LLMOps for Your Data: Best Practices to Ensure Safety, Quality, and Cost

Search:

DAY

WEEK

MONTH

YEAR

Select your country:
Sign up | Log in

Large Language Models (LLMs) such as ChatGPT offer unprecedented potential for complex enterprise applications. However, productionizing LLMs comes with a unique set of challenges such as model brittleness, total cost of ownership, data governance and privacy, and the need for consistent, accurate outputs. Putting the right LLMOps process in place today will pay dividends tomorrow, enabling you to leverage the part of AI that constitutes your IP – your data – to build a defensible AI strategy for the future.

Join Travis Addair, CTO of Predibase, and Shreya Rajpal, Co-Founder and CEO at Guardrails AI, in this exclusive webinar to learn:

How guardrails can be used to mitigate risks and enhance the safety and efficiency of LLMs, delving into specific techniques and advanced control mechanisms that enable developers to optimize model performance effectively
Why implementing safeguards can significantly improve the development process of LLMs, ultimately leading to safer, more reliable, and robust real-world AI applications
The hidden costs of commercial LLM APIs, and how your data can be leveraged as an asset to transition towards a more defensible and robust AI strategy built atop open source AI over time
Benefits and practical solutions for effectively fine-tuning and productionizing task-specific LLMs to improve model quality, reduce latency, and decrease total cost of ownership

January 18th, 2023 at 9:30am PST, 12:30pm EST, 5:30pm GMT

Brought to you by:

Shreya Rajpal, Co-Founder and CEO at Guardrails AI & Travis Addair, Co-Founder and CTO at Predibase

Shreya Rajpal is the creator and maintainer of Guardrails AI, an open source platform developed to ensure increased safety, reliability, and robustness of large language models in real-world applications. Her expertise spans a decade in the field of machine learning and AI. Most recently, she was the founding engineer at Predibase, where she led the ML infrastructure team. In earlier roles, she was part of the cross-functional ML team within Apple's Special Projects Group and developed computer vision models for autonomous driving perception systems at Drive.ai.

Travis Addair is co-founder and CTO of Predibase, the fastest and most efficient platform to fine-tune and serve open-source LLMs. He is lead maintainer of Horovod, the open-source distributed deep learning framework, and is a co-maintainer of Ludwig, the open-source declarative deep learning framework. He previously led Uber’s deep learning infrastructure team as part of the Michelangelo machine learning platform.

Product Management Today