Remove Artificial Inteligence Remove Examples Remove Generative AI
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LLM benchmarking: How to find the right AI model

CIO

But how do companies decide which large language model (LLM) is right for them? But beneath the glossy surface of advertising promises lurks the crucial question: Which of these technologies really delivers what it promises and which ones are more likely to cause AI projects to falter?

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Extend large language models powered by Amazon SageMaker AI using Model Context Protocol

AWS Machine Learning - AI

For MCP implementation, you need a scalable infrastructure to host these servers and an infrastructure to host the large language model (LLM), which will perform actions with the tools implemented by the MCP server. To create an MCP server, we use the official Model Context Protocol Python SDK.

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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

Organizations are increasingly using multiple large language models (LLMs) when building generative AI applications. Although an individual LLM can be highly capable, it might not optimally address a wide range of use cases or meet diverse performance requirements.

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Have we reached the end of ‘too expensive’ for enterprise software?

CIO

Generative artificial intelligence ( genAI ) and in particular large language models ( LLMs ) are changing the way companies develop and deliver software. Instead of manually entering specific parameters, users will increasingly be able to describe their requirements in natural language.

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Build and deploy a UI for your generative AI applications with AWS and Python

AWS Machine Learning - AI

The emergence of generative AI has ushered in a new era of possibilities, enabling the creation of human-like text, images, code, and more. Solution overview For this solution, you deploy a demo application that provides a clean and intuitive UI for interacting with a generative AI model, as illustrated in the following screenshot.

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Reimagine application modernisation with the power of generative AI

CIO

2] The myriad potential of GenAI enables enterprises to simplify coding and facilitate more intelligent and automated system operations. By leveraging large language models and platforms like Azure Open AI, for example, organisations can transform outdated code into modern, customised frameworks that support advanced features.

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AI in action: How enterprises are scaling AI for real business impact

CIO

To capitalize on the enormous potential of artificial intelligence (AI) enterprises need systems purpose-built for industry-specific workflows. Strong domain expertise, solid data foundations and innovative AI capabilities will help organizations accelerate business outcomes and outperform their competitors.