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Artwork for No Priors: Artificial Intelligence | Technology | Startups
No Priors: Artificial Intelligence | Technology | Startups · Nov 21, 2024 · 44 min

Model Plateaus and Enterprise AI Adoption with Cohere's Aidan Gomez

In this episode of No Priors, Sarah is joined by Aidan Gomez, cofounder and CEO of Cohere. Aidan reflects on his journey to co-authoring the groundbreaking 2017 paper, “Attention is All You Need,” during his internship, and shares his motivations for building Cohere, which delivers AI-powered language models and solutions for businesses. The discussion explores the current state of enterprise AI adoption and Aidan’s advice for companies navigating the build vs. buy decision for AI tools. They also examine the drivers behind the flattening of model improvements and discuss where large language models (LLMs) fall short for predictive tasks. The conversation explores what the market has yet to account for in the rapidly evolving AI ecosystem, as well as Aidan’s personal perspectives on AGI—what it might look like and when it could arrive. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @AidanGomez Show Notes: 0:00 Introduction 0:36 Co-authoring “Attention is all you need” 2:27 Leaving Google and founding Cohere 4:04 Cohere’s mission and models 6:15 Pitfalls of current AI 8:14 How enterprises are deploying AI today 10:58 Build vs. buy strategy for AI tools 14:37 Barriers to enterprise adoption 20:04 Which types of companies should pretrain models? 24:25 Addressing flaws in open-source models 25:12 Current and expected progress in scaling laws 29:54 Advances in multi-step problem solving and reasoning 32:29 Key drivers behind the flattening curve of model improvements 36:25 Exploring AGI 39:59 Limitations of LLMs 42:10 What the market has mispriced

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show notes

In this episode of No Priors, Sarah is joined by Aidan Gomez, cofounder and CEO of Cohere. Aidan reflects on his journey to co-authoring the groundbreaking 2017 paper, “Attention is All You Need,” during his internship, and shares his motivations for building Cohere, which delivers AI-powered language models and solutions for businesses. The discussion explores the current state of enterprise AI adoption and Aidan’s advice for companies navigating the build vs. buy decision for AI tools. They also examine the drivers behind the flattening of model improvements and discuss where large language models (LLMs) fall short for predictive tasks. The conversation explores what the market has yet to account for in the rapidly evolving AI ecosystem, as well as Aidan’s personal perspectives on AGI—what it might look like and when it could arrive.


Sign up for new podcasts every week. Email feedback to show@no-priors.com

Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @AidanGomez


Show Notes:

0:00 Introduction

0:36 Co-authoring “Attention is all you need”

2:27 Leaving Google and founding Cohere

4:04 Cohere’s mission and models

6:15 Pitfalls of current AI 

8:14 How enterprises are deploying AI today

10:58 Build vs. buy strategy for AI tools

14:37 Barriers to enterprise adoption 

20:04 Which types of companies should pretrain models?

24:25 Addressing flaws in open-source models

25:12 Current and expected progress in scaling laws

29:54 Advances in multi-step problem solving and reasoning

32:29  Key drivers behind the flattening curve of model improvements 

36:25 Exploring AGI

39:59 Limitations of LLMs

42:10 What the market has mispriced

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