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Meet The Startups That Bring Artificial Intelligence To Log Management And Analysis

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By bringing Machine Learning to log analysis, the systems become smart by becoming proactive. Sensing the opportunity in algorithmic log management, a few startups have built viable business models in the space of Security Information and Event Management (SIEM). Perspica, the San Jose-based startup was found in 2014 by JF Huard, ex-CTO of Netuitive, Inc. Like most of its competitors, it promises to deliver artificial intelligence powered analytics and observability for TechOps and DevOps. It integrates with mainstream monitoring systems, log aggregation engines and Big Data platforms.


What we learned at ElevateAI – integrate.ai – Medium

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Many presenters, from long-time deep learning researchers like Geoff Hinton and Yoshua Bengio to younger pillars of the community like Tomi Poutanen of Layer6 AI, underscored the importance of curiosity-based research to fuel the future economy. The team at D-Wave still don't know what products their delicately entangled qubits may enable: we look forward to exploring how the Quantum Machine Learning cohort at the Creative Destruction Lab will apply this entirely new approach to optimization in machine learning this fall. Efforts like those at ThinkData Works to curate and supply open data sets can only support future Canadian research. Finally, Debow and our CEO & Founder Steve Irvine both underscored the importance of openness, boldness, and mutual support in continuing to push the momentum in our thriving AI ecosystem.


Integrate.ai is a truly global tech company

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While San Francisco and New York are both diverse cities, Toronto has a uniquely cosmopolitan technology community." Hume came to Toronto in May 2017 to join a Toronto AI start-up led by Canadian Steve Irvine, who made headlines early in 2017 when he decided to leave his executive role at Facebook in Silicon Valley to start a company in Toronto. Integrate.ai is building an Artificial Intelligence -powered platform for B2C enterprises that integrates with business processes to make customer interactions more natural and valuable. "In the new AI-oriented world, things are much more probabilistic, so companies can make educated guesses on what the optimal path through the customer journey might be for separate sub-segments of their customer base and optimize the lifetime value those groups will have for their business," explains Hume, who prizes the company's core values and their interdisciplinary approach to technology.


Kakao to integrate AI platform with Samsung's Bixby user interface

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South Korean mobile messenger operator Kakao has partnered with Samsung Electronics in artificial intelligence (AI) technology, Yonhap news agency reports. Under the terms of the deal, Kakao will integrate its'Kakao I' AI platform with Samsung's voice recognition software Bixby. Kakao also plans to expand cooperation with Samsung in other sectors, such as the IoT.


Alzheimer's Spotted Early through Machine-Learning Technique GEN

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The team published its study ("Cascaded Multi-view Canonical Correlation (CaMCCo) for Early Diagnosis of Alzheimer's Disease via Fusion of Clinical, Imaging and Omic Features") in Scientific Reports. "In this work, we present a combined framework, cascaded multiview canonical correlation (CaMCCo), for fusion and cascaded classification that incorporates all diagnostic categories and optimizes classification by selectively combining a subset of modalities at each level of the cascade." In predicting which patients in the study had Alzheimer's disease, CaMCCo reportedly outperformed individual indicators as well as methods that combine them all without selective assessment. It also was better at predicting who had mild cognitive impairment than other methods that combine multiple indicators.


Evolving Government: Why government needs open-source deep learning - Fedscoop

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Beyond being open-source, the deep learning tools that will serve government most effectively should be scalable and fast to handle nation-state level data volumes, and they should integrate with the government's existing technologies well. One reason is because most data science tools don't integrate well with the enterprise production stack. It was this experience that led us to develop Deeplearning4j, the most widely used deep-learning tool for Java, and it's why the Department of Homeland Security chose our framework to perform risk profiling for the Global Traveler Assessment System, as they seek to identify persons of interest from the high volume of travelers making their way to the U.S. Tools that plug into previously adopted frameworks can ensure that data science doesn't die on insight; that is, some data science tools produce insights but can't be easily integrated into production systems, so those insights are difficult to apply to real-time data. By the same token, an AI solution has to serve multiple teams: not just data scientists but also the data engineers building data pipelines, and the DevOps teams that maintain the solution in production.


What you need to know to be an effective virtual leader

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This will help to create a more effective working structure especially if you can include virtual employees in team meetings via Skype so that they contribute to discussions and update the office on their progress and achievements. Usually people work with virtual employees to lessen their responsibilities, not to increase them. I've seen a lot of companies fail to successfully integrate virtual employees into their teams because of they haven't had the right tools in place. Think about it like this: when you hire an in-house employee you provide them with a desk, a computer and a pack of stationary, when you hire a virtual employee you need to set them up with a digital working space.


Today in AI: Integrate.ai closes $5.6M, Element AI partners with Automat

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"Participating in this early strategic round is an exciting opportunity to be part of the Integrate.ai Element AI has announced a partnership with Montreal-based Automat, a conversational marketing platform that leverages AI to help companies talk to their customers. Automat and Element AI will collaborate to deliver messaging experiences leveraging Automat's Conversational Marketing Cloud platform, along with Element AI's enterprise-grade platform. The goal is to ensure Element AI and Automat's customers have access to the products, technology, and expertise required to develop messaging experiences of any nature or complexity. "Working with Automat will offer joint customers a wide array of AI capabilities engineered from our larger AI platform," said Element AI CEO Jean-François Gagné.


AI-machine-learning-are-fueling-advances-in-chatbot-technology?utm_campaign=sca_bizapps1&utm_medium=social&utm_source=twitter&utm_content=1490620761

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Amit Zavery, senior vice president and general manager of integration products for the Oracle Cloud Platform, recently explained the company's positioning in an exclusive interview with SearchCloudApplications. We have embedded machine learning algorithms and AI systems into our database, management products, as well as applications for many years. It is up to all of the providers of chatbot technology, including Oracle, to adhere to industry standards, contribute back into the community, and collaborate across different systems to make sure things work. Zavery: When we look at our chatbot technology, we work with several messaging services providers to make sure we can integrate and interoperate with Facebook Messenger, WeChat and others.


How Quantum Computers Will Revolutionize Artificial Intelligence, Machine Learning And Big Data

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That's why there's a race from the biggest leaders in the industry to be the first to launch a viable quantum computer that would be exponentially more powerful than today's computers to process all the data we generate every single day and solve increasingly complex problems. Once one of these industry leaders succeed at producing a commercially viable quantum computer, it's quite possible that these quantum computers will be able to complete calculations within seconds that would take today's computers thousands of years to calculate. That will be critical if we are going to be able to process the monumental amount of data we generate and solve very complex problems. While today's computers struggle or are unable to solve some problems, these same problems are expected to be solved in seconds through the power of quantum computing.