InfoQ Homepage Machine Learning Content on InfoQ
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Unsupervised Object Detection and Semantic Segmentation Using Deep Learning
Meta AI released CutLER, a state-of-the-art zero-shot unsupervised object detector which improves detection performance by over 2.7 times on 11 benchmark datasets for different domains like video frames, painting, sketches, etc. This model’s simplicity allows compatibility with different object-detection architectures across different domains.
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Google Unveils MusicLM, an AI That Can Generate Music from Text Prompts
Google researchers have introduced MusicLM, an AI model that can generate high-fidelity music from text. MusicLM creates music at a constant 24 kHz throughout a number of minutes by modeling the conditional music generating process as a hierarchical sequence-to-sequence modeling problem.
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Doordash Introduces ML to Understand the Marketplaces Status
DoorDash introduces an ML model to predict the operational status of a store in order to increase the user experience and save thousands of orders cancellation. Understanding the merchant’s operational status and the ability to receive and fulfill orders is crucial for the DoorDash platform.
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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.
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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.
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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.
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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.
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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.