New AI-Based Search Engines are a “Game Changer” for Science Research

November 14, 2016

ee203bd1-b7e0-4864-a75641c2719b53a8By Nicola Jones, Nature magazine

A free AI-based scholarly search engine that aims to outdo Google Scholar is expanding its corpus of papers to cover some 10 million research articles in computer science and neuroscience, its creators announced on 11 November. Since its launch last year, it has been joined by several other AI-based academic search engines, most notably a relaunched effort from computing giant Microsoft.

Semantic Scholar, from the non-profit Allen Institute for Artificial Intelligence (AI2) in Seattle, Washington, unveiled its new format at the Society for Neuroscience annual meeting in San Diego. Some scientists who were given an early view of the site are impressed. “This is a game changer,” says Andrew Huberman, a neurobiologist at Stanford University, California. “It leads you through what is otherwise a pretty dense jungle of information.”

The search engine first launched in November 2015, promising to sort and rank academic papers using a more sophisticated understanding of their content and context. The popular Google Scholar has access to about 200 million documents and can scan articles that are behind paywalls, but it searches merely by keywords. By contrast, Semantic Scholar can, for example, assess which citations to a paper are most meaningful, and rank papers by how quickly citations are rising—a measure of how ‘hot’ they are.

When first launched, Semantic Scholar was restricted to 3 million papers in the field of computer science. Thanks in part to a collaboration with AI2’s sister organization, the Allen Institute for Brain Science, the site has now added millions more papers and new filters catering specifically for neurology and medicine; these filters enable searches based, for example, on which part of the brain part of the brain or cell type a paper investigates, which model organisms were studied and what methodologies were used. Next year, AI2 aims to index all of PubMed and expand to all the medical sciences, says chief executive Oren Etzioni.

“The one I still use the most is Google Scholar,” says Jose Manuel Gómez-Pérez, who works on semantic searching for the software company Expert System in Madrid. “But there is a lot of potential here.”

Microsoft’s revival

Semantic Scholar is not the only AI-based search engine around, however. Computing giant Microsoft quietly released its own AI scholarly search tool, Microsoft Academic, to the public this May, replacing its predecessor, Microsoft Academic Search, which the company stopped adding to in 2012.

Microsoft’s academic search algorithms and data are available for researchers through an application programming interface (API) and the Open Academic Society, a partnership between Microsoft Research, AI2 and others. “The more people working on this the better,” says Kuansan Wang, who is in charge of Microsoft’s effort. He says that Semantic Scholar is going deeper into natural-language processing—that is, understanding the meaning of full sentences in papers and queries—but that Microsoft’s tool, which is powered by the semantic search capabilities of the firm’s web-search engine Bing, covers more ground, with 160 million publications.

Like Semantic Scholar, Microsoft Academic provides useful (if less extensive) filters, including by author, journal or field of study. And it compiles a leaderboard of most-influential scientists in each subdiscipline. These are the people with the most ‘important’ publications in the field, judged by a recursive algorithm (freely available) that judges papers as important if they are cited by other important papers. The top neuroscientist for the past six months, according to Microsoft Academic, is Clifford Jack of the Mayo Clinic, in Rochester, Minnesota.

Other scholars say that they are impressed by Microsoft’s effort. The search engine is getting close to combining the advantages of Google Scholar’s massive scope with the more-structured results of subscription bibliometric databases such as Scopus and the Web of Science, says Anne-Wil Harzing, who studies science metrics at Middlesex University, UK, and has analysed the new product. “The Microsoft Academic phoenix is undeniably growing wings,” she says. Microsoft Research says it is working on a personalizable version—where users can sign in so that Microsoft can bring applicable new papers to their attention or notify them of citations to their own work—by early next year.

Other companies and academic institutions are also developing AI-driven software to delve more deeply into content found online. The Max Planck Institute for Informatics, based in Saarbrücken, Germany, for example, is developing an engine called DeepLife specifically for the health and life sciences. “These are research prototypes rather than sustainable long-term efforts,” says Etzioni.

In the long term, AI2 aims to create a system that will answer science questions, propose new experimental designs or throw up useful hypotheses. “In 20 years’ time, AI will be able to read—and more importantly, understand—scientific text,” Etzioni says.

This article is reproduced with permission and was first published on November 11, 2016.

https://www.scientificamerican.com/article/new-ai-based-search-engines-are-a-ldquo-game-changer-rdquo-for-science-research/

Why the World Is Better Than You Think in 10 Powerful Charts

November 14, 2016

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By

When I published Abundance: The Future is Better Than You Think in February 2012, I included about 80 charts in the back of the book showing very strong evidence that the world is getting better.

Over the last five years, this trend has continued and accelerated.

This blog includes additional “Evidence for Abundance” that you can share with friends and family to change their mindset.

We truly are living in the most exciting time to be alive.

By the way, if you have additional ‘Evidence for Abundance’ (charts, data, etc.) that you’ve encountered, please email them to me at data@diamandis.com.

Why This Is Important

Before I share the new “data” with you, it’s essential that you understand why this matters.

We live in a world where we are constantly bombarded by negative news from every angle. If you turn on CNN (what I call the Crisis News Network), you’ll predominantly hear about death, terrorism, airplane crashes, bombings, financial crisis and political scandal.

I think of the news as a drug pusher, and negative news as their drug.

There’s a reason for this.

We humans are wired to pay 10x more attention to negative news than positive news.

Being able to rapidly notice and pay attention to negative news (like a predator or a dangerous fire) was an evolutionary advantage to keep you alive on the savannas of Africa millions of years ago.

Today, we still pay more attention to negative news, and the news media knows this. They take advantage of it to drive our eyeballs to their advertisers. Typically, good news networks fail as businesses.

It’s not that the news media is lying — it’s just not a balanced view of what’s going on in the world.

And because your mindset matters a lot, my purpose of my work and this post is to share with you the data supporting the positive side of the equation and to give you insight to some fundamental truths about where humanity really is going…

The truth is, driven by advances in exponential technologies, things are getting much better around the world at an accelerating rate.

NOTE: This is not to say that there aren’t major issues we still face, like climate crisis, religious radicalism, terrorism, and so on. It’s just that we forget and romanticize the world in centuries past — and life back then was short and brutal.

My personal mission, and that of XPRIZE and Singularity University, is to help build a “bridge to abundance”: a world in which we are able to meet the basic needs of every man, woman and child.

So, now, let’s look at 10 new charts.

More Evidence for Abundance

Below are 10 powerful charts illustrating the positive developments we’ve made in recent years.

1. Living in Absolute Poverty (1981-2011)

Declining rates of absolute poverty (Source: Our World in Data, Max Roser)

Declining rates of absolute poverty (Source: Our World in Data, Max Roser)

Absolute poverty is defined as living on less than $1.25/day. Over the last 30 years, the share of the global population living in absolute poverty has declined from 53% to under 17%.

While there is still room for improvement (especially in sub-Saharan Africa and South Asia), the quality of life in every region above has been steadily improving and will continue to do so. Over the next 20 years, we have the ability to extinguish absolute poverty on Earth.

2. Child Labor Is on the Decline (2000-2020)

Child Labor on the decline (Source: International Labor Organization)

Child Labor on the decline (Source: International Labor Organization)

This chart depicts the actual and projected changes in the number of children (in millions) in hazardous work conditions and performing child labor between 2000 and 2020.

As you can see, in the last 16 years, the number of children in these conditions has been reduced by more than 50%. As we head to a world of low-cost robotics, where such machines can operate far faster, far cheaper and around the clock, the basic rationale for child labor will completely disappear, and it will drop to zero.

3. Income Spent on Food

Income spent on food (Source: USDA, Economic Research Service, Food Expenditure Series)

Income spent on food (Source: USDA, Economic Research Service, Food Expenditure Series)

This chart shows the percent per capita of disposable income spent on food in the U.S. from 1960 to 2012.

If you focus on the blue line, ‘Food at home,’ you can see that over the last 50 years, the percent of our disposable income spent on food has dropped by more than 50 percent, from 14% to less than 6%.

This is largely a function of better food production technology, distribution processes and policies that have reduced the cost of food. We’re demonetizing food rapidly.

4. Infant Mortality Rates

Infant Mortality Rate (Source: Devpolicy, UN Interagency Group for Child Mortality Est. 2013)

Infant Mortality Rate (Source: Devpolicy, UN Interagency Group for Child Mortality Est. 2013)

This chart depicts global under-five-years-old mortality rates between 1990 and 2012 based on the number of deaths per 1,000 live births.

In the last 25 years, under-five mortality rates have dropped by 50%. Infant mortality rates and neonatal mortality rates have also dropped significantly.

And this is just in the last 25 years. If you looked at the last 100 years, which I talk about in Abundance, the improvements have been staggering.

5. Annual Cases of Guinea Worm

Guinea worm cases (Source: GiveWell, Carter Center)

Guinea worm cases (Source: GiveWell, Carter Center)

Guinea worm is a nasty parasite that used to affect over 3.5 million people only 30 years ago. Today, thanks to advances in medical technologies, research and therapeutics, the parasite has almost been eradicated. In 2008, there were just 4,647 cases.

I’m sharing the chart above because it represents humanity’s growing ability to address and cure diseases that have plagued us for ages. Expect that through technologies such as gene drive/CRISPR-Cas9 and other genomic technologies, we will rapidly begin to eliminate dozens or hundreds of similar plagues.

6. Teen Birth Rates in the United States

Teen birth rates (Source: Vox, Centers for Disease Control)

Teen birth rates (Source: Vox, Centers for Disease Control)

The chart above shows the dramatic decline in the number of teen (15 to 19 years old) birth rates in the United States since 1950. At its peak, 89.1 out of 1,000 teenage women were giving birth. Today, it’s dropped under 29 out of 1,000.

This is largely a function of the population becoming better educated, the cost of birth control being reduced and becoming more widely available, and cultural shifts in the United States.

7. Homicide Rates in Western Europe

Homicide rates in Europe (Source: Our World in Data, Max Roser & Manuel Eisner)

Homicide rates in Europe (Source: Our World in Data, Max Roser & Manuel Eisner)

The chart above shows the number of homicides per 100,000 people per year in five Western European regions from 1300 to 2010.

As you can see, Western Europe used to be a very dangerous place to live. Over the last 700+ years, the number of homicides per 100,000 people has decreased to almost zero.

It is important to look back this far (700 years) because we humans lose perspective and tend to romanticize the past, but forget how violent life truly was in, say, the Middle Ages, or even just a couple of hundred years ago.

We have made dramatic and positive changes. On an evolutionary time scale, 700 years is NOTHING, and our progress as a species is impressive.

8. U.S. Violent Crime Rates, 1973 – 2010

U.S. violent crime rates (Source: Gallup, Bureau of Justice Statistics)

U.S. violent crime rates (Source: Gallup, Bureau of Justice Statistics)

In light of the recent terrorist shooting in Orlando, and the school shootings in years past, it is sometimes easy to lose perspective.

The truth is, in aggregate, we’ve made significant progress in reducing violent crimes in the United States in the last 50 years.

As recent as the early 80s and mid-90s, there were over 50 violent crime victims per 1,000 individuals. Recently, this number has dropped threefold to 15 victims per 1,000 people.

We continue to make our country (and the world) a safer place to live.

9. Average Years of Education, 1820-2003

Average years of education (Source: Our World in Data, Max Roser)

Average years of education (Source: Our World in Data, Max Roser)

I love this chart. In the last 200 years, the average number of ‘years of education’ received by people worldwide has increased dramatically.

In the U.S. in 1820, the average person received less than 2 years of education. These days, it’s closer to 21 years of education, a 10X improvement.

We are rapidly continuing the demonetization, dematerialization and democratization of education. Today, I’m very proud of the $15 million Global Learning XPRIZE as a major step in that direction.

Within the next 20 years, the best possible education on Earth will be delivered by AI for free — and the quality will be the same for the son or daughter of a billionaire as it is for the son or daughter of the poorest parents on the planet.

10. Global Literacy Rates

Global literacy rates (Source: Our World in Data, Max Roser)

Global literacy rates (Source: Our World in Data, Max Roser)

Along those same lines, the extraordinary chart above shows how global literacy rates have increased from around 10% to close to 100% in the last 500 years.

This is both a function of technology democratizing access to education, as well as abundance giving us the freedom of time to learn.

Education and literacy is a core to my abundance thesis — a better-educated world raises all tides.

Again, if you have other great examples of abundance (charts and data), please send them to me at data@diamandis.com.

We live in the most exciting time to be alive! Enjoy it.

Why the World Is Better Than You Think in 10 Powerful Charts

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.”

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/

What artificial intelligence will look like in 2030

November 14, 2016

ai

Artificial intelligence (AI) has already transformed our lives — from the autonomous cars on the roads to the robotic vacuums and smart thermostats in our homes. Over the next 15 years, AI technologies will continue to make inroads in nearly every area of our lives, from education to entertainment, health care to security.

The question is, are we ready? Do we have the answers to the legal and ethical quandaries that will certainly arise from the increasing integration of AI into our daily lives? Are we even asking the right questions?

Now, a panel of academics and industry thinkers has looked ahead to 2030 to forecast how advances in AI might affect life in a typical North American city and spark discussion about how to ensure the safe, fair, and beneficial development of these rapidly developing technologies.

“Artificial Intelligence and Life in 2030” is the first product of the One Hundred Year Study on Artificial Intelligence (AI100), an ongoing project hosted by Stanford University to inform debate and provide guidance on the ethical development of smart software, sensors, and machines. Every five years for the next 100 years, the AI100 project will release a report that evaluates the status of AI technologies and their potential impact on the world.

 AI Landscape: Global Quarterly Financing History

Image: CB Insights

 

“Now is the time to consider the design, ethical, and policy challenges that AI technologies raise,” said Grosz. “If we tackle these issues now and take them seriously, we will have systems that are better designed in the future and more appropriate policies to guide their use.”

“We believe specialized AI applications will become both increasingly common and more useful by 2030, improving our economy and quality of life,” said Peter Stone, a computer scientist at the University of Texas, Austin, and chair of the report. “But this technology will also create profound challenges, affecting jobs and incomes and other issues that we should begin addressing now to ensure that the benefits of AI are broadly shared.”

The report investigates eight areas of human activity in which AI technologies are already affecting urban life and will be even more pervasive by 2030: transportation, home/service robots, health care, education, entertainment, low-resource communities, public safety and security, employment, and the workplace.

Some of the biggest challenges in the next 15 years will be creating safe and reliable hardware for autonomous cars and health care robots; gaining public trust for AI systems, especially in low-resource communities; and overcoming fears that the technology will marginalize humans in the workplace.

Issues of liability and accountability also arise with questions such as: Who is responsible when a self-driven car crashes or an intelligent medical device fails? How can we prevent AI applications from being used for racial discrimination or financial cheating?

The report doesn’t offer solutions but rather is intended to start a conversation between scientists, ethicists, policymakers, industry leaders, and the general public.

Grosz said she hopes the AI 100 report “initiates a century-long conversation about ways AI-enhanced technologies might be shaped to improve life and societies.”

https://www.weforum.org/agenda/2016/09/what-artificial-intelligence-will-look-like-in-2030

Read the report: https://ai100.stanford.edu/2016-report

Will the coming robot nanny era turn us into technophiles?

November 14, 2016

A vector illustration of a robot ironing clothes

Robots intrigue us. We all like them. But most of us don’t love them. That may dramatically change over the next 10 years as the “robot nanny” makes its way into our households.

In as little time as a decade, affordable robots that can bottle-feed babies, change diapers and put a child to sleep might be here. The human-machine bond that a new generation of kids grows up with may be unbreakable. We may end up literally loving our machines almost like we do our mothers and fathers.

I’ve already seen some of this bonding in action. I have a four-foot interactive Meccanoid robot aboard my Immortality Bus, which I’ve occasionally used for my presidential campaign. The robot can do about 1,000 functions, including basic interaction with people, like talking, answering questions and making wisecracks. When my five-year-old rides with me on the bus, she adores it. After being introduced to it, she obsessively wanted to watch Inspector Gadget videos and read books on robots.

My two daughters (the other one is two years old) have always been near technology, and both were able to successfully navigate YouTube watching videos on iPhones by the time they were 12 months old. Yet, while my kids love the iPhone, and they want to use it regularly, it doesn’t bond them to technology in a maternal sense like the Meccanoid robot does. More importantly, the smartphone doesn’t bond them to technology in an anthropomorphic sense — where one gives technology human attributes, like personalities.

My kids instinctively know the iPhone is a tool. But Meccanoid is a friend. If you kick the robot, leave it in the rain or lock it away in the closet, my kids will freak out. To them, the robot is personal — and the love is real.

If some of this reminds you of Rosie the Robot — the cleaning, cooking nanny robot from the Jetsons — you’re not alone. Humans will soon regularly engage with machines as fellow companions in life, giving psychologists, anthropologists and Congress new ideas to consider. There is already chatter all across the internet in the transhumanist community about humans wanting the right to marry machines — and all that goes with that. In fact, in the Transhumanist Bill of Rights I delivered to Washington, DC, we explicitly aim to give future conscious beings personhood — as well as other rights covered by the 1948-adopted United Nations Universal Declaration of Human Rights.

Despite the thorniness of some of the issues between humans and robots, the reason we are entering this robot age is because of one simple fact: functionality. Robots will make our lives far easier. In fact, the robot nanny is a prime example: It will be adored by parents — and likely much more so than the human nannies who are known to call in sick, show up to work late and, on occasion, sue their employers when they hurt themselves on the job. Robot nannies will replace real nannies like the automobile replaced the horse and cart — allowing parents much new free time and opportunity to pursue careers.

One major factor going for the development of robot nannies is their cost effectiveness. I’ve been either watching my kids or hiring nannies for the last five years. About $200,000 later (which is what 8-hour weekday childcare costs in San Francisco for five years), it’s safe to say a robot nanny is not going to cost as much as I’ve spent. And once my kids are old enough and no longer need immediate supervision, I’ll be left with the robot to sell or give to a family in need.

But essential questions remain: Will some robots be allowed to watch kids when parents go out for the night or off to work — and other robots not? Who will make that determination? The parent? The manufacturer? The government?

Will robots that can perform CPR, put out fires, squish poisonous spiders and perform the Heimlich maneuver on a choking child be authorized while others are not? Will robots that can detect smoke and carbon monoxide, where others can’t, make the “nanny-worthy” grade?

And then come the questions ethicists and programmers are already facing with driverless cars. If an autonomous vehicle is forced into a choice to hit a young family of five or an old man, what does it choose? Nanny robots may one day be programmed with similar instructions and values.

But what if a robot nanny is watching twins, and both start choking at the same time? Which child will it choose to help first? Will programmers allow parents to program which child should be helped first?

The questions are endless. I suspect, like the U.S. Department of Transportation’s National Highway Traffic Safety Administration’s Federal Motor Vehicle Safety Standards and Regulations, a robot equivalent will have to be established.

It’s been years since the American household has gotten a new fixture that all households must have. One of the last major ones was the computer — and now nearly 85 percent of American households have one. I suspect nanny robots will be one of the next commonplace items we have in our homes. And our love for them will grow as they influence and play an integral part of the next generation’s upbringing.

Will the coming robot nanny era turn us into technophiles?

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

Video

Dave Brain: What a planet needs to sustain life

September 24, 2016

“Venus is too hot, Mars is too cold, and Earth is just right,” says planetary scientist Dave Brain. But why? In this pleasantly humorous talk, Brain explores the fascinating science behind what it takes for a planet to host life — and why humanity may just be in the right place at the right time when it comes to the timeline of life-sustaining planets.

The ‘impossible’ EM Drive is about to be tested in space

September 24, 2016

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An actual EM Drive is about to be launched into space for the first time, so scientists can finally figure out – once and for all – if it really is possible for a rocket engine to generate thrust without any kind of exhaust or propellant.

Built by American inventor and chemical engineer, Guido Fetta, the EM Drive is as controversial as it gets, because while certain experiments have suggested that such an engine could work, it also goes against one of the most fundamental laws of physics we have.

As Newton’s Third Law states, “To each action there’s an equal and opposite reaction,” and many physicists say the EM Drive categorically violates that law.

This is because in order for a thruster to gain momentum in a certain direction, it has to expel some kind of propellent or exhaust in the opposite direction.

But the EM Drive simply goes in one direction with no propellant, and thus violates the law of conservation of momentum, which Newton derived from his Third Law.

And not only that, but it could produce enough thrust to blast humans to Mars in just 70 days.

As Fiona MacDonald put it back in June, space enthusiasts love to get excited about the EM Drive, because if it works, it has the potential to remove major barriers in our need to explore the Solar System and beyond.

But just as many are sick of hearing about it, because, on paper at least, it doesn’t work within the laws of physics.

Invented by British scientist Roger Shawyer back in 1999, the EM Drive – short for electromagnetic propulsion drive – purportedly works like this.

It uses electromagnetic waves as ‘fuel’, creating thrust by bouncing microwave photons back and forth inside a cone-shaped closed metal cavity. This causes the ‘pointy end’ of the EM Drive to accelerate in the opposite direction that the drive is going.

“To put it simply, electricity converts into microwaves within the cavity that push against the inside of the device, causing the thruster to accelerate in the opposite direction,” Mary-Ann Russon explains over at The International Business Times.

Since its invention, the EM drive has shown no signs of quitting, in test after test. Last year, trials by NASA scientists at the Eagleworks lab revealed “anomalous thrust signals”, and an independent researcher in Germany conceded that the propulsion system, somehow, does indeed produce thrust.

Fast-forward to now, and there are rumours that the NASA Eagleworks paper we reported on in June has finally passed the peer-review process, and is expected to be published by the American Institute of Aeronautics and Astronautics’ Journal of Propulsion and Power.

If the rumours by José Rodal from MIT are true – and let’s be clear, they’re still just rumours at this point – it could be huge.

As Brendan Hesse explains for Digital Trends:

“This is an important step for the EM Drive as it adds legitimacy to the technology and the tests done thus far, opening the door for other groups to replicate the tests. This will also allow other groups to devote more resources to uncovering why and how it works, and how to iterate on the drive to make it a viable form of propulsion.

So, while a single peer-reviewed paper isn’t going to suddenly equip the human race with interplanetary travel, it’s the first step toward eventually realising that possible future.”

And on top of all of that, we’re about to see an actual EM Drive be blasted into space.

Guido Fetta is CEO of Cannae Inc, and the inventor of the Cannae Drive – a rocket engine that’s based on Roger Shawyer’s original EM Drive design. Last month, he announced that he would launch this thruster on a 6U CubeSat – a type of miniaturised satellite.

David Hambling reports for Popular Mechanics that roughly one-quarter of this shoebox-sized satellite will be taken up by the Cannae Drive, and they’ll stay in orbit for at least six months: “The longer it stays in orbit, the more the satellite will show that it must be producing thrust without propellant.”

No launch date has been set just yet, but it could happen in as soon as six months’ time.

As Hambling points out, Fetta better hurry, because a team of engineers in China, and Shawyer himself, are both also working on their own launchable EM Drives, so someone’s going to get there first, and we seriously cannot wait to see what will happen.

http://www.sciencealert.com/the-impossible-em-drive-is-about-to-be-tested-in-space

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

Mark Zuckerberg and Priscilla Chan’s $3 billion effort aims to rid world of major diseases by end of century

September 24, 2016

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Facebook co-founder Mark Zuckerberg and his wife, Priscilla Chan, on Wednesday announced a $3 billion effort to accelerate scientific research with the wildly ambitious goal of “curing all disease in our children’s lifetime.”

The many components of the initiative include creating universal technology “tools” based on both traditional science and engineering on which all researchers can build, including a map of all cell types, a way to continuously monitor blood for early signs of illness, and a chip that can diagnose all diseases (or at least many of them). The money will also help fund what they referred to as 10 to 15 “virtual institutes” that will bring together investigators from around the world to focus on individual diseases or other goals — an idea that has the potential to upend biomedical science.

Being a scientist in academia today can often be a solitary endeavor as the system is set up to encourage colleagues to keep data exclusive in the hopes that this strategy helps them be more competitive at getting publications and grants. But as more Silicon Valley entrepreneurs like Zuckerberg are seeking to make their mark in the biological sciences, they are emphasizing the power of collaboration and openness.

A centerpiece of the new effort, called Chan Zuckerberg Science, involves creating a “Biohub” at the University of California at San Francisco (UCSF) Mission Bay campus that will bring together scientists from Stanford, the University of California at Berkeley and UCSF.

Zuckerberg and Chan, among the world’s 10 wealthiest couples, with a net worth of $55.2 billion, emphasized that their timeline is long — by the end of the century.

“We have to be patient. This is hard stuff,” Zuckerberg said.

Chan said, “That doesn’t mean no one will ever get sick, but it means our children and their children should get sick a lot less.”

Many of themes articulated by Zuckerberg and Chan on Wednesday in San Francisco echo ideas furthered by other technology philanthropists who have donated substantial amounts of money to medical science. Sean Parker, a Napster co-founder, earlier this year set up a multi-center, $250 million effort to bring together top researchers from around the country to focus on immunotherapy for cancer. Microsoft’s Paul Allen has already invested $100 million in a cell-biology institute to try to create models of the fundamental building blocks of life.

https://www.washingtonpost.com/news/to-your-health/wp/2016/09/21/mark-zuckerberg-and-priscilla-chans-3-billion-scientific-effort-aims-to-rid-world-of-major-diseases-by-end-of-century/