Category: FAANG

Posted by Ameya Velingker, Research Scientist, Google Research, and Balaji Venkatachalam, Software Engineer, Google Graphs, in which objects and their relations are represented as nodes (or vertices) and edges (or links) between pairs of nodes, are ubiquitous in computing and machine learning (ML). For example, social networks, road networks, and molecular structure and interactions are …

Read more “Exphormer: Scaling transformers for graph-structured data”

In today’s data-driven world, the ability to leverage real-time data for machine learning applications is a game-changer. Two key players in this field, Striim and Google Cloud with BigQuery, offer a powerful combination to make this possible. Striim serves as a real-time data integration platform that seamlessly and continuously moves data from diverse sources to …

Read more “Real-time data processing for machine learning with Striim and BigQuery”

Mark Swinnerton aims to fight climate change by transforming abandoned mines into storage tanks of renewable energy. The CEO of startup Green Gravity is prototyping his ambitious vision in a warehouse 60 miles south of Sydney, Australia, and simulating it in NVIDIA Omniverse, a platform for building 3D workflows and applications. The concept requires some …

Read more “Buried Treasure: Startup Mines Clean Energy’s Prospects With Digital Twins”

by Peter Wilczynski, Product Lead for the Ontology System “Show me the incentive and I’ll show you the outcome” — Charlie Munger I. As an industry, we are producing more software at an ever-increasing rate and yet the impact of this software on economic productivity has been marginal. This lack of progress is inherent to how the software industry …

Read more “Ontology-Oriented Software Development”

Amazon Textract is a machine learning (ML) service that enables automatic extraction of text, handwriting, and data from scanned documents, surpassing traditional optical character recognition (OCR). It can identify, understand, and extract data from tables and forms with remarkable accuracy. Presently, several companies rely on manual extraction methods or basic OCR software, which is tedious …

Read more “Build a vaccination verification solution using the Queries feature in Amazon Textract”

In this post, we demonstrate how to use neural architecture search (NAS) based structural pruning to compress a fine-tuned BERT model to improve model performance and reduce inference times. Pre-trained language models (PLMs) are undergoing rapid commercial and enterprise adoption in the areas of productivity tools, customer service, search and recommendations, business process automation, and …

Read more “Reduce inference time for BERT models using neural architecture search and SageMaker Automated Model Tuning”