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Fine-Tuning Open AI’s GPT-3.5 to Unlock Enterprise Use Cases

Posted Nov 07, 2023 | Views 6.5K
Colin Jarvis
Solutions Architect @ OpenAI

Colin is a product-minded solutions architect who works with customers to solve their most complex problems using OpenAI’s cutting edge AI technology. Colin brings a unique mix of business and technical skills, coming from roles as both product owner and developer across clients in the Financial Services, Oil and Gas, Health & Social Care and Government sectors. Colin is currently based in Glasgow.

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Luv Kothari
Head of Product, Enterprise Generative Platform @ Scale AI

Luv Kothari is the Head of Product for all Enterprise efforts at Scale AI, where he is focused on developing and deploying cutting-edge Generative AI solutions for large enterprises. Previously, Luv led the Google Assistant on Android, and grew the product from 10M to 500M monthly users. Prior to Google, Luv was a consultant at Bain & Company and a Product Manager at Broadcom. He holds an MBA from Berkeley, an MS from UIUC and a B.Tech from IIT. Luv is a named inventor on more than 25 patents in AI, ML, security and consumer applications.

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Chloe Ho
GTM Strategic Accounts @ Scale AI

Chloe Ho is a go-to-market leader covering strategic accounts at Scale AI, with a focus on generative AI products. Her expertise lies in datasets needed for gen AI model training, and evaluative products such as Test & Evaluation and Red Teaming. Previously, she led the Sales Ops and Strategy team, scaling the GTM team from 30 to 60, and was the first Biz Ops and Strategy hire at Scale. Prior to that, she was a Data Scientist at Razorfish and an Equity Associate at Morgan Stanley. She holds an MBA from Harvard Business School and BA/Bsc from the University of Pennsylvania, and is based in New York.

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About the Tech Talk Fine-tuning is the key to unlocking the performance of LLMs for every organization’s most critical use cases. Join OpenAI and Scale as we explore what it takes to optimize fine-tuning for your organization and how you can unlock the potential of your data. From this talk, you will learn:

When you should consider fine-tuning GPT-3.5 and how to get started Optimizing your proprietary data for fine-tuning GPT-3.5 and how to tell when you need to generate new data Lessons learned and best practices from helping the world's leading enterprises fine-tune GPT-3.5 for their most difficult use cases

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