InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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Microsoft Releases AI Training Library ZeRO-3 Offload
Microsoft recently open-sourced ZeRO-3 Offload, an extension of their DeepSpeed AI training library that improves memory efficiency while training very large deep-learning models. ZeRO-3 Offload allows users to train models with up to 40 billion parameters on a single GPU and over 2 trillion parameters on 512 GPUs.
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Microsoft Introduces Microsoft Build of OpenJDK
Microsoft has introduced a preview release of Microsoft Build of OpenJDK, a new open-source downstream distribution of OpenJDK. Microsoft Build of OpenJDK supports x64 server and desktop environments on macOS, Linux, and Windows. Bruno Borges, principal program manager, Java Engineering Group at Microsoft, spoke to InfoQ about Microsoft Build of OpenJDK.
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Google Announces the General Availability of A2 Virtual Machines
Recently, Google announced A2 Virtual Machines (VMs)' general availability based on the NVIDIA Ampere A100 Tensor Core GPUs in Compute Engine. According to the company, the A2 VMs will allow customers to run their NVIDIA CUDA-enabled machine learning (ML) and high-performance computing (HPC) scale-out and scale-up workloads efficiently at a lower cost.
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Google Bolsters Cloud Spanner with Point-in-Time Recovery
Google recently released a point-in-time-recovery feature for its Cloud Spanner database that aims to help protect against accidental data loss and corruption. The new point-in-time recovery (PITR) features seek to provide users more granular control over data recovery processes.
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Alibaba Announces 10 Billion Parameter Multi-Modal AI M6
Alibaba has created an AI model called Multi-Modality to Multi-Modality Multitask Mega-transformer (M6). The model contains 10 billion parameters and is pretrained on a dataset consisting of 1.9TB of images and 292GB of Chinese-language text. M6 can be fine-tuned for several downstream tasks, including text-guided image generation, visual question answering, and image-text matching.
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Google's Apollo AI for Chip Design Improves Deep Learning Performance by 25%
Scientists at Google Research have announced APOLLO, a framework for optimizing AI accelerator chip designs. APOLLO uses evolutionary algorithms to select chip parameters that minimize deep-learning inference latency while also minimizing chip area. Using APOLLO, researchers found designs that achieved 24.6% speedup over those chosen by a baseline algorithm.
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Google DeepMind’s NFNets Offers Deep Learning Efficiency
Google’s DeepMind AI company recently released NFNets, a normalizer-free ResNet image classification model that achieved a training performance of 8.7x faster than current state-of-the-art EfficientNet. In addition, it helps neural networks to generalize better.
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PyTorch 1.8 Release Includes Distributed Training Updates and AMD ROCm Support
PyTorch, Facebook's open-source deep-learning framework, announced the release of version 1.8 which includes updated APIs, improvements for distributed training, and support for the ROCm platform for AMD's GPU accelerators. New versions of domain-specific libraries TorchVision, TorchAudio, and TorchText were also released.
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.NET News Roundup - Week of March 15th, 2021
It's been a busy week for the .NET community, with the release of the new Azure SDK, multiple Akka.NET plugins, and the streaming of Include 2021, a digital event host by Microsoft focused on diversity and inclusion. InfoQ examined these and a number of smaller stories in the .NET ecosystem from the week of March 15th, 2021.
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Amazon Redshift Data Sharing Now Generally Available
Amazon has recently announced the general availability of the Amazon Redshift Data Sharing functionality to share live data across Amazon Redshift clusters. This allows the use of a single data warehouse cluster for multi-cluster deployments and sharing data instantly without the need to copy or move them.
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Amazon Redshift Cross-Database Queries and Data Sharing Are Now GA
Users of Amazon Redshift can now run cross-database queries and share data across Redshift clusters as AWS released these enhancements to general availability.
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Using Machine Learning in Testing and Maintenance
With machine learning, we can reduce maintenance efforts and improve the quality of products. It can be used in various stages of the software testing life-cycle, including bug management, which is an important part of the chain. We can analyze large amounts of data for classifying, triaging, and prioritizing bugs in a more efficient way by means of machine learning algorithms.
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Stanford Publishes AI Index 2021 Annual Report
Stanford University’s Institute for Human-Centered Artificial Intelligence (HAI) has published its AI Index annual report. This underlying data for this year's report has been expanded compared to the previous year's, and the report includes several perspectives on the COVID-19 pandemic's impact on AI research and development.
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DataStax Announces Astra Serverless Database-as-a-Service
DataStax , the company behind the Cassandra database, announced last week the general availability of Astra serverless, the open, multi-cloud serverless database-as-a-service (DBaaS).
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Amazon Lookout for Vision Now Generally Available
Amazon has recently announced the general availability of Amazon Lookout for Vision, an anomaly detection product that uses machine learning to process images to spot process defects and anomalies in manufactured products.