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From LLM Mess to LLM Mesh: Building Scalable AI Applications

Dataiku

At Dataiku Everyday AI events in Dallas, Toronto, London, Berlin, and Dubai this past fall, we talked about an architecture paradigm for LLM-powered applications: an LLM Mesh. What actually is an LLM Mesh? How does it help organizations scale up the development and delivery of LLM-powered applications?

IT 52
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Understanding the Why and How of the LLM Mesh Architecture

Dataiku

field engineer at Dataiku, discussed the common challenges of IT leaders when implementing large language models (LLMs) at scale. They also discussed the solution by introducing us to the Dataiku LLM Mesh architecture. Let's delve into the essence of this webinar.

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Introducing the LLM Mesh: A Common Backbone for Generative AI Applications

Dataiku

The answer is yes, via the LLM Mesh — a common backbone for Generative AI applications that promises to reshape how analytics and IT teams securely access Generative AI models and services.

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AI agents: The next stage in the evolution of enterprise AI

CIO Business Intelligence

Unlike traditional AI chatbots or simple copilots for SaaS products , AI agents leverage the full range of LLM capabilities. An AI agent is an LLM-powered system that pursues specific goals within defined autonomy boundaries and uses various tools. They can not only generate text, but also solve complex problems (almost) independently.

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Benefits of the LLM Mesh, Part 1: Decoupling Application From Service Layer

Dataiku

At Everyday AI New York last September, Dataiku CTO and co-founder Clément Stenac shared our vision for the LLM Mesh , a common backbone for Generative AI applications in the enterprise.

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Benefits of the LLM Mesh, Part 2: Enforcing a Secure API Gateway

Dataiku

With Generative AI top of mind for many companies, IT leaders have been tasked with figuring out how to make the most of this new technology through pilot use cases and experimentation.

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Introducing LLM Cost Guard, the Newest Addition to the LLM Mesh

Dataiku

When it comes to Large Language Models (LLMs) , many IT team leaders are trying to get a handle on the question “How much will it all cost?”