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Google is applying machine learning to more than 100 projects Information Age

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At the end of last month, Sundar Pichai wrote his first annual shareholder letter as CEO of Google. Eight months prior, Larry Page and Sergey Brin led a restructure of the company they founded, separating its core internet business from subsidiaries focusing on new areas of innovation, such as self-driving cars, drones, augmented reality, biotech and life sciences. Page and Brin now lead umbrella company Alphabet as CEO and president respectively, while Pichai heads up Google. It was the first time the annual shareholder letter had been written by anyone other than Page and Brin. Pichai kept it simple, outlining the key areas Google will focus on across its product lines – but he was bold enough to say they will all be driven by a long-term investment in machine learning and artificial intelligence.


AI And Machine Learning To Power The Alphabet (NASDAQ:GOOG) Cloud

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Alphabet Inc-A (NASDAQ:GOOGL) unveiled new cloud computing services that allow any developer or business to use the Machine Learning (ML) technologies that power the company's most powerful services, Wired reports. The recent, spectacular victory of Alphabet's AlphaGo program over top Go player Lee Sedol has been hailed as a major Artificial Intelligence (AI) breakthrough and indicates how AI is rapidly becoming a mature technology with a potential for world-changing applications. In fact, AI is becoming adept at more and more high-level cognitive tasks that used to be considered as too complex for automation. "The victory is notable because the technologies at the heart of AlphaGo are the future," noted Wired. "They're already changing Google and Facebook and Microsoft and Twitter, and they're poised to reinvent everything from robotics to scientific research."


NVIDIA vs. Alphabet in the World of AI Technology -- The Motley Fool

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NVIDIA (NASDAQ:NVDA) and Alphabet (NASDAQ:GOOG) (NASDAQ:GOOGL) have turned out to be the unlikeliest of rivals in a slugfest for a greater share of the artificial intelligence (AI) market. So far, Alphabet has been using NVIDIA's GPUs (graphics processing units) to power AI applications on the Google Cloud Platform, though it looks like the search giant has now decided to go it alone in this lucrative space. Let's take a closer look at NVIDIA and Google's AI feud and the potential implications for both companies. Alphabet revealed its plans for its own AI chip -- the Tensor Processing Unit (TPU) -- at last year's Google I/O conference. The TPU chip was already deployed across a variety of applications, including optimizing search results and speech recognition, and in Alphabet's data centers.


Facebook's latest open-source tool will dramatically speed up AI projects

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Since becoming actively involved with the artificial intelligence ecosystem in early 2015, Facebook Inc. has made numerous contributions ranging from niche software modules to entire server blueprints. The social networking giant expanded its repertoire yet again this week by open-sourcing a toolkit called Torchnet that provides building blocks for deep learning projects. As the name implies, it's designed for use with Torch, a popular AI development framework that has been adopted by several of Facebook's engineering teams. Torchnet's main selling point is a set of five programming abstractions meant to common tasks involved in implementing deep learning functionality. One module provides logic for training models and testing their accuracy, while another helps assess the results.


How Open Source Machine Learning Is Accelerating Adoption - Disruption

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As of last month Alphabet Inc.'s AI division, Google DeepMind, has open-sourced their new machine learning platform DeepMind Lab. Artificial Intelligence is the technology of the moment, constantly debated and attracting massive attention from investors. Despite warnings from influential figures including Professor Stephen Hawking, Google's decision to open up their software to other developers is part of a mass movement to advance the capabilities of AI. Facebook open sourced its own deep learning software last year, and Elon Musk's non-profit organisation OpenAI recently released Universe, an open software platform that can be used to train AI systems. So, why have Google, OpenAI and others made these platforms public, and how will this affect the adoption of Artificial Intelligence and machine learning as a whole?