conference


Google to open Chinese artificial intelligence research lab

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Google's announcement about a new facility in China comes after a period of speculation and a talent hunt in the country. As a country, China is both strict on foreign firms influencing its population, and supportive of AI research and development, and Google has been making efforts to demonstrate its AI products there. A new Beijing centre was announced today (13 December) in Shanghai, and will be led by Fei-Fei Li, a professor at Stanford University who is chief scientist of AI and machine learning at Google Cloud, and Dr Jia Li, head of research and development at Google Cloud AI. Google describes itself as an "AI-first" firm. It is extending its artificial intelligence research into China, despite its search engine, App Store, email and cloud services being banned in the country.


MCubed returns to London in 2018, call for papers open

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Events The call for papers for MCubed 2018 is open, and we really want to hear how you're putting machine learning, AI and robotics to work in real organisations. We pulled it off, as you can see here, and are aiming to push things forward in 2018, reflecting the breakneck progress in the sector over the last year – not forgetting to learn from any breakages along the way. So we want to hear from you if you can explain the fundamental technologies and thinking underpinning today's tech – and if you're one of the people taking these fundamentals and putting them to work. You might be applying ML to make sense of vast unstructured data lakes to throw up profound new insights – or on discrete sets of data to make existing processes run more smoothly. You might be developing AI to make sense of huge amounts of financial data to empower your traders, or working out the UX that will help them understand the insights in the first place.


Making R Code Faster : A Case Study

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I had a working, short script that took 3 1/2 minutes to run. While this may be fine if you only need to run it once, I needed to run it hundreds of time for simulations. My first attempt to do so ended about four hours after I started the code, with 400 simulations left to go, and I knew I needed to get some help. This post documents the iterative process of improving the performance of the function, culminating in a runtime of .64 seconds for 10,000 iterations, a speed-up of more than 100,000x. At Etsy I work a lot on our A/B Testing system.


Google can't miss out on China's AI boom--so it's opening a research lab there

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Google announced today it will open a lab in Beijing dedicated to researching artificial intelligence (AI). The news comes as China's government and tech companies race ahead to dominate the field, putting Google in a position where it has no choice but to set up locally in order to remain at the cutting edge. According to the search giant, the lab will be led by a small team of researchers and supported by Google engineers already working in China on developing the company's global-facing products. It will be helmed by Jia Li, head of research and development at Google Cloud AI, and Fei-fei Li, director of the Stanford Artificial Intelligence Lab and a chief scientist at Google Cloud AI. In a blog post announcing the move, Li notes that the company is currently hiring for positions at the lab--something media outlets picked up on a few months ago.


Fundamentals of Machine Learning: Perspectives from a Data Scientist - Conferences - ISC West

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As our world grows more connected, organizations are collecting ever-growing amounts of data. Almost always there are hidden insights in such data that can lead to better outcomes and more value. One important tool to tap into these opportunities is Machine Learning (ML), and across all verticals more and more companies are investing into their ML operations. In this talk, we will take a look at what ML is, what problems it solves, how it is applied, and why companies need to make sure that they have a strategy to employ ML. First, we will explain the relevant fundamental concepts with a focus on supervised learning and geometric models.


The U.S. leads in artificial intelligence, but for how long?

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Even as the world's top artificial-intelligence researchers gathered in Los Angeles this week, many are beginning to wonder just how much longer the U.S. will remain the epicenter of AI. The Neural Information Processing System (NIPS) conference in Long Beach is the number one place for presenting breakthroughs in AI. But U.S. government policies threaten to put a dampener on the recent boom in the field. The U.S. Congress's tax plan is the latest challenge, threatening to raise costs for graduate students significantly. This follows reduced funding for fields including AI and tightening of rules on immigration for international researchers.


Calling All AI Innovators – Join the 'Cloud AI Challenge' for a Chance to Win $25,000

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This post is authored by Vani Mandava, Director of Data Science at Microsoft Research. The AI revolution is poised to unleash unprecedented innovation and impact on our society. Several research and development groups across Microsoft have hit their stride in delivering world-changing impact through the power of AI. Working together, we are creating a comprehensive Microsoft AI platform and a set of AI services that will enable the next generation of intelligent applications that will augment human intelligence. The AI buzz has been impossible to miss at numerous conferences that Microsoft has participated in during the past year.


The First AI-Driven Solution for SAP Cybersecurity CRM Daily

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Nov. 21, 2017 -- ERPScan, the most innovative ERP cybersecurity provider, announces the release of the first and only AI-driven SAP cybersecurity platform at "Cybersecurity for SAP Customers" conference in Las Vegas. The new platform leverages Machine Learning and Deep Learning to provide predictive, preventive, detective and responsive capabilities thus covering all aspects of SAP Security in one platform. Gartner predicted, "Through 2022, AI will be a major battleground for technology leadership," and we already started to drive it [1]. While cyberattacks are looming large over enterprises, it is inappropriate to rely on the detection and patching of vulnerabilities alone but crucial to detect any potential attack. Business applications are customized in the way that building the signature-based threat detection is ineffective, and, as a matter of fact, traditional approaches can hardly help.


[slides] Continuous Deep Learning for Visual Systems @CloudExpo @CalSci #AI #ML #DL #Cloud

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In his session at 21st Cloud Expo, James Henry, Co-CEO/CTO of Calgary Scientific Inc., introduced you to the challenges, solutions and benefits of training AI systems to solve visual problems with an emphasis on improving AIs with continuous training in the field. He explored applications in several industries and discuss technologies that allow the deployment of advanced visualization solutions to the cloud. Speaker Bio James Henry is Co-CEO/CTO of Calgary Scientific Inc., a company specializing in bringing real time interactive software to cloud and mobile platforms. He has 25 years of experience leading software teams in many industries including the oil and gas, healthcare, telecommunication, geolocation, construction and simulation industries. His current interest is in enabling people, data and AIs to interact in real time to solve complex problems.


NEW REPORT ALERT: AI First - SogetiLabs

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'We are at a tipping point where AI is really taking off … […] I think we will evolve in computing from a mobile first to an AI first world.' It is not surprising that Sundar Pichai, CEO of Google, repeatedly praises the potential of AI. In an explanation of the quarterly figures of the world's largest search engine, he says that the past ten years have been about'mobile first'. In his view, the next ten years will be about'AI first'. He anticipates that in the near future the concept of the device will fade completely.