computing


Silicon Valley CFP @CloudExpo #DevOps #Serverless #FinTech #IoT #AI #DX

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Cloud Expo, to be held October 31 - November 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA, brings together Cloud Computing, Big Data, Internet of Things, DevOps, Digital Transformation, Machine Learning and WebRTC to one location. Join Cloud Expo / @ThingsExpo conference chair Roger Strukhoff (@IoT2040), June 6-8, 2017, at the Javits Center in New York City, NY and October 31 - November 2, 2017, Santa Clara Convention Center, CA for three days of intense Enterprise Cloud and'Digital Transformation' discussion and focus, including Big Data's indispensable role in IoT, Smart Grids and (IIoT) Industrial Internet of Things, Wearables and Consumer IoT, as well as (new) Digital Transformation in Vertical Markets. Accordingly, attendees at the upcoming 20th Cloud Expo / @ThingsExpo June 6-8, 2017, at the Javits Center in New York City, NY and October 31 - November 2, 2017, Santa Clara Convention Center, CA will find fresh new content in a new track called FinTech, which will incorporate machine learning, artificial intelligence, deep learning, and blockchain into one track. The upcoming 20th International @CloudExpo @ThingsExpo, June 6-8, 2017, at the Javits Center in New York City, NY and October 31 - November 2, 2017, Santa Clara Convention Center, CA announces that its Call For Papers for speaking opportunities is open.


The Artificial Activist Investor (AAI)

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Deep learning can screen social media behaviour on Twitter, Facebook and additional news stories to connect data points and make predictions. To figure this out, in 2014 the NASA, the Universities Space Research Association and Google joint the Quantum Artificial Intelligence Lab. Eurekahedge, an independent data provider and alternative investment research firm that specialises in hedge fund databases, stated that their own Eurekahedge AI/Machine Learning Hedge Fund Index has outperformed both traditional quant and more generalized hedge funds since 2010. The Guardian: Google's DeepMind makes AI program that can learn like a human


Are AI and "deep learning" the future of, well, everything?

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However, this is just the beginning: with companies such as Google, Microsoft and Facebook spending millions on research into advanced neural networks and deep machine learning, computers are set to get smarter still. "There's a good reason why Google remains at the forefront of the deep learning revolution: data, and lots of it." Although Apple has recently been on a hiring mission, seeking 80-plus AI experts to help make Siri smarter than Google Now or Microsoft's Cortana, it's still playing catch-up. Google is using the lessons it's learnt in image recognition to advance a whole gamut of technologies including speech recognition, Street View detection, language translation and spam detection.


The Biggest Challenges Facing Artificial Intelligence (AI) In Business And Society

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AI – specifically the machine learning and deep learning techniques which show the most promise, require a huge number of calculations to be made very quickly. Data science courses focusing on the core skills needed for AI development – mathematics, computer science and statistics – have become prevalent and are generally over-subscribed. "For example algorithms used by banks are mainly linear maths and it's pretty easy to explain the path from the input to the output – 'I denied your mortgage application because, you don't have a job, or whatever…' "With multi-layer neural networks, the average human doesn't understand, so now we're making predictions based on things that people don't understand and that's going to make people uncomfortable." The problem here is that "naturally" intelligent organisms like humans are capable of taking into consideration learning and data from tasks other than the one we are currently working on.


How a new wave of machine learning will impact today's enterprise

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First, advances in computing technology (GPU chips and cloud computing, in particular) are enabling engineers to solve problems in ways that weren't possible before. For example, chipmaker NVIDIA has been ramping up production of GPU processors designed specifically to accelerate machine learning, and cloud providers like Microsoft and Google have been using them in their machine learning services. Rather than focus on general intelligence, machine learning algorithms work by improving their ability to perform specific tasks using data. However, rather than hire teams of AI innovators like the first wave of AI tech giants have done, today's technology companies must build their AI capabilities using out-of-the-box machine learning tools from AI-focused platform providers like Microsoft and Google.


[video] #SmartCities with @InteractorTeam @ThingsExpo #IoT #IIoT #AI #DX

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With major technology companies and startups seriously embracing Cloud strategies, now is the perfect time to attend 21st Cloud Expo, October 31 - November 2, 2017, at the Santa Clara Convention Center, CA, and June 12-14, 2018, at the Javits Center in New York City, NY, and learn what is going on, contribute to the discussions, and ensure that your enterprise is on the right path to Digital Transformation. With major technology companies and startups seriously embracing Cloud strategies, now is the perfect time to attend @CloudExpo @ThingsExpo, October 31 - November 2, 2017, at the Santa Clara Convention Center, CA, and June 12-4, 2018, at the Javits Center in New York City, NY, and learn what is going on, contribute to the discussions, and ensure that your enterprise is on the right path to Digital Transformation. Join Cloud Expo @ThingsExpo conference chair Roger Strukhoff (@IoT2040), October 31 - November 2, 2017, Santa Clara Convention Center, CA, and June 12-14, 2018, at the Javits Center in New York City, NY, for three days of intense Enterprise Cloud and'Digital Transformation' discussion and focus, including Big Data's indispensable role in IoT, Smart Grids and (IIoT) Industrial Internet of Things, Wearables and Consumer IoT, as well as (new) Digital Transformation in Vertical Markets. Accordingly, attendees at the upcoming 21st Cloud Expo @ThingsExpo October 31 - November 2, 2017, Santa Clara Convention Center, CA, and June 12-14, 2018, at the Javits Center in New York City, NY, will find fresh new content in a new track called FinTech, which will incorporate machine learning, artificial intelligence, deep learning, and blockchain into one track.


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The world's top researchers are pushing the boundaries of artificial intelligence at the NVIDIA AI Labs, known as NVAIL, located at 20 top universities around the globe. At University of Toronto, Raquel Urtasun is developing affordable self-driving cars. But because genomic data is highly complex, researchers must develop more effective deep learning techniques, said Adriana Romero, a post-doctoral fellow at Montreal Institute for Learning Algorithms, Université of Montréal. "Right now you see robots in factories or other settings where they repeat the same thing over and over again," said Chelsea Finn, a doctoral student working in the University of California, Berkeley's AI lab, which was one of the first to receive an NVIDIA DGX-1.


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WIRED

To build and run machine learning services you need computing power and data, and the more you have of each the more powerful your software can be. Image recognition is particularly good on mobile devices, says Song Han, a Stanford University graduate student working on compressing neural networks. He developed one such system that helps Facebook's augmented reality platform track objects. And Qualcomm, the leading chipmaker for Android devices, has been working on hardware tricks to speed up neural networks on mobile devices for some time.


3 Ways AI Can Boost NVIDIA -- The Motley Fool

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The graphics specialist has been applying its graphics processing units (GPUs) to train AI models, setting itself up to tap an AI chip market that could be worth $16 billion in 2022, according to Markets and Markets. The company launched its first-generation DRIVE PX platform two years ago, hoping to partner with automakers and develop self-driving cars. All of these partnerships have pushed NVIDIA's automotive revenue from just $56 million at the end of fiscal year 2015 to $140 million in the first quarter of fiscal 2018. NVIDIA saw this trend early and launched its Tesla GPU accelerators around five years ago for supercomputing applications.


China may match or beat America in AI

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AT THE start of this year, two straws in the wind caught the attention of those who follow the development of artificial intelligence (AI) globally. First, Qi Lu, one of the bosses of Microsoft, said in January that he would not return to the world's largest software firm after recovering from a cycling accident, but instead would become chief operating officer at Baidu, China's leading search engine. Another AI startup, iFlytek, has developed a voice assistant that translates Mandarin into several languages, including English and German, even if the speaker uses slang and talks over background noise. And Megvii Technology's face-recognition software, Face, identifies people almost instantaneously.