CategoryLarge Language Models (LLMs)
AI Ascends — But Not Above Its Teachers
LLMs are tools, able to augment human accomplishment in extraordinary ways. But to call them intelligent in the same way we describe human minds is a mistake
AI Large Language Models: Real Intelligence or Creative Thievery?
AI lacks originality because it cannot originate. It can only borrow. This is as true of impressive chatbots (large language models or LLMS) as of all other types
Yes, Large Language Models May Soon be Smarter than Humans…
But not for the reason you think
LLMs Still Cannot be Trusted for Financial Advice
The limitations of Large Language Models (chatbots) are illustrated by their struggles with financial advice
Large Language Models: A Lack-of-Progress Report
They will not be as powerful as either hoped or feared
Machine Learning Algos Often Fail: They Focus on Data, Ignore Theory
Without a theory, a pattern is just a pattern
Analysts: AIs Are Often Wrong But Never Uncertain
Gary Marcus and Ernest Davis note that getting AIs to admit uncertainty is "one of the most important *unsolved* challenges" in the field
AI Peer Review Called “Inevitable” by Some, “Disaster” by Others
The whole debate raises a question: How much original thought goes into peer review anyway? And what purpose does it ultimately serve?
Yes, the AI Stock Bubble Is a Bubble
It's unfolding the way a financial bubble typically does
Chatbots Alone Together: “Let’s Skip the Small Talk …”
Did you know that humans empower AI bots to confer with each other in Gibberlink code? Nothing could go wrong with that, right?...
Why LLMs Are Not Boosting Productivity
If LLMs were as reliably useful as economist Tyler Cowen alleges, businesses would be using them to generate profits faster than LLMs generate text. They aren’t.
Intelligence Requires More Than Following Instructions
Post-training improves the accuracy and usefulness of LLMs but does not make them intelligent in any meaningful sense — as the Monty Hall problem shows
How the Father of Information Theory Invented Modern AI
In 1948 Claude Shannon used Andrey Markov’s 1906 process to formulate an appproach that enabled the development of chatbots (large language models)
The Large Language Model (LLM) “Superpower” Illusion Dies Hard
Historic confirmation bias around ESP and spirit cabinets makes for an interesting comparison with the current need to believe in the abilities of LLMs
Why LLMs (chatbots) Won’t Lead to Artificial General Intelligence
The biggest obstacle is seldom discussed: Most consequential real-world decisions involve uncertainty
Unequal Profits: Why AI Needs Successful Applications
Readers may be surprised to learn that these widely touted AI advances are not making their developers much money
DeepSeek: Honing In on the Challenges It Presents
Although the program is admirably streamlined, censorship, data breaches, copyright violation, and lack of guardrails are among the most prominent challenges
Gen AI: A Neutral Tool? Let’s Look More Closely
All technologies change us. Some technologies change us in ways where the harms far outweigh any benefits.