Geek Stuff category archive

Brine for your brain? It’s the real dill.

Therapeutic? Bwaaa-haaaa-haaaa-haaaa.

Properly secured? Not according to security expert Bruce Schneier.

Mageia v. 9 with the Plasma desktop. The wallpaper is from my collection.

Trustworthy? That bridge in Brooklyn is still on the market.

Along those lines, you might want to listen to Harry Shearer’s conversation with Gary Marcus on this week’s episode of Le Show. It starts at about the eight minute mark.

Aside:

We recently watched The Matrix.

Methinks they got it wrong.

Machines didn’t subordinate mankind. Mankind seems quite willing, eager even, to subordinate themselves to the machines.

Fodder for the easily fooled? All too often.

At Psychology Today Blogs, Cornelia C. Walther looks at why person may tend to fall for AI generated mis- and disinformation. She points out that

Perhaps most concerning is our inherent vulnerability to what psychologists term “automation bias”—our tendency to trust machine-generated content more than human-created material. This cognitive bias creates a perfect storm for AI manipulation. We trust AI-generated content partly because we don’t recognize it as AI-generated, and partly because we assume machines are more objective than humans.

Recent studies reveal that people consistently underestimate AI’s persuasive capabilities, making them more vulnerable to manipulation. When survey participants were told content was AI-generated, their resistance increased significantly. However, in real-world scenarios, AI-generated persuasive content is rarely labeled as such, leaving audiences defenseless against sophisticated psychological manipulation.

She goes on to offer some techniques to fend off falsehoods.

I think you will find it worth your while.

Trustworthy? I’ve still got that bridge for sale in Brooklyn.

Fomenting folderol? Well, garbage in, garbage out, as Steven J. Vaughan-Nichols reports at El Reg. Here’s a bit of his article:

Welcome to Garbage In/Garbage Out (GIGO). Formally, in AI circles, this is known as AI model collapse. In an AI model collapse, AI systems, which are trained on their own outputs, gradually lose accuracy, diversity, and reliability. This occurs because errors compound across successive model generations, leading to distorted data distributions and “irreversible defects” in performance. The final result? A Nature 2024 paper stated, “The model becomes poisoned with its own projection of reality.”

In related news, in this week’s Le Show, Harry Shearer reports on how big tech’s fascination with AI is leading to record levels of usage of electricity and of water to cool data centers. The relevant portion starts at about the 38-minute mark.

Also, too.

Intellectually stimulating? Let’s talk about the bridge I’ve got for sale in Brooklyn.

Competent legal advisor? Not according to this judge.

The new blow-up dall? No air pump needed, baby!

Functionally illiterate? Judge for yourself.

The dialog: Hey, I got an acetylene torch in the truck.

The closed caption: Hey, I got a zeppelin torch in the trunk.