Author: AI Generated Robotic Content

Amazon SageMaker provides a suite of built-in algorithms, pre-trained models, and pre-built solution templates to help data scientists and machine learning (ML) practitioners get started on training and deploying ML models quickly. These algorithms and models can be used for both supervised and unsupervised learning. They can process various types of input data, including tabular, …

Read more “Churn prediction using Amazon SageMaker built-in tabular algorithms LightGBM, CatBoost, TabTransformer, and AutoGluon-Tabular”

Many machine learning (ML) use cases, like fraud detection, ad targeting, and recommendation engines, require near real-time predictions. The performance of these predictions is heavily dependent on access to the most up-to-date data, with delays of even a few seconds making all the difference. But it’s difficult to set up the infrastructure needed to support …

Read more “Enabling real-time AI with Streaming Ingestion in Vertex AI”

New cloud services to support AI workflows and the launch of a new generation of GeForce RTX GPUs featured today in NVIDIA CEO Jensen Huang’s GTC keynote, which was packed with new systems, silicon, and software. “Computing is advancing at incredible speeds, the engine propelling this rocket is accelerated computing, and its fuel is AI,” …

Read more “Keynote Wrap-Up: NVIDIA CEO Unveils Next-Gen RTX GPUs, AI Workflows in the Cloud”

Recommender systems, the economic engines of the internet, are getting a new turbocharger: the NVIDIA Grace Hopper Superchip. Every day, recommenders serve up trillions of search results, ads, products, music and news stories to billions of people. They’re among the most important AI models of our time because they’re incredibly effective at finding in the …

Read more “Why the New NVIDIA Grace Hopper Superchip Is Ideal for Next-Gen Recommender Systems”