Category Archives: Singularity

Theres a classic scene in almost every police procedural: a weathered detective stands staring at a collection of photos pinned to a wall. Thin, red yarn traces the connections between the different players. Somethings clearly missing.

In a sudden flash of inspiration, the final link snaps into the detectives mind. He dashes off, frantically yelling to his partner that he finally figured out whodunnit.

Although were not all seasoned crime solvers, under the hood our brains share one remarkable skill: the ability to reason about how one thing relates to another.

This type of logical acrobaticsdubbed relational reasoningsilently operates behind even the most banal situations: when is it safe to cross the street with multiple oncoming cars? Which entre and wines go best together? How many attractions are around your hotel?

To a human, reasoning about relationships feels intuitive and simple. To an AI, its unfathomably hard.

That may be set to change. Last week, the researchers at DeepMind, the mysterious deep learning company that gave us AlphaGo, published a paper detailing a new algorithm that endows machines with a spark of human ingenuity.

The plug-and-play relation networks (RNs) are bits of code that forces an AI to explicitly think about relations between a group of mental representationsstatic objects, moving people, or even abstract ideas.

Like a powerful Turbo charger, when combined with existing machine learning tools, RNs gave the AIs a logic boostso much so that they outperformed humans on several image-based reasoning tasks.

As a fundamental part of human intelligence, relational reasoning acts like a multitool to transfer know-how from one domain to another, says Dr. Sam Gershman, a computational neuroscientist at Harvard who was not involved in the study.

And while RNs only capture a snippet of human reasoning, its a step in the right direction towards generally intelligent machines with the flexibility and efficiency of human thought.

Not all AIs are created equal. Like students specializing in either arts or sciences, the two main types of AIssymbolic and statisticaleach have their own quirks.

Symbolic AIs use a powerful set of math operations to reason about relations between things, so they do deal with logic. The problem is that theyre constrained by predetermined rules. In other words, theyre terrible at learning on the fly, and any small variation in the task can throw them off tracknot exactly ideal to tackle the challenges of our ever-changing world.

In contrast, statistical AIs (better known as machine learning) rely on millions of examples to find patterns in a dataset. The poster child of statistical AIs is deep learning, the driving force behind AlphaGo and various face-tagging services that has taken the world by storm.

As revolutionary as they are, however, deep neural networks are still terrible at finding complex relations in a data structure, especially when they dont have enough training examples.

DeepMind combines the best of both worlds with their new algorithm: an artificial neural network capable of pattern recognition and reasoning about those patterns.

Artificial neural networks are loosely based on their biological counterparts in our brains. Rather than operating on pre-set rules, they learn to discover patterns by tweaking the connections between their neuronslike fine-tuning a guitar.

Each neural network has their own structure to support one task: labeling images, translating languages or playing GO and Atari games. DeepMinds RN is similar in this way: it has a unique structure that primes it to compare every possible pair of objects within a system.

Were explicitly forcing the network to discover the relationships that exist between the objects, says study author Timothy Lillicrap. The capacity to compute relations is baked into the RN architecture, he adds.

In a series of experiments, the team carefully tested the RNs capabilities. First, they trained the algorithm on CLEVRa database of images composed of simple objects designed to explicitly explore an AIs ability to perform several types of reasoning, such as counting, comparing or querying.

In each image, the algorithm had to answer questions about the relations between objects in a scene. For example, What shape is the small object that is in front of the yellow matte thing and behind the gray sphere? or What number of objects are blocks that are in front of the large red cube or green balls?

What seems like a no-brainer to humans is actually a two-step process. To get it right, you need to first identify the objects and characterize their properties. Then, you have to put them all into a broader context of the image to build hypotheses about how they relate to each other.

But the RN didnt go at it alone. To tackle this task, the authors combined it with two other neural networks: one for image processing, and one for interpreting the questions. After rounds and rounds of training, the algorithm network answered correctly 96 percent of the time, more than the 92 percent humans scored. Traditional neural networks without the RN module faltered far behind, netting around 63 percent.

Next, DeepMind switched gears and tested the RN on a word-based task to gauge its versatility. The network was exposed to short stories like Sandra picked up the football, and Sandra went to the office, which led to the question Where is the football?

The RN-augmented network performed just as well as state-of-the-art models at 95 percent on most of the tasks, but especially excelled at questions requiring inference The dog is a black Deerhound. The Deerhounds name is Sirius. What color is Sirius?scoring twice as high as conventional networks.

Finally, the algorithm parsed a simulation of 10 bouncing balls, with some randomly selected to pair up, as if tied by invisible springs or rigid constraints. By analyzing the relative positions and speed of the balls, the RN identified more than 90 percent of the connected pairs.

The beauty of RN lies in its simplicity. The core of the algorithm is a single equation, meaning it can be tagged onto existing network structures to give them a boost. RN-enhanced networks could one day automatically analyze surveillance footage, study social networks, or guide self-driving cars through complex intersections with many moving components.

That said, RN only analyzes pair-wise connections. To really understand ever more complex relational structures, theyll have to compare triplets, quadruplets or (more meta) pairs-of-pairs. And while it deals with moving objects to an extent, it doesnt predict the future trajectory of objectsa crucial part of relational reasoning.

There is a lot of work needed to solve richer real-world data sets, says study author Adam Santoro.

DeepMind has already made strides on this problem. In another paper, they described a Visual Interaction Network (VIN) that predicts the future of moving objects based on their properties and physical surroundingsa sort of physics engine, like the one built into our brains.

In a variety of systems, VIN accurately predicted what will happen to moving objects hundreds of steps into the future, wrote the DeepMind team in a blog post.

Both of the studies show that by carving the world into objects and their relations, we could give AIs the ability to generalize. They learn to form new combinations of objects and reason about scenes that superficially might look very different but have underlying common relations, explain the authors.

And while thats not the only aspect of intelligence, its certainly a necessary one.

Excerpt from:

Machine Reasoning Gets a Boost With This Simple New Algorithm - Singularity Hub

Datacentrix, a provider of high performing and secure ICT solutions, is tackling the topic of the reality of singularity, investigating the future of technology and the transformation that will result from its integration into every aspect of our lives, at its second annual Showcase event.

Showcase 2017 will take place at Montecasino in Johannesburg on Thursday, 27 July.

Technology is becoming increasingly integrated into our everyday lives and even our bodies disrupting civilisation and life as we know it, explains Rudie Raath, Datacentrix Chief Digital Strategist.

Consider more recent technological breakthroughs such as 3D printed organs, online connected pacemakers and insulin pumps that feed real-time information back to medical staff, and the assimilation of data analytics and algorithms with human decision making.

In some cases, such as within the financial services and insurance sectors, artificial intelligence has already become a major disruptive force, taking on certain functions, based on parameters and inputs that we provide think banking chatbots, robo-advisors, and AI within claims processing for example.

Developments like these leave most of us with one question though, is this the first phase of singularity? Raath asks.

Featuring speakers such as venture capitalist, former banker and Singularity University alum and contributor, Dr Michael Jordaan, Datacentrix vision is for Showcase 2017 to help local businesses embrace the connected world, prompt the right questions on singularity, and ultimately equip companies to bridge the gap between business and technology to survive the digital age.

Showcase 2017 will explore the future course that business will be navigating as a result of the integration of technology into our lives and the impact of disruptive technologies on the way we work. Other considerations will involve the responsibility that companies have to their people and communities where they operate in an all-digital, all-connected world, adds Raath. Well also help to map technology solutions that will support tomorrows data-driven, application-powered, hyper-connected business, providing not only better business outcomes, but excellent user experiences.

Showcase 2017 builds on the success of the inaugural 2016 event that brought together 28 local and international technology partners and attracted more than 1,200 delegates. It also resulted in Datacentrix achieving Veritas Technologies award for the best marketing event within the EMEA (Europe, Middle East, and Africa) region last year.

Showcase 2017s flexible format; powerful opening plenary; 20-minute breakaway sessions; comprehensive showroom, and interactive lunchtime panel discussion with industry experts mediated by tech-guru, Toby Shapshak are just some of the highlights that delegates can look forward to.

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Datacentrix talks singularity at second annual showcase event - BizNis Africa (press release)

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The Japanese Company Betting Billions to Prepare for the Singularity - WIRED

We live in a world of accelerating change. New industries are constantly being born and old ones are becoming obsolete. A report by the World Economic Forum reveals that almost 65 percent of the jobs elementary school students will be doing in the future do not even exist yet. Both the workforce and our knowledge base are rapidly evolving.

Combined with the effects of technological automation on the workforce, this leaves us with a crucial question: What are the skills future generations will need?

Education expert Tony Wagner has spent a lifetime trying to answer this very question. Through investigating the education sector, interviewing industry leaders and studying the global workforce at large, Wagner has identified seven survival skills of the future. These are skills and mindsets young people absolutely need in order to meet their full potential.

We spend so much time teaching students how to answer questions that we often neglect to teach them how to ask them. Asking questionsand asking good onesis a foundation of critical thinking. Before you can solve a problem, you must be able to critically analyze and question what is causing it. This is why critical thinking and problem solving are coupled together.

Wagner notes the workforce today is organized very differently than it was a few years ago. What we are seeing are diverse teams working on specific problems, as opposed to specific specialties. Your manager doesnt have all the answers and solutionsyou have to work to find them.

Above all, this skill set builds the very foundation of innovation. We have to have the ability to question the status quo and criticize it before we can innovate and prescribe an alternative.

One of the major trends today is the rise of the contingent workforce. In the next five years, non-permanent and remote workers are expected to make up 40 percent of the average companys total workforce. We are even seeing a greater percentage of full-time employees working on the cloud. Multinational corporations are having their teams of employees collaborate at different offices across the planet.

Technology has allowed work and collaboration to transcend geographical boundaries, and thats truly exciting. However, collaboration across digital networks and with individuals from radically different backgrounds is something our youth needs to be prepared for. According to a New Horizons report on education, we should see an increasing focus on global online collaboration, where digital tools are used to support interactions around curricular objectives and promote intercultural understanding.

Within these contexts, leadership among a team is no longer about commanding with top-down authority, but rather about leading by influence. Ultimately, as Wagner points out, Its about how citizens make change today in their local communitiesby trying to influence diverse groups and then creating alliances of groups who work together toward a common goal.

We live in a VUCA (Volatile, uncertain, complex and ambiguous) world. Hence, Its important to be able to adapt and re-define ones strategy.

In their book, Critical Thinking: How to Prepare Students for a Rapidly Changing World, Richard Paul & Dillion Beach note how traditionally our education and work mindset has been designed for routine and fixed procedure. We learned how to do something once, and then we did it over and over. Learning meant becoming habituated, they write. But what is it to learn to continually re-learn? To be comfortable with perpetual re-learning?

In the post-industrial era, the impact of technology has meant we have to be agile and adaptive to unpredictable consequences of disruption. We may have to learn skills and mindsets on demand and set aside ones that are no longer required.

Traditionally, initiative has been something students show in spite of or in addition to their schoolwork. For most students, developing a sense of initiative and entrepreneurial skills has often been part of their extracurricular activities. With an emphasis on short-term tests and knowledge, most curricula have not been designed to inspire doers and innovators.

Are we teaching our youth to lead? Are we encouraging them to take initiative? Are we empowering them to solve global challenges? Throughout his research, Wagner has found that even in corporate settings, business leaders are struggling to find employees who consistently seek out new opportunities, ideas and strategies for improvement.

A study by the Partnership for 21st Century Skills showed that about 89 percent of employer respondents report high school graduate entrants as deficient in communication.

Clear communication isnt just a matter of proper use of language and grammar. In many ways, communicating clearly is an extension of thinking clearly. Can you present your argument persuasively? Can you inspire others with passion? Can you concisely capture the highlights of what you are trying to say? Can you promote yourself or a product?

Billionaire entrepreneur Richard Branson has famously said Communication is the most important skill any leader can possess. Like many, he has noted it is a skill that can be learned and consequently used to open many opportunities.

We now live in the information age. Every day we create 2.5 quintillion bytes of data. As this infographic shows, this would fill 10 million Blu-ray disks.

While our access to information has dramatically increased, so has our access to misinformation. While navigating the digital world, very few students have been taught how to assess the source and evaluate the content of the information they access. Moreover, this information is continuously evolving as we update our knowledge base faster than ever before.

Furthermore, in the age of fake news, an active and informed citizen will have to be able to assess information from many different sources through a critical lens.

Curiosity is a powerful driver of new knowledge and innovation. It is by channeling a child-like sense of awe and wonder about the world that we can truly imagine something even better. It takes powerful imagination to envision breakthroughs and then go about executing them. It is the reason Albert Einstein famously said, Imagination is more important than knowledge.

We consistently spoon-feed students with information instead of empowering them to ask questions and seek answers. Inquisitiveness and thinking outside the box need to be treated with the same level of importance the school system gives to physics or math.

There is a stark contrast between these seven survival skills of the future and the focus of education today. Instead of teaching students to answer questions, we should teach them to ask them. Instead of preparing them for college, we should prepare them for life.

Beyond creating better employees, we must aim to create better leaders and innovators. Doing so will not only radically transform the future of education and the workforce, it will also transform the world we live in.

Stock Media provided by ra2studio / Pond5 Deep Dream Generator

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7 Critical Skills For the Jobs of the Future - Singularity Hub

As advertisers wake up to the capabilities that artificial intelligence (AI) can offer them in their roles, not least in helping them understand consumer behavior, this year's Cannes Lions Festival of Creativity featured the leading mind in such a field.

Futurist and inventor, Ray Kurzweil, is the mind behind the theory of the singularity taking place by 2045, the point when humans multiply our effective intelligence a billion fold by merging with the intelligence we have created. He is attending the festival this year with PHD in order to appear on stage and film for a new documentary the media agency is making. It is also using the presence of Kurzweil to launch a book on the topic, appropriately named 'Merge the closing gap between technology and us.

"It's an optimistic group that welcomes the future as I do," says Kurzweil when asked what he thinks of the festival. He is sitting quietly on a large deep chair in the middle of the grand lobby of the JW Marriott on Le Croisette having flown in just that morning from the US. He is clearly tired when The Drum greets him but soon warms up while discussing the topic he has spent his professional life leading the transformational power of technology on people and language.

Asked about his views on the advancement of advertising and communications as a result of technological progress, Kurzweil immediately turns to how useful advertising can be now as it becomes more focused through understanding online user interests.

"Advertising is really blending in with other forms of communication and that is something that people welcome because it is topics that they have an interest in," he says.

"Brands are very important because we need to trust information. Not everything on the internet can be relied on so we use brands as a way of knowing what is reliable," he explains, before later adding that AI can help ensure people are treated as individuals rather than a mass audience being served the same message in unison.

"People will resent wasting their time with messages that don't agree with them, that are in areas they are not interested in, so AI is going to tell people they are going to like a movie or a song and we appreciate that because it's usually right and brands have to be associated with good quality information. You can't sell something that people are not going to like," he says.

He cites advice his aunt, who was a senior vice president of Doyle Dane and Bernbach (DDB) in New York gave, that trying to advertise a brand that people aren't going to like is the quickest way to kill it: "You have to be selling something that is worthwhile and then people will appreciate the message and it's more and more important that people can trust in an era that is filled with misinformation."

He goes on to claim that "language is at the heart of human intelligence" and says that the understanding of human language cannot be faked when asked what technological developments are exciting him currently.

"To really understand language you really have to understand human intelligence and knowledge at human levels. That's what I work on and that is what I think is most exciting but AI keeps doing things that people thought were only the province of human intelligence. Every time AI does something we say 'that's not really AI' and it has been called 'the set of problems we haven't solved yet' but that is getting smaller and smaller."

He repeatedly states that the dawn of AI is not "an alien invasion from Mars" but a result of human ingenuity and believes that technology will ultimately "go inside our bodies and brains" to aid health and and that the neo-cortex of the human brain will be linked directly to the cloud, taking man's evolution a step further as technology assists brains to access more knowledge than ever before.

"We are going to connect our neo-cortex to the cloud and add again to the hierarchy and make ourselves smarter and create capabilities we can't even imagine today. Try explaining language or music or humor to a primate that doesn't understand those concepts. We'll create new types of knowledge that we can't understand today when we increase our neo-cortex wirelessly to the cloud. That's my vision of the future that's a 2030 scenario," he confides.

"If you read my predictions going back to the 80s and 90s, I am always surprised when things I have talked about come true," he later admits. "Although I write about them I still find them remarkable. People very quickly get used to them. It's always been that way," he says, before using the smartphone as an example of something that was mass adopted five years ago and quickly change society.

And it's the accuracy of such predictions that have made Kurzweil's name. For all his writings, he is still best known for his prediction of the Singularity, and despite the continued increase in the speed of technological advancements, he says he still stands by his assertion that the artificial intelligence will be able to pass a Turing test 12 years from now, and that the singularity will still happen in 2045 despite the continued debate of others in the field.

"There are more and more developments that support that view. My view has stayed the same, the consensus view of experts and the general public is moving towards me," he says.

He continues: "There is a growing group of people who think I'm too conservative but I see no reason to change my view. AI is doing more and more things that people said it would never do... by 2029 they will do anything humans can do...

"We make these machines to be smarter and we are already smarter. The idea that we are going to merge with this technology is not radical. We are doing it right now and the typical dystopian futurist movie is the AI versus the brave band of humans fighting for control of humanity. We don't have one single AI in the world today, we have, on last count around 3 billion. Phones are AIs. They have really empowered the individual. They are getting more and more capable and they will be in 8 billion hands within a few years and they are getting more and more integrated with us and they are starting to go into our bodies and brains and it starts with extreme cases like Parkinson's patients but that will be ubiquitous in the 2030s. Whether they are inside our bodies or not, they are already extending our capability."

Finally, when asked about the most accurate depiction of AI he has seen in film, he says that Spike Jonze's Oscar-winning 'Her' is his favourite, but that he felt the ending was a 'cop out' and admits that despite the Terminator being one of the most famous depictions of AI on screen, he has yet to meet its famous director and writer James Cameron.

"He did express an interest in an interview for a series he's doing but I haven't met him yet," he responds casually.

This century, if Kurzweil is correct, humanity is set to evolve and reach a new level of intelligence and expand its horizons to new heights with the aid of intelligence. How marketers will deal with that challenge when they are already struggling to deal with other technological developments appearing at a rapid rate will be a fascinating leap for the industry to deal with. How do you advertise to robots anyway?

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Ray Kurzweil, father of the singularity, on brand trust, how AI can help advertisers & technology aiding human evolution - The Drum

Flying car concepts have been around nearly as long as their earthbound cousins, but no one has yet made them a commercial success. MIT engineers think weve been coming at the problem from the wrong direction; rather than putting wings on cars, we should be helping drones to drive.

The team from the universitys Computer Science and Artificial Intelligence Laboratory (CSAIL) added wheels to a fleet of eight mini-quadcopters and tested driving and flying them around a tiny toy town made out of cardboard and fabric.

Adding the ability to drive reduced the distance the drone could fly by 14 percent compared to a wheel-less version. But while driving was slower, the drone could travel 150 percent further than when flying. The result is a vehicle that combines the speed and mobility of flying with the energy-efficiency of driving.

CSAIL director Daniela Rus told MIT News their work suggested that when looking to create flying cars, it might make more sense to build on years of research into drones rather than trying to simply put wings on cars.

Historically, flying car concepts have looked like someone took apart a Cessna light aircraft and a family sedan, mixed all the parts up, and bolted them back together again. Not everyone has abandoned this approachtwo of the most developed flying car designs from Terrafugia and AeroMobil are cars with folding wings that need an airstrip to take off.

But flying car concepts are looking increasingly drone-like these days, with multiple small rotors, electric propulsion and vertical take-off abilities. Take the eHang 184autonomous aerial vehicle being developed in China, theKitty Hawk all-electric aircraft backed by Google founder Larry Page, which is little more than a quadcopter with a seat, the AirQuadOne designed by UK consortium Neva Aerospace, or Lilium Aviations Jet.

The attraction is obvious. Electric-powered drones are more compact, maneuverable, and environmentally friendly, making them suitable for urban environments.

Most of these vehicles are not quite the same as those proposed by the MIT engineers, as theyre pure flying machines. But a recent Airbus concept builds on the same principle that the future of urban mobility is vehicles that can both fly and drive. Its Pop.Up design is a two-passenger pod that can either be clipped to a set of wheels or hang under a quadcopter.

Importantly, they envisage their creation being autonomous in both flight and driving modes. And theyre not the only ones who think the future of flying cars is driverless. Uber has committed to developing a network of autonomous air taxis within a decade. This spring, Dubai announced it would launch a pilotless passenger drone serviceusing the Ehang 184as early as next month (July).

While integrating fully-fledged autonomous flying cars into urban environments will be far more complex, the study by Rus and her colleagues provides a good starting point for the kind of 3D route-planning and collision avoidance capabilities this would require.

The team developed multi-robot path planning algorithms that were able to control all eight drones as they flew and drove around their mock up city, while also making sure they didnt crash into each other and avoided no-fly zones.

This work provides an algorithmic solution for large-scale, mixed-mode transportation and shows its applicability to real-world problems, Jingjin Yu, a computer science professor at Rutgers University who was not involved in the research, told MIT News.

This vision of a driverless future for flying cars might be a bit of a disappointment for those whod envisaged themselves one day piloting their own hover car just like George Jetson. But autonomy and Uber-like ride-hailing business models are likely to be attractive, as they offer potential solutions to three of the biggest hurdles drone-like passenger vehicles face.

Firstly, it makes the vehicles accessible to anyone by removing the need to learn how to safely pilot an aircraft. Secondly, battery life still limits most electric vehicles to flight times measured in minutes. For personal vehicles this could be frustrating, but if youre just hopping in a driverless air taxi for a five minute trip across town its unlikely to become apparent to you.

Operators of the service simply need to make sure they have a big enough fleet to ensure a charged vehicle is never too far away, or theyll need a way to swap out batteries easily, such as the one suggested by the makers of the Volocopter electric helicopter.

Finally, there has already been significant progress in developing technology and regulations needed to integrate autonomous drones into our airspace that future driverless flying cars can most likely piggyback off of.

Safety requirements will inevitably be more stringent, but adding more predictable and controllable autonomous drones to the skies is likely to be more attractive to regulators than trying to license and police thousands of new amateur pilots.

Image Credit: Lilium

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Forget Flying Cars, the Future Is Driving Drones - Singularity Hub

Green energy is a popular topic right now, with many countries signing on to the Paris Climate Accord and planning to move away from fossil fuels toward renewable energy.

While most countries are working toward establishing solar and wind power farms, some countries like Canada are looking toward the creation ofcompressed air storage plantsfor power storage and generation.

How can compressed air change the way countries use and store green energy?

Compressing air in porous caves can serve as a backup form of power that can be tapped when the demand for power is high. Essentially, the compressed air is stored in caves of porous basalt rock when power demand is low. When more power is needed, the air is heated and piped through turbines to generate power.

This is a great way for countries that already rely on wind power to hedge their bets, so to speakto ensure that there is a sufficient supply of power even if the wind doesnt blow as much as they would like.

But aproblem with this type of energy storage is that it relies on natural gas to heat the air. As of 2016, natural gas use made up more than one third of the US energy industry, and while it is more efficient than coal power, it is still a non-renewable resource.

The biggest difference between traditional compressed air storage plants and the new 7 MWh plant approved to be built in Goderich, Ontario, is the way the air is heated before being piped through the turbines. As mentioned, standard plants rely on natural gas to heat the air used to generate power. The new Goderich plant, on the other hand, uses a heat exchange system.

This heat exchange system stores the heat that is generated when the air is initially stored. When the air needs to be heated to generate power, that heat is simply released, making this an emission-free form of energy storage.

This is a step away from the traditional energy storage markets. Lithium-ion batteries like the ones in the Tesla Home battery system currently hold the majority of the market. Most of these batteries, though, are designed for small, single-home applications. Compressed air storage, on the other hand, can generate power for entire communities or power grids when the need arises.

Compressed air storage plants are a growing field, especially with the global focus on green energy. Anywhere that has a sufficient layer of basalt stone can be used for compressed air storage, making it an option for markets around the world.

The market for the equipment just to treat the air that is being compressed is expected to grow by more than six percent, reaching $11.2 billion by 2025.

Treating the compressed air is important to protect the compression equipment. The ambient air can contain contaminants that could damage or clog the equipment and pollute the compressed air.

With the path toward green energy growing clearer every year, construction projects like the new emission-free compressed air plant in Canada are the first steps toward a green planet, and toward getting humans away from fossil fuels and greenhouse gases.

While construction hasnt started yet on the Canadian plant, it will be fascinating to see how much power this emission-free plant can generate once its up and running, not to mention the amount of power that will eventually come from additional compressed air storage plants in the coming years.

Stock Media provided by noppasinw / Pond5

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Canada Is Building a 7 Megawatt-Hour Compressed Air Energy Storage Plant - Singularity Hub

At some point, youve probably heard or read someone refer to the singularity. A singularity can be many things, but the singularity usually refers to the idea of a Technological singularity. There are many ways to define this concept, but its basically the idea that humanity will inevitably create an artificial intelligence greater than itself, which will trigger exponential and unforeseen changes to the world as we know and experience it.

While the concept has been around for over a hundred years, we can more clearly see this inevitability today than before. Even if you dont subscribe to the idea, its hard not to see how technology continues to reshape our lives. We live among real, living Cyborgs. Several large companies are competing to be the first to bring self-driving technology to market. Amazons warehouses are so autonomous that they require just a minute of human labor to ship a package, from taking it off the shelf, packaging it, and sending it to the correct mail truck. Oh, and then theres their drone delivery ambitions.

Okay, cool, but how does this relate to baseball? The best example of technology taking over in baseball is MLBs Statcast technology. If you read this blog, you probably like baseball enough to at least be aware of Statcast. For the uninitiated, MLBs glossary describes Statcast as a state-of-the-art tracking technology...capable of measuring previously unquantifiable aspects of the game...using a series of high-resolution optical cameras along with radar equipment to track the location and movements of the ball and every player on the field, resulting in an unparalleled amount of information covering everything from the pitcher to the batter to base-runners and defensive players.

I have often used the Statcast data hosted at BaseballSavant.com to analyze hitters. That was thanks to Statcast being able to track both the Exit Velocity (the speed at which the ball leaves the bat) and Launch Angle (the vertical angle at which the ball leaves the bat) of most batted balls. From those two basic stats, a lot can be built on top. For instance, for each combination of the two, you can find its average production, whether in terms of hit probability, HR%, wOBA, BABIP or any other metric you can think of.

Theres a lot of other neat things you can figure out though. For instance, Joe Trezza wrote about how the Cards pitching staff has worked hard on holding runners on better. Carlos Martinez, Adam Wainwright, and Mike Leake have all cut a half a foot or more off the average lead a runner takes on them. Theyve also worked on being quicker to the plate, another aspect Statcast tracks.

After soon-to-be-former Cub and noted clubhouse cancer Miguel Montero blamed his pitcher to the media after allowing 7 stolen bases to the Nationals, Travis Sawchik used Statcast to investigate. The technology tracks each catchers pop-time (the time from receiving the ball to releasing it on an attempted steal), as well each pitchers time to home.

Montero has the worst average pop-time in the majors this year at 2.12 seconds, and the average is about 2 seconds flat. A very experienced scout can certainly detect that extra tenth of a second, but he still cant quantify it without a stopwatch, diligence, and attending several games to get a good feel for the players average. Hed have a good sense of average, but hed need to keep excellent records to find out what that extra tenth of a second means in terms of throwing out runners.

There are several other Statcast stats listed in the glossary linked above, some of the more notable being Spin Rate (the speed at which the ball rotates, something our own Joe Schwartz has often used in his pitching analysis), Route Efficiency (how close to optimal a defenders route was to the ball), and Catch Probability, which uses a balls hang-time and the distance a defender had to cover to get there to generate the average chance that a ball is caught.

One new feature is Sprint Speed, released this past week. The point of this stat is to find the average max-effort speed of a runner. In a truly shocking result, Billy Hamilton is leading in Sprint Speed in 2017. They also have a leaderboard, and a really cool graphic to go with it:

for a more interesting version of this picture, check out the leaderboard linked above, which has the same image but it tells you who each dot is when you hover your cursor above it.

Despite coming out just days ago, our fearless leader Craig Edwards has already tested the stats relationship with base-running and defensive value in the current year, and fellow Cardinal blogger Zach Gifford has already looked at the predictive powers of the stat, as well as where the Cardinals regulars rank.

The point is, these all are things that are done by scouts. How hard the ball comes off the bat, the average lead a runner can get away with, a catchers pop-time, a pitchers time to the plate, an outfielders speed and efficiency can all be assessed by observing a player. But can they see, remember, and properly aggregate every single time a player showcases those tools? Of course not. Technology is already way better at this than humans. Scouts dont judge a pitchers velocity by sight. They use a radar gun. And they dont even need to do that at the MLB level. They can just look at their Pitch F/x numbers.

At the same time, its upending the way we look at stats. When examining changes in a players contact quality, we used to look at a breakdown of his Hard%, Medium%, and Soft%, but now we have average Exit Velocity and Barrel%. We used to look at a players Ground ball/Line Drive/Fly ball profile, now we look at their Launch Angle distribution. We use to have Speed Score, but now we have Sprint Speed. The best public defensive metrics - Ultimate Zone Rating (UZR) and Defensive Runs Saved (DRS) - look set to be dethroned by the fruits of Catch Probability and whatever else the braintrust working on Statcast dream up.

Theres also the fact that Statcast still has more potential to spare. Remember above I mentioned that Statcast tracks the ball and every player. Noticeably absent is the bat. Statcast offers a lot of improvement in terms of measuring performance at the plate, but tracking the bat opens up another world of possibilities.

I often think of a hypothetical application, which in my head I call Bat F/x. Perhaps a more suitable name would be Batcast. Anyway, the idea is that you could gain a lot of information from tracking the bat that is currently still something only scouts can observe. Swing velocity and Swing plane are two more obvious examples. These can be measured with special bats as a method of practice and training, but Im talking about an in-game solution that evaluates performance.

Another neat one I would want to see would be a bat heatmap. That is, a heatmap of the half of the bat facing the pitcher at the point of impact. Then it could be color-coded based on where the hitters bat most often came in contact with the ball.

Perhaps Statcast just isnt advanced enough to do that yet, I dont know the technology well enough to say. Other technology is able to though, and it has some very obvious use cases for evaluating talent. Humans have already hit a wall when it comes to what they can reasonably do to evaluate talent by eye. Technology offers endless possibilities.

All the way back in 2004, when sabermetrics was gaining steam but still wasnt dominating front offices like they are now, Dayn Perry had this gem of a quote:

A question that's sometimes posed goes something like this: "Should you run an organization with scouts or statistics?" My answer is the same it would be if someone asked me: "Beer or tacos?" Both, you fool. Why construct an either-or scenario where none need exist? Heady organizations know they need as much good information as possible before they make critical decisions.

Statcast represents the ultimate combination of scouting and stats. A beer-flavored taco if you will. Okay, maybe the analogy breaks down there, because that sounds horrible. Statcast technology is able to scout better than the most observant and persistent scouts, through its ability to directly measure a players tools and properly aggregate them over time. At the same time, its going to upend the existing set of stats we used before. Statcast offers a brave new world of player evaluation, and I for one am going to enjoy seeing what comes next.

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If youre one of the many people whos embraced the sharing economy, youve probably stayed in someone elses apartment or ridden in someone elses car. Maybe youve also done away with your clutter of DVDs, books, or CDs, since you can watch movies on Netflix, read books on Kindle, and hear music on Pandora.

The concept of having more while owning less sounds paradoxical, but thats exactly the scenario were finding ourselves in. Technology is enabling us to move away from ownership and towards an economy based on sharing and subscriptions. Platforms like Airbnb and Lyft or Uber connect renters and riders to landlords and drivers, and digitization means all kinds of media can be stored, streamed, or downloaded in seconds.

But where does it end? Are there things well always want to own, and if so, what are they?

In a new video from Big Think, author and WIRED founding executive editor Kevin Kelly explores the limits of what he calls the subscription economy and asks, Is this the end of owning stuff?

Kelly points out how easy its become to make things like games or books intangible. These things have gone from being physical products to information on a screen.

If we can deliver these intangibles anytime, anywhere, to anybody, that instant aspect of them means we dont have to own them anymore, Kelly says.

And its not just intangibles we dont need to own. If you can summon a car to pick you up within minutes, why own one, especially when owning means storing, cleaning, maintaining, and insuring? Subscribing, Kelly says, gives you all the benefits of owning without any of the liabilities.

But is there a limit to what people will be willing to rent?

Ownership isnt always just about practicality or convenience. Its also about comfort, familiarity, and status, tooand these arent as easy to digitize or subscribe to.

Kelly uses clothes as an example of something else we may soon subscribe to. Your body would be scanned so youd know the clothes would fit, then theyd get delivered to you, youd wear them once, send them back, and theyd be cleaned and sent to the next person.

On the one hand, it would be nice not to lug a suitcase of clothes and personal items along when you travel, instead receiving whatever you need at your destination (and leaving it there when you depart).

But what about your old gym shoes that are perfect for long days of walking? Or that t-shirt youve washed so many times it feels like wearing a fluffy cloud? And dont forget about the brand-name suit you saved up for months to buy, and the hat that bears your alma maters namehow will you tell the world who you are without these?

Not to mention, wouldnt wearing the same clothes dozens of other people have worn be kind of, well, gross?

Similar points might be made about items like kitchenware, toys, camping equipment, or really anything thats among the piles and stashes of stuff in our homes today.

We own things because its convenient, but also because its sentimentalmaybe it would be nice to rent a turkey roaster once a year instead of having it take up space in your cabinet for 364 days, but its also nice to use the one Aunt Sue gifted you from your wedding registry.

For better or worse, ownership also serves as a status symbol. If you can afford expensive cars and luxury-brand clothing and accessories, you may want to own them even if theyre not practical or convenient.

The answer to Kellys question, then, is a bit more nuanced than yes or no. This is the beginning of being able to significantly reduce what we own while retaining access to more than we had before. Its a phenomenon that will spread to new classes of things with varying speed.

How quickly we shift from owning to subscribing will be influenced by price and convenience, but the personal and cultural aspects of ownership will likely provide a counterbalance. I, for one, will always love my comfy old t-shirts and bulky paper books.

That said, preferences tend to change over time and evolve along with cultural norms. As evidenced by Airbnbs explosive growth in a relatively short period of time, many people have readily gone from thinking of their homes as private space to using them as money-makers. Similarly, though we may not be crazy about the idea of sharing clothes right now, the next generation could be as comfortable with it as we are sleeping in other peoples beds.

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Why the Future of Stuff Is Having More and Owning Less - Singularity Hub

Sam Cossman was hit by a big idea next to a lava lake. With his sight obscured by fumes and vapors, he couldnt be confident of his next step. Traditional thermal imaging was a solution, but not an ideal one. So, Cossman cofoundedQwake Tech with Dr. John Long,mer Hacimeroglu, and Bahar Wadia.

Qwake Techs augmented reality system, C-Thru, is built into a futuristic helmet and relies on a thermal imaging camera, toxicity sensors, edge detection, and an AR display to cut through smoke with useful visuals. It might have been born in a volcano, but Qwake Tech thinks the systemhas wider applications in disaster situations, such as a burning building.

The company is working with firefighters to improve current handheld thermal imaging, which requires a firefighter to stop, hold up a device, look through it, interpret the display, put it down, and move forward. C-Thrus display is positioned in front of the eyes, providinga hands-free AR video feed. It further clarifies the videoby highlighting key details with bright edges. The company says this will allowfirefighters to move much more quickly through buildings.

The ability to see in the types of environments that we work in is a game-changer for our industry, says Tom Calvert, Menlo Park Fire Protection District battalion chief. It could mean the difference between life and death.

Image Credit: Qwake Tech

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