Remove Artificial Inteligence Remove Generative AI Remove Machine Learning Remove Serverless
article thumbnail

AWS at NVIDIA GTC 2024: Accelerate innovation with generative AI on AWS

AWS Machine Learning - AI

AWS was delighted to present to and connect with over 18,000 in-person and 267,000 virtual attendees at NVIDIA GTC, a global artificial intelligence (AI) conference that took place March 2024 in San Jose, California, returning to a hybrid, in-person experience for the first time since 2019.

article thumbnail

Build a contextual text and image search engine for product recommendations using Amazon Bedrock and Amazon OpenSearch Serverless

AWS Machine Learning - AI

Search engines and recommendation systems powered by generative AI can improve the product search experience exponentially by understanding natural language queries and returning more accurate results. A multimodal embeddings model is designed to learn joint representations of different modalities like text, images, and audio.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Leveraging Serverless and Generative AI for Image Captioning on GCP

Xebia

Leveraging Serverless and Generative AI for Image Captioning on GCP In today’s age of abundant data, especially visual data, it’s imperative to understand and categorize images efficiently. In our system, it’s the powerhouse behind generating the captions.

article thumbnail

Oracle makes its pitch for the enterprise cloud. Should CIOs listen?

CIO

This technology, leveraging artificial intelligence, offers a self-managing, self-securing, and self-repairing database system that significantly reduces the operational overhead for businesses.” These days that includes generative AI. The allure of such a system for enterprises cannot be overstated, Lee says. “We

article thumbnail

Serverless Image Generation Application Using Generative AI on AWS

Dzone - DevOps

But text-to-image conversion typically involves deploying an end-to-end machine learning solution, which is quite resource-intensive. What if this capability was an API call away, thereby making the process simpler and more accessible for developers?

article thumbnail

Vitech uses Amazon Bedrock to revolutionize information access with AI-powered chatbot

AWS Machine Learning - AI

Hosting large language models Vitech explored the option of hosting Large Language Models (LLMs) models using Amazon Sagemaker. Vitech needed a fully managed and secure experience to host LLMs and eliminate the undifferentiated heavy lifting associated with hosting 3P models.

article thumbnail

Use RAG for drug discovery with Knowledge Bases for Amazon Bedrock

AWS Machine Learning - AI

Knowledge Bases is completely serverless, so you don’t need to manage any infrastructure, and when using Knowledge Bases, you’re only charged for the models, vector databases and storage you use. RAG is a popular technique that combines the use of private data with large language models (LLMs).