Build conversational AI experiences powered by LLMs with Vertex AI Conversation and Dialogflow CX

Published on ‎09-25-2023 08:55 AM by Community Manager

Conversational interfaces are among the most widely-applicable generative AI use cases. Whether you’re setting up chatbots in just a few steps or creating deep customizations and conversation flows, Google Cloud Dialogflow CX - now with Generative AI features - and Vertex AI Conversation provide tools that make it easy for your business to create personalized richer experiences for both employees and customers.

In this session, join Google Cloud Champion Innovator and Google Developer Expert in Machine Learning, Xavier Portilla Edo, and Developer Advocate, Alessia Sacchi, to learn: 

  • The latest Generative AI features in Vertex AI Conversation and Dialogflow CX
  • How to combine traditional agent design techniques and best practices with Google's latest generative large language models (LLMs) to create complex conversational applications that are prepared to handle the many different ways that users might interact with it
  • Examples of tasks that Conversational AI, Search and LLMs can solve for, including demos 

You’ll also have the opportunity to ask questions and receive answers live from the experts.

Please complete this form to register for the event. Once registered, you'll receive a calendar invite via email. Even if you can't make it live, register and we'll send you a link to the recording. 

Thank you - we hope to see you there!



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Start:
Tue, Oct 24, 2023 09:00 AM PDT
End:
Tue, Oct 24, 2023 10:00 AM PDT
2 Comments
mohamed67421
Bronze 2
Bronze 2

Great work 

NukeOfWar
New Member

What would be nice is a steady processor for rending, compiling, generating, writing, semantically, at a controlled axiomatic rate, that renders itself as some category of sets within classes with closure - or not...then just permutes itself within it's own gradient-radiant permeable space.

I mean simple analyzing GNU's Locales in such a way...would do a thing or two if allowed to TryCatch in a sandbox...until a bijection of co & domain establish a instrumented efficiency difference of sets...then just rotate the linked-list until you are back at the head...and copy paste that sector and the code into-out of...there is where you are fining the gradient of permeable space to permute into PE metric result sets...
I promise....Vs Code, GitHub, if anyone is there yet...they holding back a 1 -3-2 -KO...fing darpa.

https://github.com/2652660/Mathematics/
https://github.com/2652660/Catalog/

❤️working on it bosses. gonna go watch some ffm,,,ttyl noob