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Category: robotics/AI – Page 2,022

Here come the robots: intelligent machines could take, make, or reboot software testing and security jobs

By Rohit Talwar, Steve Wells, Alexandra Whittington, and Maria Romero

As artificial intelligence (AI) revolutionises work as we know it, how will the software testing and security industry be impacted?

The robots are coming: “Lock up your knowledge and protect your job at all costs!” The apocalyptic warnings are starting to flow of how artificial intelligence (AI) and robotics combined with other disruptive technologies could eliminate the need for humans in the workplace. Equally sceptical voices are rubbishing the idea that anything drastic will happen, citing previous industrial revolutions as proof that new jobs will emerge to fill any gaps created by the automation of existing ones. In practice, no one really knows how quickly AI might eliminate jobs or what the employment needs will be of the future businesses and industries that have not yet been born.

But the future is not

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Apple buys Xnor.ai, an edge AI startup spin-out from Paul Allen’s research lab, for $200 million

Tech giant Apple has acquired Xnor.ai, an artificial intelligence startup that came from Microsoft co-founder Paul Allen’s research lab. The acquisition suggests that Apple may be planning to Xnor.ai’s machine learning tools int iPhones and iPads in the future, with processing on-device instead of in the cloud.

GeekWire first broke the news earlier Wednesday, citing sources with knowledge of the deal. According to GeekWire, the deal is reportedly worth up about $200 million. Apple paid the same $200 million for another Seattle-based AI startup, Turi, in 2016.

Unlike traditional AI that runs in massive data centers and requires network connectivity, XNOR makes AI highly efficient by allowing deep learning models to run directly on phones, IoT devices and low power microprocessors. XNOR’s technology enables AI experiences that are up to 10x faster, 200 percent more power efficient, and use 15x less memory.

Machine learning on the edge

In a recent IEEE Spectrum article, learn how engineers are taking machine learning to the smallest microprocessors, while facing challenges in energy consumption, compressing neural networks, and privacy practices. #tinyML #neuralnetworks #machinelearning

IN FEBRUARY, a group of researchers from Google, Microsoft, Qualcomm, Samsung, and half a dozen universities will gather in San Jose, Calif., to discuss the challenge of bringing machine learning to the farthest edge of the network, specifically microprocessors running on sensors or other battery-powered devices.

How 3D Printing, Vertical Farming, and Materials Science Are Overhauling Food

Within the next 10 years, what we eat and how it’s grown will be fundamentally transformed.

And converging exponential technologies—from materials science to AI-driven digital agriculture—are not slowing down. Today’s breakthroughs will soon allow our planet to boost its food production by nearly 70 percent, using a fraction of the real estate and resources, to feed 9 billion by mid-century.

What you consume, how it was grown, and how it will end up in your stomach will all ride the wave of converging exponentials, revolutionizing the most basic of human needs.

[Note: This article is an excerpt from my next book The Future Is Faster Than You Think, co-authored with Steven Kotler, to be released January 28th, 2020.]

Printing Food