Day One of the 12th annual Emerging Technologies for the Enterprise Conference was held on Tuesday, April 18 in Philadelphia, PA. This two-day event included keynotes by Blair MacIntyre (augmented reality pioneer) and Scott Hanselman (podcaster), and featured speakers Monica Beckwith (JVM consultant at Oracle), Yehuda Katz (co-creator of Ember.js), and Jessica Kerr (lead engineer at Atomist).
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.
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.
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.
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.
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.
Nine months after acquiring BoldRadius, Lightbend announced their acquisition of OpsClarity, a company specializing in monitoring reactive applications. InfoQ interviewed Mark Brewer, president and CEO at Lightbend and Alan Ngai, co-founder of OpsClarity and now VP of cloud services at Lightbend to learn more about this new partnership.
Beam exits incubation period and graduates to top-level Apache project, Google support and contribution to open source integration for various data processing backends and more.
Deep Learning is a rapidly evolving subfield of Machine Learning originating from Neural Networks. Recent algorithmic advances and utilization of GPU parallelization have resulted in Deep Learning based algorithms mastering the game of Go as well as several practical applications. The fashion industry is one of the target sectors for Deep Learning. Gilt is using Deep Learning for real world apps
Microsoft has developed and open sourced AirSim, a tool that can be used to simulate the flight of drones around the world. The simulator is built on the Unreal Engine and Microsoft will soon add support for robots and other types of vehicles.
Apache Flink 1.2 was announced and features dynamic rescaling, security, queryable state, and more. The release resolved 650 issues, maintains compatibility with all public APIs and ships with Apache Kafka 0.10 and Apache Mesos support. Flink’s dynamic rescaling allows one to change the parallelism of a streaming job or of an operator within the job.
MindMeld, a conversational AI company, has published The Conversational AI Playbook, a guide outlining the challenges and the steps to be made to create conversational applications.
Apache HBase 1.3.0 was released mid-January 2017 and ships with support for date-based tiered compaction and improvements in multiple areas, like write-ahead log (WAL), and a new RPC scheduler, among others. The release includes almost 1,700 resolved issues in total.
Apache Eagle, an open-source solution for identifying security and performance issues on big data platforms, graduates to Apache top level project on January 10, 2017. Firstly open-sourced by eBay on October 2015, Eagle was created to instantly detect access to sensitive data or malicious activities and, to take actions in a timely fashion.
In late 2016, Microsoft announced the general availability of Azure SQL Database In-Memory technologies. In-Memory processing is only available in Azure Premium database tiers and provides performance improvements for On-line Analytical Processing (OLTP), Clustered Columnstore Indexes and Non-clustered Columnstore Indexes for Hybrid Transactional and Analytical Processing (HTAP) scenarios.