Microsofts autonomous glider soars through the air above Hawthorne, Nev. Once airborne, the glider uses artificial intelligence to find and rely on thermals, or columns of air that rise due to heat, to stay aloft. (Microsoft Photo / John Brecher)

Paying attention to the rise of the machines increasingly means scanning the skies for things other than conventional aircraft or birds. But what if the line between the two begins to blur and autonomous planes can somehow be taught to mimic nature?

Thats the hope of researchers from Microsoft who are using artificial intelligence to keep a sailplane aloft without the help of a motor. A new report on the Redmond, Wash.-based tech giants website details the efforts of scientists launching test flights in a Nevada desert.

The researchers have found that through a complex set of AI algorithms, they can get their 16 1/2-foot, 12 1/2-pound aircraft to soar much like a hawk would, byidentifying things like air temperature and wind direction to locatethermals invisible columns of air that rise due to heat.

Birds do this seamlessly, and all theyre doing is harnessing nature. And they do it with a peanut-sized brain, Ashish Kapoor, a principal researcher at Microsoft, said in the report.

Kapoor said its probably one of the few AI systems operating in the real world thats not only making predictions but also taking action based on those predictions. He said the planes could eventually be used for such things as monitoring crops in rural areas or providing mobile Internet service in hard-to-reach places.

Beyond those practical tasks,Andrey Kolobov, the Microsoft researcher in charge of the projects research and engineering efforts, said the sailplane is charting a course for how intelligent learning itself will evolve over the coming years, calling the project a testbed for intelligent technologies. Its becoming increasingly important for systems of all kinds to make complex decisions based on a number of variables without making costly or dangerous mistakes.

Read more about what Microsoft is learning this summer in the desert via the story from the companys News Center.

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It's a bird! It's a plane! It's Microsoft using artificial intelligence to teach a machine to stay aloft - GeekWire

In the mid-1990s, Douglas Eck worked as a database programmer in Albuquerque, New Mexico, while moonlighting as a musician. After a day spent writing computer code inside a lab run by the Department of Energy, he would take the stage at a local juke joint, playing what he calls punk-influenced bluegrass Johnny Rotten crossed with Johnny Cash. But what he really wanted to do was combine his days and nights, and build machines that could make their own songs. My only goal in life was to mix AI and music, Mr. Eck said.

It was a naive ambition. Enrolling as a graduate student at Indiana University, in Bloomington, not far from where he grew up, he pitched the idea to Douglas Hofstadter, the cognitive scientist who wrote the Pulitzer Prize-winning book on minds and machines, Gdel, Escher, Bach: An Eternal Golden Braid . Mr. Hofstadter turned him down, adamant that even the latest artificial intelligence techniques were much too primitive.

But during the next two decades, working on the fringe of academia, Mr. Eck kept chasing the idea, and eventually, the AI caught up with his ambition.

Last spring, a few years after taking a research job at Google, Mr. Eck pitched the same idea he pitched to Mr. Hofstadter all those years ago. The result is Project Magenta, a team of Google researchers who are teaching machines to create not only their own music but also to make so many other forms of art, including sketches, videos and jokes.

With its empire of smartphones, apps and internet services, Google is in the business of communication, and Mr. Eck sees Magenta as a natural extension of this work. Its about creating new ways for people to communicate, he said during a recent interview inside the small two-story building here that serves as headquarters for Google AI research.

Growing effort

The project is part of a growing effort to generate art through a set of AI techniques that have only recently come of age. Called deep neural networks, these complex mathematical systems allow machines to learn specific behaviour by analysing vast amounts of data.

By looking for common patterns in millions of bicycle photos, for instance, a neural network can learn to recognise a bike. This is how Facebook identifies faces in online photos, how Android phones recognise commands spoken into phones, and how Microsoft Skype translates one language into another. But these complex systems can also create art. By analysing a set of songs, for instance, they can learn to build similar sounds.

As Mr. Eck says, these systems are at least approaching the point still many, many years away when a machine can instantly build a new Beatles song or perhaps trillions of new Beatles songs, each sounding a lot like the music the Beatles themselves recorded, but also a little different.

Tools for artists

But that end game is not what he is after. There are so many other paths to explore beyond mere mimicry. The ultimate idea is not to replace artists but to give them tools that allow them to create in entirely new ways.

In the 1990s, at that juke joint in New Mexico, Mr. Eck combined Johnny Rotten and Johnny Cash. Now, he is building a software that does much the same thing. Using neural networks, he and his team are cross-breeding sounds from very different instruments say, a bassoon and a clavichord creating instruments capable of producing sounds no one has ever heard.

Much as a neural network can learn to identify a cat by analysing hundreds of cat photos, it can learn the musical characteristics of a bassoon by analysing hundreds of notes. It creates a mathematical representation, or vector, that identifies a bassoon. So, Mr. Eck and his team have fed notes from hundreds of instruments into a neural network, building a vector for each one.

Now, simply by moving a button across a screen, they can combine these vectors to create new instruments. One may be 47% bassoon and 53% clavichord. Another might switch the percentages. And so on.

For centuries, orchestral conductors have layered sounds from instruments atop one other. But this is different. Rather than layering sounds, Mr. Eck and his team combine them to form something that did not exist before, creating new ways that artists can work.NYT

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How Artificial Intelligence is reshaping art and music - The Hindu

The AI (artificial intelligence) revolution is well and truly upon us, and we are at a significant watershed moment in our lives where AI could become the new electricity pervasive and touching every aspect of our life. While many industries including healthcare, education, retail and banks have already started adopting AI in key business aspects, there are also new business models which are predicated on AI.

With the global market of AI expected to grow at 36% annually, reaching a valuation of $3 trillion by 2025 from $126 bn in 2015, new age disruption is not only redefining the way traditional businesses are run, but is also unfolding as a new factor of production.

However, the fear of what might happen once AI evolves into artificial general intelligence which can perform any intellectual task that a human can do has now taken centre stage with the ongoing debate between two tech titans Elon Musk and Mark Zuckerberg. Similarly, Microsoft co-founder Bill Gates had also voiced his views that in a few years, AI would have evolved enough to warrant wide attention, while Facebook has ended up shutting down one of its AI projects as chatbots had developed their own language (unintelligible to humans) to communicate.

Beyond this, the common citizen wants to know if she should be worried about AI taking away her job? This calls for broader thinking, including the evolution of industry protocols, while making sure that the public is ready for these futuristic advancements.

Will AI move my cheese?

The emergence of AI has seen criticism because of the probability that it could replace human jobs by automation. However, as we see the shift of AI from R&D stage to various real-life business prototypes, it seems evident that goal of most AI applications is to augment human abilities through hybrid business models.

According to McKinsey, AI would raise global labour productivity by 0.8% to 1.4% a year between now and 2065. I believe that both policy makers and corporates must recognise AIs potential to empower the workforce and invest in creating training programmes/workshops to help the labour force adapt to these newer models.

For instance, Ocado, the UK online supermarket has embedded robotics at the core of warehouse management. Robots steer thousands of product-filled bins to human packers just in time to fill shopping bags which are then sent to delivery vans whose drivers use AI applications to pick the best route based on traffic conditions and weather.

Technology will create more new jobs than it eliminates

We must learn from the history of the industrial and technological revolutions over the last 500 years that jobs eliminated in one sector have been replaced by newer jobs requiring refreshed skill-sets. As a corollary, countries such as Japan, Korea or Germany, which have the highest levels of automation, should have seen large scale unemployment over the past 4-5 decades. This is not necessarily the case.

Having said that, in the near future, every routine operational task is certainly likely to become digitised and AI could be running the back-office of most businesses. Over the next few decades, many middle skill jobs are also likely to be eliminated. However, AI is unlikely to replace jobs which require human to human interaction. Consequently, fundamental human thinking skills such as entrepreneurship, strategic thinking, social leadership, connected salesmanship, philosophy, and empathy, among others, would be in even greater demand.

Further, till a point of singularity is reached, AI will not be able to service or program on its own leading to new, high-skilled jobs for technicians and computing experts.

Lets be prepared

Globally, policymakers and corporations will need to significantly revamp the education system to address technology gaps.

In India, this represents an enormous opportunity for policymakers to make better informed decisions, tackle some of the toughest socio-economic challenges, and address the woeful shortage of qualified doctors, teachers etc.

We need to immediately plan for state and nation-wide university hubs, and MOOCs (massive open online courses) built on the framework of DICE (design, innovation, creativity led entrepreneurship). Curricula should be focussed on developing basic skills in STEM (science, technology , engineering and mathematics) fields, coupled with a new emphasis on creativity, critical and strategic thinking. Adaptive and individualised learning systems need to be established to help students at different levels work collaboratively amongst themselves as well as with AI in the classroom.

The National Skills Development Corporation will need to evolve into National Future Skills Development, as we as a civil society prepare to bring the future into the present!

Rana Kapoor is MD and CEO, YES Bank; and Chairman, YES Global Institute

The views expressed are personal

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The artificial Intelligence wave is upon us. We better be prepared - Hindustan Times

Like mobile technology, cloud computing, big data and IoT before it, artificial intelligence may just be the next big thing that channel partners should have on their radars. But as with any new technology that comes along, partners need to ensure they have the right business skill sets for system implementations.

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The hype about AI is rising, although the jury is still out on whether the artificial intelligence market will be a great opportunity for the channel, said Seth Robinson, senior director of technology analysis at CompTIA.

"AI is not going to be on its own something that is all that tangible that you can grasp and pursue," he said.

A sure sign of the growing interest is recent vendor product releases, noted Steve White, program vice president of channels and alliances at IDC. "When we spoke to channel and alliance folks 18 months ago, it was IoT, and now it's AI. It's the new golden child," he said.

Once vendors like Microsoft, Google, Salesforce and Cisco have announced offerings it creates greater access and interest for the technology, "and they're not investing unless they see opportunity," White said. "That's definitely why the channel should be interested."

Another appeal of the artificial intelligence market is that the technology is applicable for use in most industries, observers said.

That said, AI is still "very early in overall adoption cycle" and people are mainly curious about the technology and are in the exploratory phase right now, Robinson said.

He believes AI platforms will be complicated and there needs to be a deeper conversation with customers about the business needs for deploying the technology. That conversation should be about what AI is and how it fits into their business, Robinson said. "We haven't seen much readiness to move into that strategic conversation yet."

Without a clear understanding of the business objectives, companies may not utilize the technology's features, such as machine learning and cognitive computing, and then they obviously won't reap the benefits, he said. For example, if a company spends extra on help desk software with AI baked in but uses it in a standard way without utilizing AI, "you haven't moved the needle," he cautioned. "So, channel firms have to be careful about overselling without helping companies transition to new processes and workflows and the best usage of these things that are available today."

Probably the best and earliest example of AI in the enterprise is IBM's Watson technology, Robinson said. Within the channel, he said, there has been a lot of buzz about CrushBank, a spinoff of a managed service provider (MSP) that built an IT help desk application on top of Watson. "They're building a help desk application that utilizes Watson, so if you want to get CrushBank's product or are working with them, you'll get this new app with AI baked into it," he said. This is not an example of reselling or installing AI, but rather, incorporating the technology into apps, "which a lot of MSPs and VARs [value-added reseller] aren't thinking about,'' Robinson said.

In CrushBank's case, they are helping customers change workflow processes to utilize help desk features in a more efficient way, he said. "And that gets out of the wheelhouse of channel firms," since the channel historically has been built on management of technology, Robinson added.

"AI is a very natural way to supplement the tasks and work we do every day to support our clients," CrushBank co-founder and CTO David Tan said."I think the need has been there, but the growth in technology and platforms has made it more pronounced, and the technology to power the solutions is finally becoming mature."

CrushBank sells its platform to other MSPs, Tan said. The next step the channel needs to focus on is to really integrate technology into a business, which is at the core of what digital transformation is all about, he said. AI, according to Tan, can be particularly effective at making that happen.

Another example of a company using AI to change business processes is Actionable Science. The company has created AI-powered bots to help medium- and large-sized businesses improve productivity, enhance customer experiences, increase employee satisfaction and reduce costs, said Manish Sharma, co-founder and head of business development.

The bots address a range of tasks for sales, servicing, IT help desk, HR help desk and other functions. Actionable Science's advanced bots have natural language conversations, evolve using machine learning and execute tasks by leveraging robotic process automation, Sharma said.

The company has about a dozen partners so far, he said, adding that the artificial intelligence market "has got to be one of the top priorities for channel partners that want to stay relevant and grow their business in the future." They can do that by developing "an expertise in one or several specific applications," Sharma said.

The skills he believes a partner needs for AI work include a combination of process analytics, user experience and "requirements management that is very specific to AI."

This [technology] is going to be a lot more consulting-heavy, so you have to have those professional consulting folks with a depth of knowledge around [AI]. Steve Whiteprogram vice president of channels and alliances, IDC

White concurred that if a partner is already doing work in business intelligence or analytics, AI "would seem like a fairly obvious add-on that they should be looking at" because it takes the products they're offering to their customers to the next level.

"At the end of the day, AI is even smarter to leverage that platform you've already built,'' and expand upon it as an opportunity for growth, White said.

Partners also need to be able to build a consulting practice around AI, White believes. "This [technology] is going to be a lot more consulting-heavy, so you have to have those professional consulting folks with a depth of knowledge around [AI]. Like most tech trends, we see the partners who act quicker, funnily enough, are the ones who are more successful."

Learn about robotic process automation

How to get started in IoT managed services

Opinion: Why BI and AI are a natural fit

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Artificial intelligence market: Weighing the IT channel's role - TechTarget

Elon Musk's recent remark on Twitter that artificial intelligence (AI) is more dangerous than North Korea is based on his bedrock belief in the power of thought. But this philosophy has a dark side.

If you believe that a good idea can take over the world and if you conjecture that computers can or will have ideas, then you have to consider the possibility that computers may one day take over the world. This logic has taken root in Musk's mind and, as someone who turns ideas into action for a living, he wants to make sure you get on board too. But hes wrong, and you shouldnt believe his apocalyptic warnings.

Here's the story Musk wants you to know but hasn't been able to boil down to a single tweet. By dint of clever ideas, hard work, and significant investment, computers are getting faster and more capable. In the last few years, some famously hard computational problems have been mastered, including identifying objects in images, recognizing the words that people say, and outsmarting human champions in games like Go. If machine learning researchers can create programs that can replace captioners, transcriptionists, and board game masters, maybe it won't be long before they can replace themselves. And, once computer programs are in the business of redesigning themselves, each time they make themselves better, they make themselves better at making themselves better.

The resulting intelligence explosion would leave computers in a position of power, where they, not humans, control our future. Their objectives, even if benign when the machines were young, could be threatening to our very existence in the hands of an intellect dwarfing our own. That's why Musk thinks this issue is so much bigger than war with North Korea. The loss of a handful of major cities wouldn't be permanent, whereas human extinction by a system seeking to improve its own capabilities by turning us into computational components in its mega-brainthat would be forever.

Musks comparison, however, grossly overestimates the likelihood of an intelligence explosion. His primary mistake is in extrapolating from recent successes of machine learning the eventual development of general intelligence. But machine learning is not as dangerous as it might look on the surface.

For example, you may see a machine perform a task that appears to be superhuman and immediately be impressed. When people learn to understand speech or play games, they do so in the context of the full range of human experiences. Thus when you see something that can respond to questions or beat you soundly in a board game, it is not unreasonable to infer that it also possesses a range of other human capacities. But that's not how these systems work.

In a nutshell, here's the methodology that has been successful for building advanced systems of late: First, people decide what problem they want to solve and they express it in the form of a piece of code called an objective functiona way for the system to score itself on the task. They then assemble perhaps millions of examples of precisely the kind of behavior they want their system to exhibit. After that they design the structure of their AI system and tune it to maximize the objective function through a combination of human insight and powerful optimization algorithms.

At the end of this process, they get a system that, often, can exhibit superhuman performance. But the performance is on the particular task that was selected at the beginning. If you want the system to do something else, you probably will need to start the whole process over from scratch. Moreover, the game of life does not have a clear objective functioncurrent methodologies are not suited to creating a broadly intelligent machine.

Someday we may inhabit a world with intelligent machines. But we will develop together and will have a billion decisions to make that shape how that world develops. We shouldn't let our fears prevent us from moving forward technologically.

Michael L. Littman is a professor of computer science at Brown University and co-director of Brown's Humanity Centered Robotics Initiative.

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Elon Musk Is Wrong Again. AI Isn't More Dangerous Than North Korea. - Fortune

Messenging app 'Messenger' launched a range of new artificial intelligence (AI) features in Australia on Wednesday.

The AI, called 'M', works almost like a prompting service, where it recognises words and phrases used in a conversation and then suggests relevant content and actions based on the chat between the two users.

For example, if you're speaking to someone on their birthday, 'M' will recognise either through a phrase used or their Messenger profile when their birthday is and then prompt you to send a birthday message.

Similarly, if you are chatting about making plans or struggling to come to a group decision about something, the AI will suggest you make a plan or start a group poll respectively. If you are chatting in a one-on-one conversation, and one person rises the idea of making a call, 'M' will prompt you to start a video or voice chat.

Other features include stickers for commonly used phrases including 'thankyou' or 'bye-bye' and a prompt to share your location with someone if phrases like 'where are you?' and 'see you soon' are used. Messenger also launched a content saving option that encourages you to save videos, Facebook posts and pages from your conversations to look at later.

If you tire of the notifications and suggestions from Messenger, it's easy to opt-out of the AI technology by adjusting your Messenger settings. It's also possible to dismiss a suggestion made by 'M' if you feel it is irrelevant.

The 'M' artificial intelligence technology was first launched in the U.S. in April and is also currently available in Mexico and Spain. Canada, South Africa and the U.K. will gain assess to the technology at the same time as all of us here in Australia.

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Messenger Launches New Artificial Intelligence Features - Huffington Post Australia

For some, the sight of the buffer circle is enough to bring on spasms of existential angst. When that spinning circle of death appears, the digital world cracks, its illusory sense of control slips from your sweaty palm, and you are reminded, however briefly, that you are not the master of this realm, and you have no real idea how the machine you are using works. Its also very annoying if youre trying to show a video to someone.

Researchers at MIT may have come up with a way to stave of techno-existential panic for good, thanks to a new artificial intelligence system that can keep video steaming buttery smooth.

Buffering happens because video streaming occurs in chunks, with your device downloading sequential portions of a file that are then stitched together. This means you can start watching the video before downloading the entire thing, but if connection wavers you might finish one chunk before the next has been fully downloaded.

Sites like YouTube use Adaptive Bitrate (ABR) algorithms to work out what resolution a video should display at. In a nutshell, these allow the system to maintain the flow of images be measuring a networks speed and lowering the resolution appropriately, or by working to maintain a sufficient buffer at the tip of the video. The issue is that neither of these techniques on their own can prevent annoying pauses in a clips if the network has a sudden drop in traffic flow say, if youre in a particularly crowded area, or if youre moving in and out of tunnels.

MIT's Computer Science and Artificial Intelligence Lab (CSAIL) AI, dubbed Pensive, takes these algorithms, but uses a neural network to intelligently work out when a system should flip between one and the other. The AI was trained on a months worth of video content, and was given reward and penalty conditions, to push it to calculate the most effective times to switch between ABR algorithms.

This system is adjustable, meaning it can be tweaked depending on what a content provider might want to prioritise such as consistent image quality or smoother playback. "Our system is flexible for whatever you want to optimise it for," commented MIT professor Mohammad Alizadeh in a statement. "You could even imagine a user personalising their own streaming experience based on whether they want to prioritise rebuffering versus resolution."

While the death of the buffer symbol might be cause for celebration, the researchers also point to the benefits the AI system could have for virtual reality potentially making it much easier for people to stream high-resolution VR games and films. This is really just the first step in seeing what we can do, noted Alizadeh.

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MIT's new artificial intelligence could kill buffering - Alphr