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David Berrio, our Senior AI/ML Engineer, will take you step by step on how to deploy an LLM locally on your machine using a RAG (Retrieval-Augmentation Generation) model architecture.
Why is this important?
Many enterprises are moving from POC to scaling and tools like ChatGPT can become cost-prohibitive and don’t allow as much flexibility. Plus infosec teams don’t like relying on API-based models like chatGPT.
Open-source models are quickly closing the gap.
By deploying LLMs locally you can test and fine-tune with different LLMs before shifting them to your cloud instance or on-prem.
PS. Services like AWS and Azure provide GPU options needed to scale these LLM models.
David Berrio is a seasoned professional in AI and Data Science with extensive expertise in developing and deploying machine learning algorithms, leveraging a strong command of MLOps and Microservices. His career features significant experience in Computer Vision, Machine Learning, Azure Cloud, and state-of-the-art Deep Learning Architectures. A lifelong learner, David is always at the forefront of technology. He believes in the power of knowledge to drive innovation and deliver impactful solutions, guiding his professional endeavors.
Jerrik Arango is a Principal Software Engineer at HatchWorks, renowned for his leadership and commitment to innovation. He excels in transforming ideas and processes, building cohesive teams, and creating frictionless user experiences. His broad expertise spans back-end and front-end development, UX, and architecture. Jerrik specializes in developing web applications that empower users to maximize the benefits of technology. Committed to excellence, he is dedicated to bringing visions to life and delivering exceptional, best-in-class results.
HatchWorks embraces Gen AI through our Generative-Driven Development™ method.
Our hands-on approach and deep understanding of the current technological landscape uniquely position us to guide you through this revolution.
Contact us today to learn more.
