InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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Google Published Results on How ML-Enhanced Code Compilation Could Improve Developers’ Productivity
The rapid advances in natural language processing (NLP) opened a new direction to use deep learning models in providing smarter suggestions for developers while writing software codes. Google AI has recently published results on ML-enhanced code compilation and how it improved developers’ productivity considering different metrics.
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Amazon Announces New Capabilities on Local Environments for SageMaker Canvas and Pipelines
Amazon is announcing multiple capabilities for SageMaker, including expanded capabilities to better prepare and analyze data for machine learning, faster onboarding with automatic data import from local disk in SageMaker Canvas, and the testing of machine learning workflows in local environments for SageMaker Pipelines.
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Berkeley Researchers Announce Robot Training Algorithm DayDreamer
Researchers from University of California, Berkeley, recently announced DayDreamer, a reinforcement-learning (RL) AI algorithm that uses a world model, which allows it to learn more quickly without the need for interacting with a simulator. Using DayDreamer, the team was able to train several physical robots to perform complex tasks within only a few hours.
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New Stanford Compute-In-Memory Chip Promises to Bring Efficient AI to Low-Power Devices
In a paper recently published in Nature, Stanford researchers presented a new compute-in-memory (CIM) chip using resistive random-access memory (RRAM) that promises to bring energy efficient AI capabilities to edge devices.
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Amazon's AlexaTM 20B Model Outperforms GPT-3 on NLP Benchmarks
Researchers at Amazon Alexa AI have announced Alexa Teacher Models (AlexaTM 20B), a 20-billion-parameter sequence-to-sequence (seq2seq) language model that exhibits state-of-the-art performance on 1-shot and few-shot NLP tasks. AlexaTM 20B outperforms GPT-3 on SuperGLUE and SQuADv2 benchmarks while having fewer than 1/8 the number of parameters.
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Azure Optimized Stack with DeepSpeed for Hyperscale Model Training
Azure Machine Learning (AzureML) now provides an optimized stack that uses the latest NVIDIA GPU technology with Quantum InfiniBand to efficiently train and fine-tune large models like Megatron-Turing and GPT-3.
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AWS Adds Coding Assistant CodeWhisperer to Lambda Console
AWS recently announced the preview of Amazon CodeWhisperer in the AWS Lambda console. Available as a native code suggestion feature in the code editor, the new functionality of the coding assistant can make code recommendations during Lambda function definition.
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Meta Develops Dataset Pruning Technique for Scaling AI Training
Researchers from Meta AI and Stanford University have developed a metric for pruning AI datasets which improves training scalability from a power-law to exponential-decay. The metric uses self-supervised learning and performs comparably to existing metrics which require more compute power.
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Machine Learning Systems Vulnerable to Specific Attacks
The growing number of organizations creating and deploying machine learning solutions raises concerns as to their intrinsic security, argues the NCC Group in a recent whitepaper (Practical Attacks on Machine Learning Systems).
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Uber Open-Sourced Its Highly Scalable and Reliable Shuffle as a Service for Apache Spark
Uber engineering has recently open-sourced its highly scalable and reliable shuffle as a service for Apache Spark. Spark is one of the most important tools and platforms in data engineering and analytics. It is shuffling data on local machines by default and causes challenges while the scale is getting very large. Shuffle as a service is a solution developed at Uber for this problem.
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Amazon Comprehend Announces the Reduction of the Minimum Requirements for Entity Recognition
Amazon is announcing that they lowered the minimal requirements for training a recognizer with plain text CSV annotation files as a result of recent advances in the models powering Amazon Comprehend. Now, you just need three documents and 25 annotations for each entity type to create a unique entity recognition model.
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Google Introduces Zero-ETL Approach to Analytics on Bigtable Data Using BigQuery
Recently, Google announced the general availability of Bigtable federated queries, with BigQuery allowing customers to query data residing in Bigtable via BigQuery faster. Moreover, the querying is without moving or copying the data in all Google Cloud regions with increased federated query concurrency limits, closing the longstanding gap between operational data and analytics.
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Meta's Genomics AI ESMFold Predicts Protein Structure 6x Faster Than AlphaFold2
Meta AI Research recently announced ESMFold, an AI model for predicting protein structure from a sequence of genes. ESMFold is built on a 15B parameter Transform model and achieves accuracy comparable to other state-of-the-art models with an order-of-magnitude inference time speedup.
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Write Directly from Cloud Pub/Sub to BigQuery with BigQuery Subscription
Recently Google introduced a new type of Pub/Sub subscription called a “BigQuery subscription,” allowing to write directly from Cloud Pub/Sub to BigQuery. The company claims that this new extract, load, and transform (ELT) path will be able to simplify event-driven architectures.
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PrefixRL: Nvidia's Deep-Reinforcement-Learning Approach to Design Better Circuits
Nvidia has developed PrefixRL, an approach based on reinforcement learning (RL) to designing parallel-prefix circuits that are smaller and faster than those designed by state-of-the-art electronic-design-automation (EDA) tools.