InfoQ Homepage Global Big Data Conference Content on InfoQ
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The Future of AI
The panelists discuss the future of artificial intelligence.
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Solving Business Problems with AI
The panelists discuss using AI to solve business problems.
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Women in AI & Blockchain
The panelists discuss the role women can play in AI and blockchain technologies.
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AI & Blockchain from an Investment Perspective
The panelists discuss building AI and blockchain systems from an investment perspective.
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The State of AI Marketing
Federico Gobbi discusses the current state of AI in marketing, trends, case studies, technologies, ethics, regulations and compliance.
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Big Data and Deep Learning: A Tale of Two Systems
Zhenxiao Luo explains how Uber tackles data caching in large-scale DL, detailing Uber’s ML architecture and discussing how Uber uses Big Data, concluding by sharing AI use cases.
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Product Management of AI Products
Manjeet Singh discusses how to bring AI to enterprise product lines, how to analyze, plan, and design AI in a SaaS environment along with practices and lessons learned from Agile AI product lifecycle.
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Accelerated Spark on Azure: Seamless and Scalable Hardware Offloads in the Cloud
Yuval Degani shows how hardware accelerations in Azure can be utilized to speed-up Spark jobs, with the aid of RDMA (Remote Direct Memory Access) support in the VM.
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Implementing AutoML Techniques at Salesforce Scale
Matthew Tovbin shows how to build ML models using AutoML (Salesforce), including techniques for automatic data processing, feature generation, model selection, hyperparameter tuning and evaluation.
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Evaluating Blockchain Companies
Michael Slinn explains the point-based scoring system that he uses when writing an assessment report, and how it applies to blockchain-related technology companies.
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AI in Finance: from Hype to Marketing and Cybersec Applications
Natalino Busa illustrates a number of use cases of using AI and machine learning techniques in finance, such as transaction fraud prevention and credit authorization.
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Systems That Learn
Stephen Buckley discusses the Systems That Learn initiative which aims to create systems that learn by combining expertise in Systems and Machine Learning.