrunk or changed shape since the last scan.

It also could provide information about things like tissue density, to give the radiologist a better sense of whether something is more likely a cyst or a tumor. And it could provide more fine-grained analysis of the health of cells surrounding a tumor.

“Doing all of that by eye is pretty much impossible,” added Dr Criminisi.

The images could also be 3D printed so that surgeons could practice a tricky operation, such as removing a hard-to -reach brain tumour, before surgery.

http://www.telegraph.co.uk/science/2016/09/20/microsoft-will-solve-cancer-within-10-years-by-reprogramming-dis/

Tiny Flying Robots Are Being Built To Pollinate Crops Instead Of Real Bees

November 14, 2016

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Honeybees, which pollinate nearly one-third of the food we eat , have been dying at unprecedented rates because of a mysterious phenomenon known as  colony collapse disorder  (CCD). The situation is so dire that in late June the White House gave a  new task force just 180 days to devise a coping strategy to protect bees and other pollinators. The crisis is generally attributed to a mixture of disease, parasites, and pesticides.

Other scientists are pursuing a different tack: replacing bees. While there’s no perfect solution, modern technology offers hope.

Last year, Harvard University researchers led by engineering professor Robert Wood introduced the first RoboBees, bee-size robots with the ability to lift off the ground and hover midair when tethered to a power supply. The details were published in the journal Science. A coauthor of that report, Harvard graduate student and mechanical engineer Kevin Ma, tells Business Insider that the team is “on the eve of the next big development.” Says Ma: “The robot can now carry more weight.”

The project represents a breakthrough in the field of micro-aerial vehicles. It had previously been impossible to pack all the things needed to make a robot fly onto such a small structure and keep it lightweight.

A Bee-Placement?

The researchers believe that as soon as 10 years from now these RoboBees could artificially pollinate a field of crops, a critical development if the commercial pollination industry cannot recover from severe yearly losses over the past decade.

The White House underscored what’s at stake, noting that the loss of bees and other species “requires immediate attention to ensure the sustainability of our food production systems, avoid additional economic impact on the agricultural sector, and protect the health of the environment.” Honeybees alone contribute more than $15 billion in value to U.S. agricultural crops each year.

But RoboBees are not yet a viable technological solution. First, the tiny bots have to be able to fly on their own and “talk” to one another to carry out tasks like a real honeybee hive.

“RoboBees will work best when employed as swarms of thousands of individuals, coordinating their actions without relying on a single leader,” Wood and colleagues wrote in an article for Scientific American. “The hive must be resilient enough so that the group can complete its objectives even if many bees fail.”

Although Wood wrote that CCD and the threat it poses to agriculture were part of the original inspiration for creating a robotic bee, the devices aren’t meant to replace natural pollinators forever. We still need to focus on efforts to save these vital creatures. RoboBees would serve as “stopgap measure while a solution to CCD is implemented,” the project’s website says.

Harvard’s Kevin Ma spoke to Business Insider about the team’s progress in building the bee-size robot since publishing its Science paper last year.

Following is an edited version of that interview.

Business Insider: Where are you a little over a year after it was announced that the first robotic insect took flight?

Kevin Ma: We’ve been continuing on the path to getting the robot to be completely autonomous, meaning it flies without being tethered and without the need for anyone to drive it. We’ve been building a larger version of the robot so that it can can carry the battery, electronic centers, and all the other things necessary for autonomous flight.

BI: Last month, Greenpeace released a short video that imagines a future in which swarms of robotic bees have been deployed to save our planet after the real insects go extinct. It’s a cautionary story rather than one of technological adaptation. What is your reaction to that?

KM: Having a multitude of options to deal with future problems is important. It’s hard to predict what exact solution we would need in the future. Flexibility is key.

BI: Will robot bees eventually be able to operate like honeybee hives to pollinate commercial crops?

KM: Yes. You could replace a hive of honeybees that would otherwise be working on a field of flowers. They would be able to perform the same task of going from flower to flower picking up and putting down pollen. They wouldn’t have to collect nectar like real bees. They would just be transmitting pollen. But to do this the robots first need to fly on their own and fly very well. In theory, they would just have to come back to something to recharge their batteries. But we’re very early on in working this out.

BI: When can we see RoboBees pollinating flowers?

KM: With continued government funding and research we could see this thing functional in 10 to 15 years.

BI: What’s next?

KM:We’re on the eve of the next big development. Something will be published in the next few months. The robot can now now carry more weight. That’s important for the battery and other electronics and sensors.

Once the robot can stay aloft on its own, we would be working on things like allowing it to perform tasks, increasing its battery life, and making it fly faster. Then there are a whole host of issues to work out dealing with wireless communications.

http://www.businessinsider.com/harvard-robobees-closer-to-pollinating-crops-2014-6

IBM is one step closer to mimicking the human brain

September 24, 2016

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Scientists at IBM have claimed a computational breakthrough after imitating large populations of neurons for the first time.

Neurons are electrically excitable cells that process and transmit information in our brains through electrical and chemical signals. These signals are passed over synapses, specialised connections with other cells.

It’s this set-up that inspired scientists at IBM to try and mirror the way the biological brain functions using phase-change materials for memory applications.

Using computers to try to mimic the human brain is something that’s been theorised for decades due to the challenges of recreating the density and power. Now, for the first time, scientists have created their own “randomly spiking” artificial neurons that can store and process data.

“The breakthrough marks a significant step forward in the development of energy-efficient, ultra-dense integrated neuromorphic technologies for applications in cognitive computing,” the scientists said.

The artificial neurons consist of phase-change materials, including germanium antimony telluride, which exhibit two stable states, an amorphous one (without a clearly defined structure) and a crystalline one (with structure). These materials are also the basis of re-writable Blue-ray but in this system the artificial neurons do not store digital information; they are analogue, just like the synapses and neurons in a biological brain.

The beauty of these powerful phase-change-based artificial neurons, which can perform various computational primitives such as data-correlation detection and unsupervised learning at high speeds, is that they use very little energy – just like human brain.

In a demonstration published in the journal Nature Nanotechnology, the team applied a series of electrical pulses to the artificial neurons, which resulted in the progressive crystallisation of the phase-change material, ultimately causing the neuron to fire.

In neuroscience, this function is known as the integrate-and-fire property of biological neurons. This is the foundation for event-based computation and, in principle, is quite similar to how a biological brain triggers a response when an animal touches something hot, for instance.

Tomas Tuma, co-author of the paper, said the breakthrough could help create a new generation of extremely dense neuromorphic computing systems
Tomas Tuma, co-author of the paper, said the breakthrough could help create a new generation of extremely dense neuromorphic computing systems

As part of the study, the researchers organised hundreds of artificial neurons into populations and used them to represent fast and complex signals. When tested, the artificial neurons were able to sustain billions of switching cycles, which would correspond to multiple years of operation at an update frequency of 100Hz.

The energy required for each neuron update was less than five picojoule and the average power less than 120 microwatts — for comparison, 60 million microwatts power a 60 watt light bulb, IBM’s research paper said.

When exploiting this integrate-and-fire property, even a single neuron can be used to detect patterns and discover correlations in real-time streams of event-based data. “This will significantly reduce the area and power consumption as it will be using tiny nanoscale devices that act as neurons,” IBM scientist and author, Dr. Abu Sebastian told WIRED.

This, IBM believes, could be helpful in the further development of internet of things technologies, especially when developing tiny sensors.

“Populations of stochastic phase-change neurons, combined with other nanoscale computational elements such as artificial synapses, could be a key enabler for the creation of a new generation of extremely dense neuromorphic computing systems,” said Tomas Tuma, co-author of the paper.

This could be useful in sensors collecting and analysing volumes of weather data, for instance, said Sebastian, collected at the edge, in remote locations, for faster and more accurate weather forecasts.

The artificial neurons could also detect patterns in financial transactions to find discrepancies or use data from social media to discover new cultural trends in real time. While large populations of these high-speed, low-energy nano-scale neurons could also be used in neuromorphic co-processors with co-located memory and processing units.

http://www.wired.co.uk/article/scientists-mimicking-human-brain-computation