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Samsung acquires Viv, a next-gen AI assistant built by the creators of Apple's Siri

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Samsung has agreed to acquire Viv, an AI and assistant system co-founded by Dag Kittlaus, Adam Cheyer and Chris Brigham -- who created Siri, which was acquired by Apple in 2010. The three left Apple in the years after the acquisition and founded Viv in 2012. Pricing information was not available, but we'll check around. Viv has been billed as a more extensible, powerful version of Siri. Viv will continue to operate as an independent company that will provide services to Samsung and its platforms.


Are you ready for your own personal Google?

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Sometimes, it's the little changes to language that give away a company's ambition. At the unveiling of Google's new Pixel phones yesterday, CEO Sundar Pichai started the event not by talking about what users can get from Google, but what they can get from their Google. Using artificial intelligence and its new digital assistant, said Pichai, Google's computing power will be available in every facet of users' lives. It'll be seamless and pervasive. "Our goal," he said, "is to build a personal Google for each and every user." Not a single Google that we all can use, but an individualized Google for everyone.


Samsung Makes Big Move In Artificial Intelligence

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Samsung said in a statement it plans to integrate the San Jose-based company's AI platform, called Viv, into the Galaxy smartphones and expand voice-assistant services to home appliances and wearable technology devices. Technology firms are locked in an increasingly heated race to make AI good enough to let consumers interact with their devices more naturally, especially via voice. Alphabet's Google is widely considered to be the leader in AI, but others including Amazon.com, Apple and Microsoft have also launched their own offerings including voice-powered digital assistants. Samsung, the world's top smartphone maker, is also hoping to differentiate its devices, from phones to fridges, by incorporating AI.


Samsung takes a big leap and buys artificial intelligence start-up founded by Siri's creators

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Samsung, the largest maker of televisions and smartphones in the world, is buying Viv Labs, a high-profile artificial intelligence startup founded by the inventors of Apple's Siri voice assistant, the South Korean electronics conglomerate said Wednesday. The move is a major land grab in the battle for cutting-edge artificial intelligence taking place among tech giants. Samsung, which has lagged in such services, is now positioned to add intelligent, Siri-like voice capabilities to its vast collection of home and mobile electronics. "We have a unique opportunity to take advantage of AI, and show the rest of the industry what the smart, connected world can look like," Jacopo Lenzi, Samsung's Senior Vice President of Business Development and Strategic Acquisitions, said in an interview. The companies declined to disclose the purchase price of the deal.


Samsung acquires Viv, an AI platform from the makers of Siri

Engadget

Just a day after Google revealed its premium Pixel phone and Google Home featuring Assistant AI baked in, Samsung is making a splash by buying up some AI power of its own. Viv Labs was founded by some of the same people behind Apple's Siri technology, who have referred to their new platform as an assistant that's capable of anything. Co-founder and CEO Dag Kittlaus writes in a blog post that "Samsung will drastically accelerate our vision." Samsung says the team will continue to operate independently, but it clearly has an eye towards integrating natural language understanding into its phones, TVs, appliances, VR and everything else.


Samsung to Acquire Major Artificial Intelligence Developer

TIME - Tech

Samsung said in a statement it plans to integrate the San Jose-based company's AI platform, called Viv, into the Galaxy smartphones and expand voice-assistant services to home appliances and wearable technology devices. Technology firms are locked in an increasingly heated race to make AI good enough to let consumers interact with their devices more naturally, especially via voice. Alphabet Inc's Google is widely considered to be the leader in AI, but others including Amazon.com, Apple and Microsoft have also launched their own offerings including voice-powered digital assistants. Samsung, the world's top smartphone maker, is also hoping to differentiate its devices, from phones to fridges, by incorporating AI.


Hands-On with Azure Machine Learning

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Get the details on Azure Machine Learning, a cloud-based service for building machine-learning models using a drag-and-drop user interface. Learn to perform sophisticated predictive analytics.


Machine Learning capabilities drive new Spunk products

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Splunk, a software platform provider for real-time Operational Intelligence, has released several new versions of its suite of Splunk products: Splunk Enterprise, Splunk IT Service Intelligence, Splunk Enterprise Security, and Splunk User Behavior Analytics. Available on-premises or in the cloud, the newest versions of Splunk solutions leverage machine learning to make it faster and easier to maximize the value machine data can deliver to organizations. Machine learning is bringing big data analytics into a new era, and Splunk is enabling companies to use predictive analytics to help optimize IT, security and business operations. "Digital transformation has changed the way that organizations work," said Splunk President and CEO Doug Merritt. "The big secret is that all of the change is underpinned by machine data. Machine learning enables organizations to get deeper insights from their machine data and ultimately increases the opportunity our customers can gain from digital transformation."


Natural Gradients and Stochastic Variational Inference

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Examining the Fisher for diagonal Gaussians allows us to see exactly how the natural gradient differs from the standard gradient. If a dimension has small variance, then preconditioning by the inverse Fisher makes the natural gradient smaller along the mean dimension, . Intuitively, this makes sense -- we want our optimization routine to slow down when the component variance is small because small changes to the mean correspond to big changes in KL (see the two skinny Gaussians above), which can result in chatoic looking optimization traces. When the variance along a dimension is large, the inverse Fisher elongates the standard gradient along that dimension. Again, this makes sense -- when the component variance is high we can move the mean a lot farther (in Euclidean distance) without moving that far in terms of KL (see the two wide Gaussians above).