Unlocking the Power of Large Language Models: Why Owning Your Own Model is Critical—and Within Reach


Large Language Models (LLMs) like ChatGPT have taken the world by storm with their ability to answer questions, write essays and even compose lyrics. These tools have profound implications for industries like financial services, retail, and healthcare. However, most organizations have yet to take advantage of LLMs. Why? The amount of compute, data, and knowledge required to build a proprietary model is daunting for many, yet the alternative is reliance on LLMs that are only accessible behind API paywalls and compromising your data privacy. In this keynote, we will explore why training, deploying, and owning your own LLM is critical (and at times even imperative). We will discuss how you can train and deploy your own models, while protecting your data and your business IP. Spoiler alert: in contrast to common wisdom, ownership of your own LLM is within reach for most organizations, and provides major benefits in increased security, flexibility, and accuracy.


Hagay Lupesko is the VP of Engineering at MosaicML, where he focuses on making generative AI training and inference efficient, fast, and accessible. Prior to MosaicML, Hagay held AI engineering leadership roles at Meta, AWS, and GE Healthcare. He shipped products across various domains: from 3D medical imaging, through global-scale web systems, and up to deep learning systems that power apps and services used by billions of people worldwide.

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