Editor’s note: Kevin Karty is CEO of Intuify, a Boston-based market research firm.
Throughout my 20-year career in data science, I was an AI skeptic. When companies bragged about the AI in their software, I cringed in embarrassment. At best, it was glorified machine learning. At worst, flat out deception.
Inevitably, the hype went bust: AI-backed hedge funds underperformed human managers (who in turn underperformed index funds). Sentiment coding tools still couldn’t understand phrases like, “That game is sick!”
When I first tried ChatGPT 3.0 (we’re on 4.0 at the time writing this article) I expected to be disappointed. I was shocked. ChatGPT is going to force radical change in our industry. No, it won’t destroy marketing research, but there will be winners and losers. The difference will be determined by how well companies and individuals adapt.
Image adapted and updated from Pablo Villalobos, Jaime Sevilla, Tamay Besiroglu, Lennart Heim, Anson Ho and Marius Hobbhahn. “Machine Learning Model Sizes and the Parameter Gap.” ArXiv [Cs.LG], 2022. arXiv. http://arxiv.org/abs/2207.02852.
Before diving in, let’s first understand the issue: How are large language models (LLMs) like ChatGPT different from traditional AI?
LLMs represent humanity’s first significant step away from narrow AI toward general AI.
AI’s implications are far reaching. Everyone will be affected. In this article I’ll share a list of some changes we can predict in the next few years.
By some estimates, 73% of marketers in the U.S. use some sort of generative AI to create content for their jobs – writing e-mails, blog posts, taglines, etc. Reasonable estimates indicate that these tools enhance productivity by 37% to 60%. We’re already at a place where if you don’t use ChatGPT and similar tools, you are at a distinct disadvantage compared to your peers.
Want a quick starter surv...