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

No Priors: Artificial Intelligence | Technology | Startups

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.

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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