InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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Tracks Announced & Registrations off to a Fast Start: QCon London 2017 (March 6-10, 2017) Update
QCon London 2017, the 11th annual practitioner-driven conference designed for team leads, architects and influencers driving innovation in their teams, hosts more than 125 speakers across 18 concurrent tracks over three days. Track topics have been finalized and published. Ticket sales for this year’s conference are off to a fast start - register before December 17 2016 and save £360.
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Spark Summit EU Highlights: TensorFlow, Structured Streaming and GPU Hardware Acceleration
Apache Spark integration with deep learning library TensorFlow, online learning using Structured Streaming and GPU hardware acceleration were the highlights of Spark Summit EU 2016 held last week in Brussels.
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New and Interesting Changes on ThoughtWorks Radar
As usual, the ThoughtWorks Technology Radar covers four areas - Language & Frameworks, Platforms, Techniques, Tools – each item having one of four recommendations – Adopt, Trial, Assess, Hold. This article lists only what is new and noteworthy in the respective areas.
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QCon SF Keynote: The History and Future of Wearable Computing and Virtual Experience
Amber Case gave the opening keynote talk at QCon San Francisco. She spoke about the history and current state of virtual reality interfaces, the challenges faced by augmented reality and how these can be overcome as people become more comfortable with the advances in technology.
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JVMs Across the Data Center and Twitter's JDK
The Twitter Sponsored Solutions track at QConSF2016 features an engineering talk on JVMs Across the Data Center and unveils an in-house OpenJDK fork, the Twitter-JDK, with noted potential open-sourcing or release to broader public.
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Google Details Allo Recommendation Graph Processing Algorithm
Google details a graph streaming algorithm for constant runtime over large graphs of varying complexity space and predictor outputs.
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Microsoft Releases Data Science Tools for Interactive Data Exploration and Modeling
Microsoft recently released two new data science tools for interactive data exploration: modeling and reporting. These tools can be reused by data science teams with data specific tasks in their projects. The goal is to ensure consistency and completeness of data science tasks across different projects in the organization.
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Microservices and Stream Processing Architecture at Zalando Using Apache Flink
Javier Lopez and Mihail Vieru spoke at Reactive Summit 2016 Conference about cloud-based data integration and distribution platform used for stream processing in business intelligence use cases. Their solution is based on technologies such as Flink, Kafka and Elasticsearch.
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Google Machine Learning Models for Image Captioning Ported to TensorFlow and Open-Sourced
As TensorFlow becomes more widely adopted in the machine learning and data science domains, existing machine learning models and engines are being ported from existing frameworks to TensorFlow for improved performance, furthering the adoption and success of the open-sourced project.
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Wolfram Wants to Deliver “Computation Everywhere” with New Private Cloud
Wolfram, the software company behind computation-centric products like Mathematica and Wolfram|Alpha, shipped a new private cloud appliance targeting companies that want to centralize their computational efforts.
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QCon Awarded 10 Diversity Scholarships for QCon SF 2016
QCon San Francisco has provided diversity scholarships to underrepresented groups in the technology community. The Conference is committed to encouraging diversity.
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Ocado Uses TensorFlow and Google Cloud Platform for Novel Customer Service Approach
Ocado Technology uses TensorFlow to categorize customer emails for automated support queue categorization and prioritization for the goals of quick response time and avoiding impersonal support bots often used with large customer volumes and finite support resources.
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CommAI, a Training and Testing AI System by Facebook
Facebook recently announced CommAI-env, a platform for training and evaluating an AI system. Inspired by A roadmap towards Machine Intelligence the system aims for teaching intelligent agents general learning capabilities that would serve as the groundwork for further, more specialized training by human or machine level interaction. The article provides a high level overview of current state and..
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Stream Processing and Lambda Architecture Challenges
Lambda architecture has been a popular solution that combines batch and stream processing. Kartik Paramasivam at LinkedIn wrote about how his team addressed stream processing and Lambda architecture challenges using Apache Samza for data processing. The challenges described are the late arrival of events and the processing of duplicated messages.
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Jay Kreps on Distributed Stream Processing with Apache Kafka and Kafka Streams
Apache Kafka and Kafka Streams frameworks help with developing stream-centric architectures and distributed stream processing applications. Jay Kreps, CEO of Confluent, gave the keynote presentation on stream processing and microservices at Reactive Summit 2016 Conference last week.