Monthly Archives: July 2017

Examples of eight fruit fly brains with regions highlighted that are significantly correlated with (clockwise from top left) walking, stopping, increased jumping, increased female chasing, increased wing angle, increased wing grooming, increased wing extension, and backing up.

Kristin Branson

By Ryan CrossJul. 13, 2017 , 1:00 PM

Can you imagine watching 20,000 videos, 16 minutes apiece, of fruit flies walking, grooming, and chasing mates? Fortunately, you dont have to, because scientists have designed a computer program that can do it faster. Aided by artificial intelligence, researchers have made 100 billion annotations of behavior from 400,000 flies to create a collection of maps linking fly mannerisms to their corresponding brain regions.

Experts say the work is a significant step toward understanding how both simple and complex behaviors can be tied to specific circuits in the brain. The scale of the study is unprecedented, says Thomas Serre, a computer vision expert and computational neuroscientist at Brown University. This is going to be a huge and valuable tool for the community, adds Bing Zhang, a fly neurobiologist at the University of Missouri in Columbia. I am sure that follow-up studies will show this is a gold mine.

At a mere 100,000 neuronscompared with our 86 billionthe small size of the fly brain makes it a good place to pick apart the inner workings of neurobiology. Yet scientists are still far from being able to understand a flys every move.

To conduct the new research, computer scientist Kristin Branson of the Howard Hughes Medical Institute in Ashburn, Virginia, and colleagues acquired 2204 different genetically modified fruit fly strains (Drosophila melanogaster). Each enables the researchers to control different, but sometimes overlapping, subsets of the brain by simply raising the temperature to activate the neurons.

Then it was off to the Fly Bowl, a shallowly sloped, enclosed arena with a camera positioned directly overhead. The team placed groups of 10 male and 10 female flies inside at a time and captured 30,000 frames of video per 16-minute session. A computer program then tracked the coordinates and wing movements of each fly in the dish. The team did this about eight times for each of the strains, recording more than 20,000 videos. That would be 225 straight days of flies walking around the dish if you watched them all, Branson says.

Next, the team picked 14 easily recognizable behaviors to study, such as walking backward, touching, or attempting to mate with other flies. This required a researcher to manually label about 9000 frames of footage for each action, which was used to train a machine-learning computer program to recognize and label these behaviors on its own. Then the scientists derived 203 statistics describing the behaviors in the collected data, such as how often the flies walked and their average speed. Thanks to the computer vision, they detected differences between the strains too subtle for the human eye to accurately describe, such as when the flies increased their walking pace by a mere 5% or less.

When we started this study we had no idea how often we would see behavioral differences, between the different fly strains, Branson says. Yet it turns out that almost every strain98% in allhad a significant difference in at least one of the behavior statistics measured. And there were plenty of oddballs: Some superjumpy flies hopped 100 times more often than normal; some males chased other flies 20 times more often than others; and some flies practically never stopped moving, whereas a few couch potatoes barely budged.

Then came the mapping. The scientists divided the fly brain into a novel set of 7065 tiny regions and linked them to the behaviors they had observed. The end product, called the Browsable Atlas of Behavior-Anatomy Maps, shows that some common behaviors, such as walking, are broadly correlated with neural circuits all over the brain, the team reports today in Cell. On the other hand, behaviors that are observed much less frequently, such as female flies chasing males, can be pinpointed to tiny regions of the brain, although this study didnt prove that any of these regions were absolutely necessary for those behaviors. We also learned that you can upload an unlimited number of videos on YouTube, Branson says, noting that clips of all 20,000 videos are available online.

Branson hopes the resource will serve as a launching pad for other neurobiologists seeking to manipulate part of the brain or study a specific behavior. For instance, not much is known about female aggression in fruit flies, and the new maps gives leads for which brain regions might be driving these actions.

Because the genetically modified strains are specific to flies, Serre doesnt think the results will be immediately applicable to other species, such as mice, but he still views this as a watershed moment for getting researchers excited about using computer vision in neuroscience. I am usually more tempered in my public comments, but here I was very impressed, he says.

See the rest here:

Artificial intelligence helps scientists map behavior in the fruit fly ... - Science Magazine

July 14, 2017

Indian IT giant Infosys said Friday that artificial intelligence was key to future profits as it bids to satisfy clients' demands for innovative new technologies.

India's multi-billion-dollar IT outsourcing sector has long been one of the country's flagship industries. But as robots and automation grow in popularity its companies are under pressure to reinvent themselves.

"We are revealing new growth with services that we (have been) focusing on for the past couple of years includingAI (artificial intelligence) and cloud computing," said Infosys chief executive Vishal Sikka, announcing a small rise in quarterly profits.

"Going forward, we will count on strong growth coming from these services," added Sikka, who signalled his intent by arriving at the press conference in a driverless golf cart.

Infosys reported an increase of 1.4 percent in consolidated net profit year-on-year for the first quarter, marginally beating analysts' expectations.

Net profit in the three months to June 30 came in at 34.83 billion rupees (540 million), marginally above the 34.36 billion rupees it reported in the same period last year, Infosys said.

India's $150-billion IT sector is facing upheaval in the face of automation and US President Donald Trump's clampdown on visas, with reports of mass redundancies.

Industry body Nasscom recently called on companies to teach employees new skills after claims they had failed to keep up with new technologies.

In April Infosys launched a platform called Nia to "help clients embrace AI".

"Nia continues to be central to all our conversations with clients as we work with them to transform their businesses," the company said in its earnings statement Friday.

Analysts surveyed by Bloomberg had expected profits of 34.3 billion rupees.

Infosys announced revenues of 170.78 billion rupees, marginally up from the 167.8 billion rupees reported for the same period last year.

Its shares rose nearly 3 percent in early trade after the company forecast revenue growth of between 6.5 to 8.5 percent for the current financial year.

Explore further: India's TCS profits fall by 6 percent

2017 AFP

India's largest IT services firm Tata Consultancy Services reported a nearly 6 percent fall in quarterly earnings Thursday owing to a strengthening rupee, the company said.

Indian software giant Infosys cut its annual earnings outlook for the second time in just three months Friday, sending shares down almost three percent, as cautious clients rein in spending.

Indian software giant Infosys Technologies reported a five percent rise in quarterly net profits on Tuesday, aided by a weak rupee and strong demand from the United States.

Infosys shares plunged more than nine percent on the Bombay Stock Exchange Friday after the Indian software giant cut its earnings outlook for the year.

Indian software giant Infosys announced Friday a better-than-expected 13 percent jump in third-quarter net profit, helped by strong demand for services in the United States.

Indian software giant Infosys Technologies saw its shares dip nearly seven percent Friday after it reported a single digit rise in yearly revenues and also missed quarterly profit estimates.

Microsoft has ended support for its Windows 8 smartphones, as the US tech giant focuses on other segments, amid ongoing speculation about its strategy for mobile.

Pilotless aircraft, flying electric vehicles and bespoke air cabins are the future of flight, Airbus said Thursday.

A glove fitted with wearable electronics can translate the American Sign Language alphabet and then wirelessly transmit the text for display on electronic devicesall for less than $100, according to a study published July ...

Dutch researchers unveiled Tuesday a model of what could become within two decades a floating mega-island to be used as a creative solution for accommodating housing, ports, farms or parks.

Microsoft wants to extend broadband services to rural America by turning to a wireless technology that uses the buffer zones separating individual television channels in the airwaves.

What's the point of smart assistants and intelligent electricity meters if people don't use them correctly? In order to cope with the energy transition, we need a combination of digital technologies and smart user behaviour ...

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Read the rest here:

India's Infosys eyes artificial intelligence profits - Phys.Org

Daesh fighters

THE NEWSEUM: Artificial intelligence is coming soon to a battlefield near you with plenty of help from the private sector. Within six months the US military will start using commercial AI algorithms to sort through its masses of intelligence data on the Islamic State.

We will put an algorithm into a combat zone before the end of this calendar year, and the only way to do that is with commercial partners, said Col. Drew Cukor.

Air Force intelligence analysts at work.

Millions of Humans?

How big a deal is this? Dont let the lack of generals stars on Col. Cukors shoulders lead you to underestimate his importance. He heads the Algorithmic Warfare Cross Function Team, personally created by outgoing Deputy Defense Secretary Bob Work to apply AI to sorting the digital deluge of intelligence data.

This isnt a multi-year program to develop the perfect solution: The state of the art is good enough for the government, he saidat the DefenseOne technology conference here this morning. Existing commercial technology can be integrated onto existing government systems.

Were not talking about three million lines of code, Cukor said. Were talking about 75 lines of code placed inside of a larger software (architecture) that already exists for intelligence-gathering.

For decades, the US military has invested in better sensors to gather more intelligence, better networks to transmit that data, and more humans to stare at the information until they find something. Our work force is frankly overwhelmed by the amount of data, Cukor said. The problem, he noted, is staring at things for long periods of time is clearly not what humans were designed for. U.S. analysts cant get to all the data we collect, and we cant calculate how much their bleary eyes miss of what they do look at.

We cant keep throwing people at the problem. At the National Geospatial Intelligence Agency, for example, NGA mission integration director Scott Currie told the conference, if we looked at the proliferation of the new satellites over time, and we continue to do business the way we do, wed have to hire two million more imagery analysts.

Rather than hire the entire population of, say, Houston, Currie continued, we need to move towards services and algorithms and machine learning, (but) We need industrys help to get there because we cannot possibly do it ourselves.

Private Sector Partners

Cukors task force is now spearheading this effort across the Defense Department. Were working with him and his team, said Dale Ormond, principal director for research in the Office of the Secretary of Defense. Were bringing to bear the combined expertise of our laboratory system across the Department of Defense complex.

Were holding a workshop in a couple of weeksto baseline where we are both in industry and with our laboratories, Ormond told the conference. Then were going to have a closed door session (to decide) what are the investments we need to make as a department, what is industry doing (already).

Just as the Pentagon needs the private sector to lead the way, Cukor noted, many promising but struggling start-ups need government funding to succeed. While Tesla, Google, GM, and other investors in self-driving cars are lavishly funding work on artificial vision for collision avoidance, theres a much smaller commercial market for other technologies such as object recognition. All a Google Car needs to know about a vehicle or a building is how to avoid crashing into it. A military AI needs to know whether its a civilian pickup or an ISIS technical with a machinegun in the truck bed, a hospital or a hideout.

An example of the shortcomings of artificial intelligence when it comes to image recognition. (Andrej Karpathy, Li Fei-Fei, Stanford University)

These are not insurmountable problems, Cukor emphasized. The Algorithmic Warfare project is focused on defeating Daesh, he said, not on recognizing every weapon and vehicle in, say, the Russian order of battle. He believes there are only about 38 classes of objects the software will need to distinguish.

Its not easy to program an artificial intelligence to tell objects apart, however. Theres no single Platonic ideal of a terrorist you can upload for the AI to compare real-life imagery against. Instead, modern machine learning techniques feed the AI lots of different real-world data the more the better until it learns by trial and error what features every object of a given type has in common. Its basically the way a toddler learns the difference between a car and a train (protip: count the wheels). This process goes much faster when humans have already labeled what data goes in what category.

These algorithms need large data sets, and were just starting labeling, Cukor said. Its just a matter of how big our labeled data sets can get. Some of this labeling must be done by government personnel, Cukor said; he didnt say why, but presumably this includes the most highly classified material. But much of it is being outsourced to a significant data-labeling company, which he didnt name.

This all adds up to a complex undertaking on a tight timeline something the Pentagon historically does not do well. I wish we could buy AI like we buy lettuce at Safeway, where we can walk in, swipe a credit card, and walk out, Cukor said. There are no shortcuts.

Go here to read the rest:

Artificial Intelligence Will Help Hunt Daesh By December - Breaking Defense