Mind Matters Natural and Artificial Intelligence News and Analysis

Gary Smith

man-and-ai-robot-waiting-for-a-job-interview-ai-vs-human-com-680701487-stockpack-adobestock
Man and AI robot waiting for a job interview: AI vs human competition

The Job Market is Telling Us Something About AI and Jobs…

But it’s not telling us the same things as the AI hypesters are telling us
The job market for recent college grads may be warning us that participation trophies for college and ChatGPT use have long-run costs. Read More ›
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Transform photo stock management with AI reasoning models that enhance image perception and optimize digital asset organization.

No, Large Reasoning Models Do Not Reason

Large reasoning models continue the Large Language Model detour away from artificial general intelligence
It is increasingly recognized that, without extensive post-training, their authoritative answers are often remarkably bad. Read More ›
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Group of youth absorbed in smartphone screens

LLMs Are Bad at Good Things, Good at Bad Things

LLMs may well become smarter than humans in the near future but not because these chatbots are becoming more intelligent
As people become attached to and dependent on their AI friends, they become less interested in their fellow humans. Read More ›
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Unrecognizable woman student using chat bot on laptop

Yes, Large Language Models May Soon be Smarter than Humans…

But not for the reason you think
Too many students are not learning how to think and write; they are learning how to use LLMs — no matter that LLM responses cannot be trusted. Read More ›
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Mock code for an AI Large Language Model (LLM) that could intelligently answer questions. LLMs are one of the most popular implementations of recent Artificial Intelligence research

LLMs Still Cannot be Trusted for Financial Advice

The limitations of Large Language Models (chatbots) are illustrated by their struggles with financial advice
The real danger remains: we may think computers are smarter than us and consequently trust them to make decisions they should not be trusted to make. Read More ›
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Close up of an AI Artificial Intelligence GPU chip on motherboard. Concept of LLM, Large Language Models.

Large Language Models: A Lack-of-Progress Report

They will not be as powerful as either hoped or feared
LLMs are enormously expensive yet it is increasingly clear that they will never be reliable enough to be trusted in complex situations where mistakes are costly Read More ›
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Digital data stream analysis cyber environment visual display technology abstract perspective

Machine Learning Algos Often Fail: They Focus on Data, Ignore Theory

Without a theory, a pattern is just a pattern
The data-mining algorithms may recognize that a statistical pattern has vanished but won’t know why because they do not understand it as a logical relationship. Read More ›
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2 Seifenblasen

Yes, the AI Stock Bubble Is a Bubble

It's unfolding the way a financial bubble typically does
Unlike the Internet, LLMs are not useful enough to prompt customers to pay prices that reflect the hundreds of billions of dollars needed to develop them. Read More ›
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Person uses laptop interacting with AI virtual assistant. AI head graphic overlay laptop keyboard. Concept of AI prompt engineering, LLM. Person types on keyboard to communicate with virtual

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.
So far, AI is dragging down economic growth by diverting so much human talent and natural resources away from more productive uses. Read More ›
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Statistical illusion in TV game. Isometric illustration of undecided businessman on stairs with open doors. Modern landing page of making decision.

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
The danger is not that computers are smarter than us but that we think they are and thus trust them to make decisions they should not be trusted to make. Read More ›
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Group of jurors sitting together in jury box during trial

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
Someone blinded by confirmation bias might believe that robots and Go victories are evidence that ChatGPT would be a reliable lawyer. Read More ›
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Robotics or ai artificial intelligence connecting interaction with human.Chat bot software network.big data and transfer protocol system.Neuralink with smart brain.ai generative technology

Why LLMs (chatbots) Won’t Lead to Artificial General Intelligence

The biggest obstacle is seldom discussed: Most consequential real-world decisions involve uncertainty
LLMs can’t help when key decisions don’t feature objectively correct probabilities but rather subjective probabilities that need interpretation. Read More ›
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Game of Tic-tac-toe with cinnamon and tangerine on a black background

Some Lessons From DeepSeek, Compared With Other Chatbots

I tested OpenAI o1, Copilot, and Gemini Flash, along with DeepSeek, on a question about Tic-Tac-Toe
Here’s the problem with the use case for LLMs: If you know the answer, you don’t need to ask an LLM; if you don’t know the answer, you can’t trust one. Read More ›
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Man working with stock market data.

Sloppy Science is a Statistical Sin

Evidence of sloppy science encourages readers to wonder if the entire research project is compromised
Journals should require authors to make their data available online before publication and encourage others to try to replicate the research they publish. Read More ›
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large language models Concept illustration Ai

AGI Is Not Already Here. LLMs Are Still Not Even Intelligent

Recent tests continue to show huge failures in comprehending common sense issues
In one test, for example — not understanding the situation — Open AI launched an extremely verbose and confused description of the situation. Read More ›
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Generative AI : A visually striking graphic that is split into two halves. On one side, depict a traditional library or database to symbolize Large Language Models

Large Language Models (LLMs) Flunk Word Game Connections

Despite hype, ChatGPT and its competitors, in all their iterations, are still just text-generators based on statistical patterns in the text databases they train on
Identification of statistical patterns in text that Large Language Models (LLMs) do not understand is not going to give us AGI, let alone superintelligence. Read More ›
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LLM, AI Large Language Model concept. Businessman use tablet and laptop with LLM icons. A language model distinguished by its general-purpose language generation capability. Chat AI.

The Promise of Artificial General Intelligence is Evaporating

Revenue from corporate adoption of AI continues to disappoint and, so far, pales in comparison to the revenue that sustained the dot-com bubble — until it didn’t
Recognition is growing that fundamental challenges make LLMs unreliable. Increasingly expensive scaling will likely hasten the popping of the AI bubble. Read More ›
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Blue and green turf meets futuristic stadium lights as football players clash, pixelated projectiles in flight, technology merging with old-school gridiron glory.

Do Fantasy Sports Tell Us Something About Artificial Intelligence?

My biggest takeaway from my own involvement is how well fantasy football illuminates some weaknesses of artificial intelligence (AI)
AI models are really good at finding patterns in data but they are bad at deciding whether these spotted patterns can be used to make reliable predictions. Read More ›
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Vintage baseball on a weathered American flag

The World Series of Coin Flips

Here we go again with the annual coin-flipping ritual known as the World Series
With the Yankees and Dodgers so evenly matched, this World Series will be somewhat like a coin-flipping contest. That's the paradox of luck and skill. Read More ›
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Businessman forecasting a crystal ball

P-Hacking: The Perils of Presidential Election Models

History professor Alan Lichtman’s model uses 13 true/false questions reflecting likely voter interests. But some of them seem rather subjective
Lichtman’s Thirteen Keys to the White House prediction model for the presidency shows some evidence of p-hacking, as does Helmut Norpoth’s Primary Model. Read More ›