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Cohere: Unlocking the Potential of Large Language Models (LLMs)

Posted Oct 21, 2022 | Views 2.1K
# TransformX 2022
# Fireside Chat
# Large Language Models (LLMs)
# Natural Language Processing (NLP)
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Aidan Gomez
Cofounder & CEO @ Cohere

Aidan Gomez is Cofounder and CEO at Cohere, a provider of cutting-edge NLP models that’s solving all kinds of language problems, including text summarization, composition, classification, and more. Prior to Cohere, Aidan co-authored the paper “Attention is All You Need,” which introduced the groundbreaking Transformer architecture. He also collaborated with a number of AI luminaries, including Geoff Hinton and Jeff Dean, during his time at Google Brain, where the team focused their efforts on large-scale machine learning. Based in Toronto, Aidan holds a B.S. in Computer Science from the University of Toronto, and is currently a doctoral student of Computer Science at the University of Oxford.

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SUMMARY

Aidan Gomez is the co-founder and CEO of Cohere, a provider of cutting-edge NLP models, and coauthor of "Attention is All You Need," one of the most-cited machine learning papers of all time, which introduced the world to the transformer architecture. Gomez and Scale CEO Alexandr Wang discuss this paper's impact on the world and how it has led to the creation of large language models (LLMs) such as GPT-3 and BLOOM.

While the current generation of LLMs is impressive, Gomez explains why they are not yet good enough for production applications and are inaccessible to most developers. He believes the industry must make it easy to access models and incorporate humans-in-the-loop to improve model performance so that the average developer without ML expertise can enrich their applications. In this fireside chat, Wang and Gomez also discuss trends to watch for, including providing AI with tools such as knowledge bases to augment its capabilities and the advent of multimodal models with text, images, video, and audio fused in one model. Gomez draws from his experience focusing on large-scale machine learning during his time at Google Brain, where he collaborated with many AI luminaries, including Geoff Hinton and Jeff Dean.

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