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Leveraging Generative AI with Amazon Bedrock


  • Webcast


  • Amazon Bedrock

Generative Artificial Intelligence (AI) is currently on the crest of a wave, capturing the imagination and attention of tech enthusiasts, researchers, and industry leaders alike. The leading technology providers have been releasing tools to let customers take advantage of Generative AI. One of the most exciting is Amazon Bedrock which AWS released to general availability just last month.

Amazon Bedrock makes building Generative AI applications easier for developers as you can leverage foundation models from leading AI companies and serving them through APIs. Models like AI21 Labs’ Jurassic-2, Amazon’s Titan, Anthropic’s Claude, Cohere’s Command, Meta’s Llama 2, and Stability AI’s Stable Diffusion. Additionally, there are further benefits of Bedrock to discover:

Fully Managed Service: Say goodbye to infrastructure hassles. Bedrock offers a fully managed service, allowing you to focus on your AI projects, not server management.
Latest Model Access: Stay at the forefront of AI innovation with seamless access to the latest model versions.
Customization Flexibility: Tailor these models to your unique needs by fine-tuning them with your own data.

In this webcast, we explore Amazon Bedrock in-depth, discussing how it can enhance everyday business processes, making them more efficient and effective. We even provide a demonstration of the tool in action, showcasing its potential for your own business use cases.

Leveraging Generative AI with Amazon Bedrock (30 mins)

What we  cover:

  • Large language models (LLMs)
  • Amazon Bedrock and how it can benefit your business
  • A demo of Amazon Bedrock

Is this for you?

  • Are you interested in Artificial Intelligence (AI)? Are you interested in how AI can benefit your business?
  • Does your company use AWS services and you want to explore more cutting edge technology from AWS?
  • Do you want to take advantage of a number of foundation models created by leading companies such as Meta, Amazon, and Anthropic but you want an easy way to experiment with them without having to manage infrastructure or model version updates?