InfoQ Homepage Machine Learning Content on InfoQ
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MIT and Toyota Release Autonomous Driving Dataset DriveSeg
Toyota's Collaborative Safety Research Center (CSRC) and MIT's AgeLab have released DriveSeg, a dataset for autonomous driving research. DriveSeg contains over 25,000 frames of high-resolution video with each pixel labelled with one of 12 classes of road object. DriveSeg is available free of charge for non-commercial use.
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Google ML Kit SDK Now Focuses on On-Device Machine Learning
Google has introduced a new ML Kit SDK aimed at working in standalone mode without requiring a tight integration with Firebase, as the original ML Kit SDK did. Additionally, it provides limited support for replacing its default models with custom ones for image labeling and object detection and tracking.
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Facebook Announces TransCoder AI to Translate Code across Programming Languages
Facebook AI Research has announced TransCoder, a system that uses unsupervised deep-learning to convert code from one programming language to another. TransCoder was trained on more than 2.8 million open source projects and outperforms existing code translation systems that use rule-based methods.
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Uber Open-Sources AI Abstraction Layer Neuropod
Uber open-sourced Neuropod, an abstraction layer for machine learning frameworks that allows researchers to build models in the framework of their choice while reducing the effort of integration, allowing the same production system to swap out models implemented in different frameworks. Neuropod currently supports several frameworks, including TensorFlow, PyTorch, Keras, and TorchScript.
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Paddle Quantum: Bringing Baidu Deep Learning Perform to Quantum Computing
Baidu has announced quantum machine learning toolkit Paddle Quantum, which makes it possible to build and train quantum neural network models. Paddle Quantum aims to support advanced quantum computing applications as well as to allow developers new to quantum machine learning to create their models step-by-step.
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Google Open-Sources Computer Vision Model Big Transfer
Google Brain has released the pre-trained models and fine-tuning code for Big Transfer (BiT), a deep-learning computer vision model. The models are pre-trained on publicly-available generic image datasets and can meet or exceed state-of-the-art performance on several vision benchmarks after fine-tuning on just a few samples.
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OpenAI Announces GPT-3 AI Language Model with 175 Billion Parameters
A team of researchers from OpenAI recently published a paper describing GPT-3, a deep-learning model for natural-language with 175 billion parameters, 100x more than the previous version, GPT-2. The model is pre-trained on nearly half a trillion words and achieves state-of-the-art performance on several NLP benchmarks without fine-tuning.
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AWS Releases its Machine Learning Powered Enterprise Search Service Kendra into General Availability
Recently Amazon announced the general availability of its enterprise search service Kendra on AWS. With the GA release of Amazon Kendra, the public cloud provider added a few new specialized features and improved service accuracy.
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Concurnas: the New Language on the JVM for Concurrent and GPU Computing
Concurnas is a new open source JVM programming language designed for building concurrent and distributed systems. Concurnas is a statically typed language with object oriented, functional, and reactive programming constructs. With native support for GPU computing and vectorization, Concurnas allows for building machine learning applications and high performance parallel applications.
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Google AI Launches NLU-Powered Tool to Help Explore COVID-19 Literature
Google AI launched COVID-19 Research Explorer, which provides a semantic search interface on top of the COVID-19 Open Research Dataset to help scientists and researchers efficiently analyze all of the dataset’s journal articles and preprints.
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Google Open-Sources New Higher Performance TensorFlow Runtime
Google open-sourced the TensorFlow Runtime (TFRT), a new abstraction layer for their TensorFlow deep-learning framework that allows models to achieve better inference performance across different hardware platforms. Compared to the previous runtime, TFRT improves average inference latency by 28%.
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Predicting Failing Tests with Machine Learning
Machine learning can be used to predict how tests behave on changes in the code. These predictions reduce the feedback time to developers by providing information at check-in time. Marco Achtziger & Dr. Gregor Endler presented how they are using machine learning to learn from failures at OOP 2020.
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Moogsoft Adds Virtual Network Operations Centre Capability
AIOps platform vendor, Moogsoft, has announced the release of Moogsoft Enterprise 8.0, featuring a capability for technology teams to build a virtual Network Operations Centre (NOC). Moogsoft Enterprise consolidates monitoring tools with the intention of helping technology teams reduce noise, prioritize incidents, reduce escalations and ensure uptime.
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DeepMind's Agent57 Outperforms Humans on All Atari 2600 Games
Researchers at Google's DeepMind have produced a reinforcement-learning (RL) system called Agent57 that has scored above the human benchmark on all 57 Atari 2600 games in the Arcade Learning Environment. Agent57 is the first system to outperform humans on even the hardest games in the suite.
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Google Cloud Healthcare API Now Generally Available
In a recent blog post, Google announced the general availability of its Cloud Healthcare API. This service facilitates the exchange of healthcare data between solutions built on Google Cloud Platform (GCP) and applications.