Google created AI that just needs a few snapshots to make 3D models of its surroundings

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The algorithm only needs a couple perspectives to figure out what objects look like.

Google’s new type of artificial intelligence algorithm can figure out what things look like from all angles — without needing to see them.

After viewing something from just a few different perspectives, the Generative Query Network was able to piece together an object’s appearance, even as it would appear from angles not analyzed by the algorithm, according to research published today in Science. And it did so without any human supervision or training. That could save a lot of time as engineers prepare increasingly advanced algorithms for technology, but it could also extend the abilities of machine learning to give robots (military or otherwise) greater awareness of their surroundings.

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How fast is artificial intelligence growing? Look at the key bellwethers

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AI & Big Data

One can intuitively surmise artificial intelligence (AI) is today’s hot commodity, gaining traction in businesses, academia and government in recent years. Now, there is data — all in one place — that documents growth across many indicators, including startups, venture capital, job openings and academic programs. These bellwethers were captured in the AI Index, produced under the auspices of was conceived within Stanford University’s Human-Centered AI Institute and the One Hundred Year Study on AI (AI100).

One key measure of AI development is startups and venture capital funding. From January 2015 to January 2018, active AI startups increased 2.1x, while all active startups increased 1.3x, the report states. “For the most part, growth in all active startups has remained relatively steady, while the number of AI startups has seen exponential growth,” the report’s authors add. The trickle of venture capital into AI startups, another bellwether, also turned into a torrent. VC funding for AI startups in the US increased 4.5x from 2013 to 2017. Meanwhile, VC funding for all active startups increased 2.08x.

Another key measure, job openings, accelerated in AI. While machine learning is the largest skill cited as a requirement, deep learning is growing at the fastest rate — from 2015 to 2017 the number of job openings requiring deep learning increased 35x, the report’s authors state.

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These people are not real – they were created by AI

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Machine learning algorithms are getting scary-good at creating fake images that look real.

Computers are getting better at generating fake images and video of people saying or doing things they never did in real life. The latest work from chip maker Nvidia takes this a step further by generating convincing-looking images of people who never existed in the first place—they’re AI creations, but they look incredibly real.

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The AI boom is happening all over the world, and it’s accelerating quickly

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The second annual AI Index report pulls together data and expert findings on the field’s progress and acceleration.

The rate of progress in the field of artificial intelligence is one of the most hotly contested aspects of the ongoing boom in teaching computers and robots how to see the world, make sense of it, and eventually perform complex tasks both in the physical realm and the virtual one. And just how fast the industry is moving, and to what end, is typically measured not just by actual product advancements and research milestones, but also by the prognostications and voiced concerns of AI leaders, futurists, academics, economists, and policymakers. AI is going to change the world — but how and when are still open questions.

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In a major breakthrough, Google unveils an AI that learns on its own

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Surpassing The Masters

We’ve written before about how Google is one of the most prominent tech companies leading the way when it comes to the development of artificial intelligence. As each month passes, its AI division, DeepMind, continues to reveal increasingly advanced AI capabilities, especially when it comes to AlphaGo.

This particular AI is most well-known for mastering the ancient Chinese game of Go…and subsequently defeating 18-time world champion Lee Se-dol, which happened just last year.

Since then, DeepMind has started adding imagination to its AI, and they also used gaming to teach the AI how to better manage tasks. AlphaGo even went on to defeat another top go player, Ke Jie, once again showing off its (potentially) unlimited potential to learn.

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Microsoft’s CTO lays out the 2 tech trends he believes will change the world: ‘People haven’t wrapped their heads around this yet’

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Microsoft’s chief technology officer, Kevin Scott, sees two big things coming down the pipeline in the tech industry, he told Business Insider.

  • The first is an explosion of cheap, powerful silicon processors coming in the next five to eight years, leading to every device, everywhere, getting a microprocessor capable of running advanced artificial intelligence.
  • The second, related trend Scott sees is the increased importance of reinforcement learning, the style of machine learning that helps power Google DeepMind’s famous game-playing software bots.
  • Combined, the explosions of software and hardware will give developers everywhere the tools they need to easily solve computing problems once thought impossible in a way that’s cheap and efficient enough for every car, toy, and appliance manufacturer to take advantage.
  • A big part of Microsoft’s role in this is making it easier for developers to take advantage of these trends in their own software, Scott said Continue reading… “Microsoft’s CTO lays out the 2 tech trends he believes will change the world: ‘People haven’t wrapped their heads around this yet’”
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This AI outperformed 20 corporate lawyers at legal work

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Technology is revolutionizing the work we do and how we do it. Increasingly, artificial intelligence (AI) and robots are taking over menial and repetitive tasks, leaving humans to concentrate on work that requires critical thinking.

But as machines become better at imitating human intelligence, they’re beginning to do more and more thinking for us.

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Machine-learning system tackles speech and object recognition, all at once

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MIT computer scientists have developed a system that learns to identify objects within an image, based on a spoken description of the image.

Model learns to pick out objects within an image, using spoken descriptions.

MIT computer scientists have developed a system that learns to identify objects within an image, based on a spoken description of the image. Given an image and an audio caption, the model will highlight in real-time the relevant regions of the image being described.

Unlike current speech-recognition technologies, the model doesn’t require manual transcriptions and annotations of the examples it’s trained on. Instead, it learns words directly from recorded speech clips and objects in raw images, and associates them with one another.

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Can AI have good taste? Auction giant Sotheby’s is counting on it

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Sotheby’s acquired startup Thread Genius, whose machine learning tech can discern clients’ artistic and style leanings–and suggest customized purchases.

Just a few doors down from its CEO and the wood-paneled cubicles where sharply dressed professionals sit, the eighth floor of Sotheby’s New York takes on a very different vibe.

Suddenly, it’s more Silicon Valley than Upper East Side as staid formality gives way to a group of millennials, some in T-shirts with their sneakered feet on desks. Computer code is scrawled on whiteboards and the room’s glass wall. It is here where the storied auction house–founded in 1744–meets its future.

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Will AI ever become conscious?

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When science-fiction worlds introduce robots that look and behave like people, sooner or later those worlds’ inhabitants confront the question of robot self-awareness. If a machine is built to truly mimic a human, its “brain” must be complex enough not only to process information as ours does, but also to achieve certain types of abstract thinking that make us human. This includes recognition of our “selves” and our place in the world, a state known as consciousness.

One example of a sci-fi struggle to define AI consciousness is AMC’s “Humans” (Tues. 10/9c starting June 5). At this point in the series, human-like machines called Synths have become self-aware; as they band together in communities to live independent lives and define who they are, they must also battle for acceptance and survival against the hostile humans who created and used them.

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