Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
How Generative AI Helps Predictive AI
 Originally published in Forbes, August 21, 2024 This is the...
4 Ways Machine Learning Can Perpetuate Injustice and What to Do About It
 Originally published in Built In, July 12, 2024 When ML...
The Great AI Myth: These 3 Misconceptions Fuel It
 Originally published in Forbes, July 29, 2024 The hottest thing...
Where FICO Gets Its Data for Screening Two-Thirds of All Card Transactions
 Originally published in The European Business Review, March 21,...
SHARE THIS:

2 years ago
AI And The Limits Of Language

 
Originally published in Noema, Aug 23, 2022.

When a Google engineer recently declared Google’s AI chatbot a person, pandemonium ensued. The chatbot, LaMDA, is a large language model (LLM) that is designed to predict the likely next words to whatever lines of text it is given. Since many conversations are somewhat predictable, these systems can infer how to keep a conversation going productively. LaMDA did this so impressively that the engineer, Blake Lemoine, began to wonder about whether there was a ghost in the machine.

Reactions to Lemoine’s story spanned the gamut: some people scoffed at the mere idea that a machine could ever be a person. Others suggested that this LLM isn’t a person, but the next perhaps might be. Still others pointed out that deceiving humans isn’t very challenging; we see saints in toast, after all.

But the diversity of responses highlights a deeper problem: as these LLMs become more common and powerful, there seems to be less and less agreement over how we should understand them. These systems have bested many “common sense” linguistic reasoning benchmarks over the years, many which promised to be conquerable only by a machine that “is thinking in the full-bodied sense we usually reserve for people.” Yet these systems rarely seem to have the common sense promised when they defeat the test and are usually still prone to blatant nonsense, non sequiturs and dangerous advice. This leads to a troubling question: how can these systems be so smart, yet also seem so limited?

To continue reading this article, click here.

 

2 thoughts on “AI And The Limits Of Language

Leave a Reply