InfoQ Homepage Machine Learning Content on InfoQ
-
GitHub Releases Copilot for Business amid Ongoing Legal Controversy
GitHub has announced Copilot for Business, a business plan for their OpenAI-powered coding assistant Copilot. The release follows a recent class action lawsuit against Microsoft, GitHub, and OpenAI for violating open-source licenses.
-
Grafana Adds Outlier Detection to Its Machine Learning Toolkit
Grafana has released outlier detection as part of their Grafana Machine Learning toolkit. Outlier detection can be used to monitor a group of similar things and be alerted when some of them start to behave differently than the norm.
-
eBay New Recommendations Model with Three Billion Item Titles
eBay developed a new recommendations model based on Natural Language Processing (NLP) techniques and in particular on BERT model. This new model, called “ranker,” uses the distance score between the embeddings as a feature; in this way the information in the titles of the products is analyzed from the semantic points of view.
-
Waymo Developed Collision Avoid Test to Evaluate Its Autonomous Driver
Waymo developed a testing framework called Collision Avoidance Test (CAT) to evaluate the ability to avoid crush or potential hazard situations of its Waymo Driver, compared to a human driver.
-
Six Essential Tracks at QCon London, March 27-29, 2023: Architecture, FinTech, ML, and More!
QCon London international software conference returns this March 27-29 with its 17th edition. Technical leaders who are driving innovation and change in software will share the latest trends and techniques from their real-world projects to help you solve common challenges. Learn about emerging trends in 2023, how to adopt them, how to avoid pitfalls, and how to embrace the best practices.
-
Amazon Releases Fortuna, an Open-Source Library for ML Model Uncertainty Quantification
AWS announced that Fortuna, an open-source toolkit for ML model uncertainty quantification, has been made generally available. Any trained neural network can be used with the calibration methods offered by Fortuna, such as conformal prediction, to produce calibrated uncertainty estimates.
-
Meta Releases data2vec 2.0 a High Efficiency Self-Supervised Model
Meta has released version 2.0 of Data2Vec, a self-supervised algorithm that can learn in the same way from three different modalities: speech, vision, and text, and achieves the same accuracy of the other computer vision models but 16x faster. The code and pretrained models are also shared with the other researchers.
-
How Twitter Automated Data Quality Check Process
Twitter engineering has recently shared a blog post on how they architected and developed a quality automation platform. Twitter digests and creates thousands of data sets for different data products and applications. The next natural step is to make sure of the quality of the data by adding automation on top of it. In this news post, we explore this architecture in more detail.
-
AWS Makes it Simpler to Share ML Models and Notebooks with Amazon SageMaker JumpStart
AWS announced that it is now easier to share machine learning artifacts like models and notebooks with other users using SageMaker JumpStart. Amazon SageMaker JumpStart is a machine learning hub that helps users accelerate their journey into the world of machine learning.
-
NVIDIA Kubernetes Device Plug-in Brings Temporal GPU Concurrency
Starting from the v12 release, the Nvidia GPU device plug-in framework started supporting time-sliced sharing between CUDA workloads on Kubernetes. This feature aims to prevent under-utilization of GPU units and make it easier to scale applications by leveraging concurrently-executing CUDA contexts.
-
Wayve's End-to-End Deep Learning Model for Self-Driving Cars
Wayve released a state-of-the-art end-to-end model for learning a world model and vehicular driving policy based on simulation data from CARLA, allowing autonomy to cars without HD maps. Wayve’s new Model-based Imitation Learning (MILE) is a machine-learning model, specifically a reinforcement learning architecture, that learns a model of the world and a driving policy during offline training.
-
Meta MultiRay Allows Efficiency on Large-Scale AI Models
Meta developed MultiRay, a platform that allows the cost-effective running state-of-the-art machine learning models. MultiRay allows models to run on the same input in order to share the majority of the running cost with a little addictive cost per model.
-
Recap of AWS re:Invent 2022
After a virtual-only event in 2020 and a reduced-size 2021 edition, re:Invent was back last week in Las Vegas with over 50,000 attendees for the 11th edition. During multiple sessions and keynotes at the largest AWS yearly conference, the cloud provider announced new services and features, with the focus more on business solutions and data options than new building blocks.
-
Apple Adds Core ML Support for Stable Diffusion on Apple Silicon
Apple released a set of optimizations to Core ML to enable running the Stable Diffusion text-to-image model on Apple Silicon-powered devices running the latest iOS or macOS versions, respectively iOS 16.2 and macOS 13.1.
-
Open Source SkyPilot Targets Cloud Cost Optimization for ML and Data Science
A team of researchers at the RISELab at UC Berkeley recently released Skypilot, an open-source framework for running machine learning workloads on the major cloud providers through a unified interface. The project focuses on cost optimization automatically finding the cheapest availability zone, region, and provider for the requested resources.