InfoQ Homepage Machine Learning Content on InfoQ
-
Microsoft Open-Sources Approximate Nearest Neighbor Search Algorithm Powering Bing
Microsoft's latest contribution to open source, Space Partition Tree And Graph (SPTAG), is an implementation of the approximate nearest neighbor search (NNS) algorithm that is used in Microsoft Bing search engine.
-
Google Releases Google-Landmarks-V2, a Large-Scale Dataset for Landmark Recognition & Retrieval
Google has released Google-Landmarks-v2, an improved dataset for Landmark Recognition & Retrieval, along with Detect-to-Retrieve, a Tensorflow codebase for large-scale instance-level image recognition. Two companion Kaggle competitions based on Google-Landmarks-v2 were also launched. With over 200,000 landmarks in 5 million images, it is the largest landmark dataset ever published.
-
Amazon Updates SageMaker Ground Truth with New Labeling Features, Vendor Support and Availability
Amazon announced that SageMaker Ground Truth now offers simplified labeling workflows, support for additional labeling vendors, and is available in the Asia Pacific (Sydney) AWS region – bringing the total to six supported AWS regions in the Americas, Europe, and Asia.
-
Google Launches AI Platform - an End-to-End Platform to Build, Run, and Manage ML Projects
Google has recently launched AI Platform, an end-to-end platform to build, test, and deploy machine learning models. It brings together a host of products and services to help businesses solve complex challenges using AI in a way that is easier and collaborative.
-
Google Scales Weak Supervision to Overcome Labeled Dataset Problem
Google recognizes that the need for labeled data in machine learning (ML) is a significant bottleneck and recently adapted the open-source Snorkel framework to overcome the problem at scale. Google enhanced Snorkel by integrating it with Tensorflow, using the file system for sharing data instead of a database, and creating separate executables for labeling functions.
-
Teaching the Computer to Play the Chrome Dinosaur Game with TensorFlow.js Machine Learning Library
A simple, yet entertaining and useful for educational purposes application of machine learning, was recently made available on Fritz's HeartBeat Medium publication. Google's machine learning TensorFlow.js library is leveraged in the browser to teach the computer to play the Chrome Dinosaur Game.
-
Salesforce Adds Intelligence to its Einstein Services Offering
In a recent press release, Salesforce announced additions to their Einstein platform that target bringing AI solutions to Salesforce developers and admins using a low code, point and click configuration-based solution. The recent additions to the platform include Einstein Translation and Einstein Optical Character Recognition (OCR).
-
How the Sequence of Characters in a Name Can Predict Race and Ethnicity
Gaurav Sood, Principal Data Scientist at Microsoft, recently spoke at the AnacondaCon 2019 Conference on how to use the sequence of characters in a person's name to predict that person's race and ethnicity, using machine learning techniques.
-
AWS Releases Enhancements to AI Services for NLP, Speech-to-Text Transcription, and Image Detection
Amazon Web Services (AWS) released new features for three of its AI services: Amazon Comprehend, Amazon Rekognition, and Amazon Transcribe.
-
Google Expands ML Kit, Adds Smart Reply and Language Identification
In a recent Android blog post, Google announced the release of two new Natural Language Processing (NLP) features for ML Kit, including Language Identification and Smart Reply. In both cases, Google is providing domain-independent APIs that help developers analyze and generate text, speak and other types of Natural Language text.
-
NSFW.js: Machine Learning Applied to Indecent Content Detection
With the beta-released NSFW.js, developers can now include in their applications a client-side filter for indecent content. NSFW.js classifies images into one of five categories: Drawing, Hentai, Neutral, Porn, Sexy. Under some benchmarks, NSFW categorizes images with a 90% accuracy rate.
-
Google Open-Sources GPipe Library for Faster Training of Large Deep-Learning Models
Google AI is open-sourcing GPipe, a TensorFlow library for accelerating the training of large deep-learning models.
-
Prashanth Southekal on Applied Machine Learning
Prashanth Southekal, managing principal at DBP Institute, hosted a workshop last month at Enterprise Data World 2019 Conference, on applied machine learning techniques and when to use different ML algorithms.
-
Bringing Intelligence to Enterprise Content Management, Google Releases Document Understanding AI
At the recent Google Cloud Next Conference, Google announced a new beta machine learning service, called Document Understanding AI. The service targets Enterprise Content Management (ECM) workloads by allowing customers to organize, classify and extract key value pairs from unstructured content, in the enterprise, using Artificial Intelligence (AI) and Machine Learning (ML).
-
Amazon Expands Its Machine Learning Offering with AWS Deep Learning Containers
Recently, Amazon introduced AWS Deep Learning Containers (AWS DL Containers), which are Docker images pre-installed with deep learning frameworks allowing customers to deploy custom machine learning environments quickly.