Top 6 Kubernetes use cases

Kubernetes, the world’s most popular open-source container orchestration platform, is considered a major milestone in the history of cloud-native technologies. Developed internally at Google and released to the public in 2014, Kubernetes has enabled organizations to move away from traditional IT infrastructure and toward the automation of operational tasks tied to the deployment, scaling and …

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Implement real-time personalized recommendations using Amazon Personalize

At a basic level, Machine Learning (ML) technology learns from data to make predictions. Businesses use their data with an ML-powered personalization service to elevate their customer experience. This approach allows businesses to use data to derive actionable insights and help grow their revenue and brand loyalty. Amazon Personalize accelerates your digital transformation with ML, …

Accelerating generative AI around the world with new data residency guarantees

Demand for enterprise-ready generative AI services is increasing around the world. As companies look to leverage generative AI to the fullest, many want to be able to control where their data is stored in light of growing data sovereignty and global regulatory requirements. For this reason, we’re announcing that customers using Google Cloud’s generative AI …

Gen AI for the Genome: LLM Predicts Characteristics of COVID Variants

A widely acclaimed large language model for genomic data has demonstrated its ability to generate gene sequences that closely resemble real-world variants of SARS-CoV-2, the virus behind COVID-19. Called GenSLMs, the model, which last year won the Gordon Bell special prize for high performance computing-based COVID-19 research, was trained on a dataset of nucleotide sequences …

New study finds bigger datasets might not always be better for AI models

From ChatGPT to DALL-E, deep learning artificial intelligence (AI) algorithms are being applied to an ever-growing range of fields. A new study from University of Toronto Engineering researchers, published in Nature Communications, suggests that one of the fundamental assumptions of deep learning models—that they require enormous amounts of training data—may not be as solid as …

Extracting Histogram of Gradients with OpenCV

Besides the feature descriptor generated by SIFT, SURF, and ORB, as in the previous post, the Histogram of Oriented Gradients (HOG) is another feature descriptor you can obtain using OpenCV. HOG is a robust feature descriptor widely used in computer vision and image processing for object detection and recognition tasks. It captures the distribution of …

Image Feature Extraction in OpenCV: Keypoints and Description Vectors

In the previous post, you learned some basic feature extraction algorithms in OpenCV. The features are extracted in the form of classifying pixels. These indeed abstract the features from images because you do not need to consider the different color channels of each pixel, but to consider a single value. In this post, you will …