InfoQ Homepage Machine Learning Content on InfoQ
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The Machine Learning Behind Android Pie Smart Linkify API
Last week, Google announced Android 9, codenamed Pie. Android is launching a set of new features, powered by Artificial Intelligence. One of the most important new AI powered features is Android Smart Linkify. This article explores the architecture behind the dual in-device Neural Network powering content understanding in context to generate smart links on any text showing up on an Android phone.
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Pymetrics Open-Sources Fairness-Aware Machine Learning Algorithms
Pymetrics, an AI start-up that specializes in providing recruitment services for organizations, has recently open-sourced their bias detection algorithms on Github. The tool, also known as Audit AI, is used to mitigate discriminatory patterns that exist within training data sets which influence or improve the probability of a population being selected by a machine learning algorithm.
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A Team's Transformation from Software Development to ML: Golestan Radwan at QCon NY
As companies start to add Big Data and Machine Learning initiatives to their project portfolios, they face several challenges including the teams' transition from software engineering to data engineering and machine learning. Golestan "Sally" Radwan spoke at QCon New York 2018 Conference about her experience in leading a traditional software engineering team on a machine learning/AI journey.
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Google Has Released Android P Beta 2
Google has released Android P Beta 2. Android P Beta 2 includes the final Android P APIs, latest system images, display cutout support, and more.
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Apple Has Released Core ML 2
At WWDC Apple released Core ML 2: a new version of their machine learning SDK for iOS devices. The new release of Core ML should create an inference time speedup of 30% for apps developed using Core ML 2. An important new feature of the Core ML SDK is Create ML. Developers can create and train custom machine learning models on their mac.
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Testing Software with Artificial Intelligence
Advances in computer vision algorithms and the application of modern artificial intelligence (AI) techniques have made writing visual tests practical. With AI in testing, autonomous testing becomes possible. The boring and rote tasks will be delegated to the AI so that the tester can do the thinking.
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Google Brings Machine Learning to Firebase with ML Kit
Google recently introduced ML Kit, a machine-learning module fully integrated in its Firebase mobile development platform and available for both iOS and Android. With this new Firebase module, Google simplifies the creation of machine-learning powered applications on mobile phones and solves some of the challenges of implementing computationally intense features on mobile devices.
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Propel Shifts Plans to Leverage TensorFlow.js
The Propel JavaScript scientific computing and machine learning library has announced a change in the project's direction. Just a few weeks after Propel's initial launch in March 2018, TensorFlow.js announced its release. Propel's initial efforts extended deeplearn.js and the C implementation of TensorFlow. Tensorflow.js is an evolution of deeplearn.js.
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Build 2018: .NET Overview & Roadmap
At Microsoft Build 2018, Scott Hunter, director program management, .NET and Scott Hanselman, director community, .NET gave a session on the future of .NET. The thrust of the presentation was that .NET can be the platform for building any kind of application: desktop, web, cloud, mobile, gaming, IoT or AI. Your existing language skills are not wasted and can be used in new areas.
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What’s New in Azure Machine Learning?
Matt Winkler delivered a talk at Microsoft Build 2018 explaining what is new in Azure Machine Learning. The new improvements come in several areas: making development easier, single container deployment to make the dev/test loop faster, using the SDK from the Azure Notebook for control, as well as helping people get started solving a particular problem.
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Tensorflow with Javascript Brings Deep Learning to the Browser
Google launched Tensorflow.js, a Javascript implementation of its open-source Tensorflow deep-learning framework during the recent TensorFlow Dev Summit 2018. Tensorflow.js enables training models directly in the browser by leveraging the WebGL JavaScript API for faster computations.
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Dataiku's Latest Release Integrates Deep-Learning for Computer Vision
Collaborative data science platform Dataiku's latest release of its Data Science Studio includes pre-trained deep learning models for image processing. The DSS platform implements each step of a data-science project from data-sourcing and visualization to production deployment. Its machine-learning module supports standard libraries and it integrates with Hadoop and multiple Spark engines.
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Baidu Release Huge Dataset "ApolloScape" for Autonomous Vehicle Research
Baidu, the Chinese internet giant, has released ApolloScape, a massive data-set for autonomous vehicle simulation and research. ApolloScape is an order of magnitude more complex than similar open data-sets. It is part of Apollo, Baidu's vehicle simulation and hardware platform. With this release, Baidu strengthens its position in the automated driving sector.
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Fighting Financial Fraud with Machine Learning at Airbnb
Airbnb, the online marketplace that matches people who rent out their homes with people who are looking for a place to stay, uses machine learning (ML) techniques to fight financial fraud. They use targeted friction to battle the chargebacks while minimizing impact to good guests using their online reservation system.
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First Pedestrian Killed by Self-Driving Car
A pedestrian was killed on Sunday evening in Tempe, Arizona, by a self-driving car operated by Uber, the BBC reports. The firm confirmed that the vehicle was traveling in autonomous mode with a safety driver, the only vehicle occupant, behind the wheel during the crash.