InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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Find Solutions to Your Software Challenges at QCon Plus
Last November at QCon Plus, over 1,450 of your peers joined us at the virtual event in order to keep on top of software trends and find solutions to validate their technical roadmaps. Now is the time to book your attendance at the next event! With less than five weeks before QCon Plus May 2021, over 1,800 senior software engineers, architects, and team leads have already booked their spot.
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Facebook Announces ZionEX Platform for Training AI Models with 12 Trillion Parameters
A team of scientists at Facebook AI Research (FAIR) announced a system for training deep-learning recommendation models (DLRM) using PyTorch on a custom-built AI hardware platform, ZionEX. Using this system, the team trained models with up to 12T parameters and achieved nearly an order-of-magnitude speedup in training time compared to other systems.
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AWS Introduces Savings Plans and Instant Price Reductions for Amazon Sagemaker
Recently, AWS announced instant price reductions and Savings Plans for Amazon SageMaker, their fully-managed Machine Learning (ML) service. With Savings Plans for Amazon SageMaker, customers can benefit from cost savings up to 64% compared to the on-demand price. The company also drops the price of several instance families in Amazon SageMaker by up to 14.2%.
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Open Source AI Can Predict Electrical Outages from Storms with 81% Accuracy
A team of scientists from Aalto University and the Finnish Meteorological Institute have developed an open-source AI model for predicting electrical outages caused by storm damage. The model can predict storm location within 15km and classifies the amount of transformer damage with 81% accuracy, allowing power companies to prepare for outages and repair them more quickly.
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MIT Announces AI Benchmark ThreeDWorld Transport Challenge
A team of researchers from MIT and the MIT-IBM Watson AI Lab have announced the ThreeDWorld Transport Challenge, a benchmark task for embodied AI agents. The challenge is to improve research on AI agents that can control a simulated mobile robot that is guided by computer vision to pick up objects and move them to new locations.
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Perceiver: One Neural-Network Model for Multiple Input Data Types
Google’s DeepMind company has recently released a state-of-the-art deep-learning model called Perceiver that receives and processes multiple input data ranging from audio to images, similarly to how the human brain perceives multimodal data. Perceiver is able to receive and classify input multiple data types, namely point cloud, audio and images.
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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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Live Webinar presented by Cockroach Labs |
Q&A moderated by InfoQ
This webinar dives deep into the internals of CockroachDB, exploring how the database uses KV at the storage layer to effectively distribute data, how Raft and MVCC are used to guarantee serializable isolation for transactions, how to tie data to a location to help with performance, and more.