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Large Language Model at Scale

Posted May 13, 2023 | Views 829
# Large Language Models
# LLM in Production
# Cohere.ai
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Nils Reimers
Director of Machine Learning @ Cohere

Nils Reimers is highly recognized throughout the AI community for creating and maintaining the now-famous Sentence Transformers library (www.SBERT.net) used to develop, train, and use state-of-the-art LLMs. The project has 900+ stars on GitHub and 30M+ installations.

Nils is currently the Director of Machine Learning at Cohere where he leads the team that develops and trains Large Language Models (LLM) with billions of parameters. Prior to Cohere, Nils created and led the science team for Neural Search at HuggingFace. Nils holds a Ph.D. in Computer Science from UKP in Darmstadt.

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Demetrios Brinkmann
Chief Happiness Engineer @ MLOps Community

At the moment Demetrios is immersing himself in Machine Learning by interviewing experts from around the world in the weekly MLOps.community meetups. Demetrios is constantly learning and engaging in new activities to get uncomfortable and learn from his mistakes. He tries to bring creativity into every aspect of his life, whether that be analyzing the best paths forward, overcoming obstacles, or building lego houses with his daughter.

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Abi Aryan
Machine Learning Engineer @ Independent Consultant

Abi is a machine learning engineer and an independent consultant with over 7 years of experience in the industry using ML research and adapting it to solve real-world engineering challenges for businesses for a wide range of companies ranging from e-commerce, insurance, education and media & entertainment where she is responsible for machine learning infrastructure design and model development, integration and deployment at scale for data analysis, computer vision, audio-speech synthesis as well as natural language processing. She is also currently writing and working in autonomous agents and evaluation frameworks for large language models as a researcher at Bolkay.

Prior to consulting, Abi was a visiting research scholar at UCLA working at the Cognitive Sciences Lab with Dr. Judea Pearl on developing intelligent agents and has authored research papers in AutoML and Reinforcement Learning (later accepted for poster presentation at AAAI 2020) and invited reviewer, area-chair and co-chair on multiple conferences including AABI 2023, PyData NYC ‘22, ACL ‘21, NeurIPS ‘18, PyData LA ‘18.

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SUMMARY

Large Language Models with billions of parameters have the possibility to change how we work with textual data. However, running them on scale at potentially hundred millions of texts a day is a massive challenge.

Nils talks about finding the right model size for respective tasks, model distillation, and promising new ways on transferring knowledge from large to smaller models.

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