Improving LLM Quality, Speed and Cost with Dynamic Routing
The Data Phoenix team invites you to our upcoming webinar, which will take place on August 1 at 10 a.m. PT.
Topic: Improving LLM Quality, Speed and Cost with Dynamic Routing
Speakers: Daniel Lenton (CEO at Unify)
Participation: free (but you’ll be required to register)
In this talk, we explore how we can improve the performance of LLM applications by dynamically routing each prompt to the most appropriate model, whilst balancing user preferences for quality, speed and cost. Further, we will demonstrate how a custom trained router can continually improve over time, by training on the stream of data being processed by the live application. We will demonstrate this for RAG applications and also for co-pilot applications, and we will also explore how the router training scales with dataset size, and explore some of the shortcomings of the approach. See you there!
Speaker
Daniel Lenton is the founder and CEO at Unify, on a mission to accelerate AI development and deployment by unifying the fragmented AI stack. Prior to founding Unify, Daniel was a PhD student in the Dyson Robotics Lab, where he conducted research at the intersection of Machine Learning, Computer Vision and Robotics. During this time, he also worked at Amazon on their drone delivery program. Prior to this, he completed his Masters in Mechanical Engineering at Imperial College, with Dean's list recognition.
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