​ . One of the ways to import data into MongoDB is by using mongoimport command, which allows you to import data from a variety of formats, including CSV files. This article will focus on the ways to import a CSV file using mongoimport command… Read More »Import CSV file using mongoimport in MongoDB AQSA Spark By {Examples}

​ The rise of text and semantic search engines has made ecommerce and retail businesses search easier for its consumers. Search engines powered by unified text and image can provide extra flexibility in search solutions. You can use both text and images as queries. For… Read More »Implement unified text and image search with a CLIP model using Amazon SageMaker and Amazon OpenSearch Service Kevin Du AWS Machine Learning Blog

​ Amazon Kendra is an intelligent search service powered by machine learning (ML). We are excited to announce the launch of Amazon Kendra Featured Results. This new feature makes specific documents or content appear at the top of the search results page whenever a user… Read More »Promote search content using Featured Results for Amazon Kendra Maran Chandrasekaran AWS Machine Learning Blog

​ How to update objects in the document array in MongoDB? We can use the $ positional operator in combination with the updateOne() or updateMany() method to update objects in an array in MongoDB. The $ positional operator allows us to update the first array… Read More »Update Objects in the Array in MongoDB AQSA Spark By {Examples}

​ Digital publishers are continuously looking for ways to streamline and automate their media workflows in order to generate and publish new content as rapidly as they can. Many publishers have a large library of stock images that they use for their articles. These images… Read More »Automatic image cropping with Amazon Rekognition Mark Watkins AWS Machine Learning Blog

​ MLPerf remains the definitive measurement for AI performance as an independent, third-party benchmark. NVIDIA’s AI platform has consistently shown leadership across both training and inference since the inception of MLPerf, including the MLPerf Inference 3.0 benchmarks released today. “Three years ago when we introduced… Read More »NVIDIA Takes Inference to New Heights Across MLPerf Tests Dave Salvator – Archives Page 1 | NVIDIA Blog

​ The 2020 release of GPT-3 served as a compelling example of the advantages of training extremely large auto-regressive language models. The GPT-3 model has 175 billion parameters—a 100-fold increase over the GPT-2 model—performed exceptionally well on various current LLM tasks, including reading comprehension, answering… Read More »Meet BloombergGPT: A Large Language Model With 50 Billion Parameters That Has Been Trained on a Variety of Financial Data Aneesh Tickoo Artificial Intelligence Category – MarkTechPost