LLMOps for Enterprise: Key Challenges when Deploying at Scale
About this webinar
There’s a lot of hype flying around about Generative AI and LLMs. In this session, the Seldon technical team are here to cut through the noise and outline what you need to know about this technology.
Generative AI and LLMs are definitely buzzwords, but how can your organisation get value from these potentially game-changing technologies? In this session, the Seldon technical team are here to cut through the noise and outline what you need to know. They’ll dive into key opportunities and challenges of Generative AI and LLMs, as well as some of the best practice approaches we are beginning to see across industry.
Through leveraging LLMs, organisations can automate typical human tasks accurately, at scale and in a personalised way. It’s clear there’s game-changing potential in the technology, but what should organisations be wary of? The wide reach of this technology has sparked a number of challenges, including data privacy concerns, consistency issues and ethical or legal risks.
However, these advances in ML havMLOe unlocked seemingly endless use cases for enterprises. At Seldon, we’re already helping organisations to deploy LLMs and are helping our customers make this easier, cheaper and faster.
We’ve brought together experts from across the Seldon technical team, CTO Clive Cox, MLOps Engineer Sherif Akoush and Solutions Engineer Andrew Wilson, to tackle this tricky topic from all angles.
What you'll learn
- The key applications of LLMs across industries
- A guide to LLM Inference and the related trade-offs
- How to ensure memory optimization when deploying LLMs
- Implementing monitoring, debugging and auditing into these processes through LLMOps
- The common challenges in this space we’ve seen from our customers