InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
-
Microsoft Open-Sources ONNX Acceleration for BERT AI Model
Microsoft's Azure Machine Learning team recently open-sourced their contribution to the ONNX Runtime library for improving the performance of the natural language processing (NLP) model BERT. With the optimizations, the model's inference latency on the SQUAD benchmark sped up 17x.
-
QCon London ML Learning Paths: Gain Practical ML/AI Skills in Two-Days
Practical machine learning experience is in high demand within the software development industry. Boost your skills with two-day, hands-on Learning Paths that takes place directly after QCon London, held at The Queen Elizabeth II Conference Centre in London March 5-6.
-
Apple Acquires Edge-Focused AI Startup Xnor.ai
Apple has acquired Xnor.ai, a Seattle-based startup that builds AI models that run on edge devices, for approximately $200 million.
-
QCon London - Keynotes & Workshops on Kubernetes, Apache Kafka, Microservices, Docker
QCon London is fast approaching. Join over 1,600 global software leaders this March 2-4. At the event, you will experience: talks that describe how industry leaders drive innovation and change within their organizations; a focus on real-world experiences, patterns, and practices (not product pitches), and implementable ideas for your projects and your teams.
-
Uber's Synthetic Training Data Speeds Up Deep Learning by 9x
Uber AI Labs has developed an algorithm called Generative Teaching Networks (GTN) that produces synthetic training data for neural networks which allows the networks to be trained faster than when using real data. Using this synthetic data, Uber sped up its neural architecture search (NAS) deep-learning optimization process by 9x.
-
Stanford Researchers Publish AI Index 2019 Report
The Stanford Human-Centered Artificial Intelligence Institute published its AI Index 2019 Report. The 2019 report tracks three times the number of datasets as the previous year's report, and contains nearly 300 pages of data and graphs related to several aspects of AI, including research, technical performance, education, and societal considerations.
-
Deep Java Library: New Deep Learning Toolkit for Java Developers
Amazon released Deep Java Library (DJL), an open-source library with Java APIs to simplify training, testing, deploying, and making predictions with deep-learning models. DJL is framework agnostic; it abstracts away commonly used deep-learning functions, using Java Native Access (JNA) on top of existing deep-learning frameworks, currently providing implementations for Apache MXNet and TensorFlow.
-
Google Open-Sources ALBERT Natural Language Model
Google AI has open-source A Lite Bert (ALBERT), a deep-learning natural language processing (NLP) model, which uses 89% fewer parameters than the state-of-the-art BERT model, with little loss of accuracy. The model can also be scaled-up to achieve new state-of-the-art performance on NLP benchmarks.
-
Uber Open-Sources Plug-and-Play Language Model for Controlling AI-Generated Text
Uber AI open-sourced the plug-and-play language model (PPLM) which can control the topic and sentiment of AI-generated text. The model's output is evaluated by human judges as achieving 36% better topic accuracy compared to the baseline GPT-2 model.
-
Microsoft Introduces Power Virtual Agents, a No-Code Solution to Building AI Bots
In a recent blog post, Microsoft announced the general availability (GA) of Power Virtual Agents, a service designed to democratize building conversational chatbots using a no-code graphical user interface. The service is part of the Microsoft Power Platform, which includes Power Apps, Power BI and Power Automate and democratizes access to building artificial intelligence-powered bots.
-
Google Cloud Team Releases AutoML Natural Language
The Google Cloud team recently announced the generally available (GA) release of AutoML Natural Language framework. AutoML Natural Language supports features for data processing and common machine learning tasks like classification, sentiment analysis, and entity extraction.
-
Pull Queries and Connector Management Added to ksqlDB (KSQL) Event Streaming Database for Kafka
The new release of KSQL, an event streaming database for Kafka, includes pull queries to allow for data to be read at a specific point in time using a SQL syntax, and connector management that enables direct control and execution of connectors built to work with Kafka Connect. The Confluent team behind KSQL believes it's a significant release, and has decided to rename the tool to ksqlDB.
-
Amazon Releases SageMaker Studio IDE for Machine Learning
At the recent re:Invent conference, Amazon Web Services (AWS) announced Amazon SageMaker Studio, an integrated development enviornment (IDE) for machine learning (ML) that brings code editing, training job tracking and tuning, and debugging all into a single web-based interface.
-
Amazon Announces the Open Preview of a Managed Apache Cassandra Service (MCS) on AWS
At the recent AWS re:Invent, Amazon announced a new way of managing Cassandra databases on AWS. With Amazon Managed Apache Cassandra Service (MCS), the public cloud vendor can offer Cassandra directly to customers instead of through third-party vendors.
-
QCon New York 2020 Registrations Open & Top Videos from QCon NY 2019
QCon New York, the practitioner-focused software conference that attracts attendees from all over the world, returns to the Marriott Marquis, June 15-19, 2020, for the 9th year. QCon is organized by the people behind InfoQ, & is dedicated to providing a platform for technical leaders & engineers to learn about, engage with, & explore key lessons from building & delivering modern software systems.
CONTENT IN THIS BOX PROVIDED BY OUR SPONSOR
Get a hands-on introduction to Machine Learning from a software professional’s point of view. Find out more about the "Introduction to AI/ML for Software Engineers" Learning Path.
Get a quided walkthrough to produce a working setup that addresses many common problems when deploying machine learning into production. Learn how to to train, track, test and deploy ML. Sign up for this Learning Path.
If you want to learn the essential tools, practices, and techniques that will equip you with practical AI and ML skills you can use immediately, sign up for a QCon Learning Path. Register now before the limited number of tickets sell out.