InfoQ Homepage Machine Learning Content on InfoQ
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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AWS Announces DataZone, a New Data Management Service to Govern Data
At AWS re:Invent, Amazon Web Services announced Amazon DataZone, a new data management service that makes it faster and easier for customers to catalog, discover, share, and govern data stored across AWS, on-premises, and third-party sources.
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Galactica: Large Language Model for Scientific Knowledge
Meta AI and Papers with Code recently released Galactica, a 120-billion-parameter scientific-language model which can search and summarize academic literature, solve math problems, and write scientific code. Galactica’s architecture is based on a transformer, an attention mechanism which draws global dependencies between input and output.
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Google Open-Sources Secure ML Operating System KataOS
Google's AmbiML team recently open-sourced KataOS, a provably secure operating system for embedded ML hardware. KataOS is based on the seL4 microkernel and is implemented in Rust. Along with KataOS, Google is releasing Sparrow, a reference implementation of the operating system targeted for a secure hardware platform based on the RISC-V architecture.
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Instagram Notification Management Now Uses Causal Inference Instead of Click-through Rate
Instagram has changed the way of creating notifications, moving from CTR to causal inference and ML models to identify highly active users who are likely to receive the notifications.