InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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Microsoft Releases Dialogue Dataset to Make Chatbots Smarter
Maluuba, a Microsoft company working towards general artificial intelligence, recently released a new open dialogue dataset based on booking a vacation. With this dataset, they help researchers and developers make their chatbots smarter.
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Google Reveals Details of TensorFlow Processor Unit Architecture
Google's hardware engineering team that designed and developed the TensorFlow Processor Unit detailed the architecture and benchmarking experiment earlier this month. This is a follow up post on the initial announcement of the TPU from this time last year.
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The AI Misinformation Epidemic
Over the past five years, Google searches for Machine Learning have gone up five times. “Fo anything that has machine learning in it or blockchain in it, the valuation goes up, 2, 3, 4, 5x”, Andy Stewart pointed out. Zachary Lipton claimed a "misinformation epidemic" in the field in a recent blog post. In this article we present the technical perspective of ML and how it can be presented.
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10 Weeks to QCon New York: Keynotes Announced and Early Peek into the Speaker Lineup
QCon New York (the 6th annual software conference) is just 10 weeks away. June 26-28 QCon returns to its new location at Times Square’s Marriott Marquis, but with the same great lineup of speakers. 2017 features speakers from Stitch Fix, Google, Netflix, Lyft, Pivotal, Redis Labs, among others.
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Amazon Lex Now Generally Available to Enable Conversational Interfaces
Amazon Lex, the platform behind Amazon Alexa, is now generally available to create voice-powered chatbots and mobile, web, and desktop apps.
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Nikita Ivanov on Apache Ignite In-Memory Computing Platform
Apache Ignite is an in-memory computing platform with transactional support, that supports both key-value persistence as well as streaming and complex-event processing. Ignite was open-sourced by GridGain in late 2014 and accepted in the Apache Incubator program. InfoQ interviewed Nikita Ivanov, CTO of GridGain, to find out more about Apache Ignite.
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Data Preparation Pipelines: Strategy, Options and Tools
Data preparation is an important aspect of data processing and analytics use cases. Business analysts and data scientists spend about 80% of their time gathering and preparing the data rather than analyzing it or developing machine learning models. Kelly Stirman spoke last week at Enterprise Data World 2017 Conference about the data preparation best practices.
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Google Announces Cloud Machine Learning API Updates
Google recently announced the Cloud Machine Learning API updates at the Google Cloud Next Conference. This includes a set of APIs in the areas of vision, video intelligence, speech, natural language, translation and job search.
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Intel Launch Optane SSD
Intel recently launched their 3D XPoint non-volatile memory (NVM) under the brand name of Optane. The SSD label in some of the branding might imply that it’s a different type of durable storage, but the technology is aimed at applications that would normally use RAM. This marks the beginning of the end of the compromise between in memory and persistent.
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Using Deep Learning Technologies IBM Reaches a New Milestone in Speech Recognition
The research team at IBM recently announced they've reached a new industry record at 5.5%, using the SWITCHBOARD linguistic corpus. This brings us closer to what's considered to be the human error rate, 5.1%. They used deep learning technologies and acoustic models to accomplish this milestone.
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FaunaDB: A New Distributed Database from the Team That Scaled Twitter
Former technical leaders from Twitter and Couchbase have created FaunaDB, a new general-purpose database.
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Netflix Demonstrates Big Data Analytics Infrastructure
At QCon San Francisco, engineers at Netflix discussed their big data strategy and analytics infrastructure. This included a summary of the scale of their data, their S3 data warehouse, and Genie, their big data federated orchestration system.
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Yahoo Open Sources TensorFlowOnSpark
Yahoo open sources TensorFlowOnSpark, allowing Spark-native TensorFlow runtime and integration for distributed training and serving on Spark or Hadoop.
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Conference Recap: Google Cloud Next
Cloud enthusiasts from around the world attended Google Cloud Next to hear an update from the search giant. Three broad themes emerged from the many keynotes and 200+ sessions: service scale and maturity, usable machine learning, and enterprise-friendliness.
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Apache Ranger Graduates to Top-Level Project
Apache Ranger, a security management framework for Apache Hadoop ecosystem, graduated to top level. Ranger is used as a centralized component to define and administer security policies that are enforced across supported Hadoop components such as Apache HBase, Hadoop (HDFS and YARN), Apache Hive, Apache Kafka, Apache Solr, among others.