In this light, Bastian’s story hits harder now than ever and I can’t help but see him as an avatar for mediocrity, wastefulness, and a society without the capacity for empathy.

In other words: You’re the middle segment in a human-AI centipede.

If the basic idea is to get the most utility out of chatbots, it seems counterintuitive to train them to waste tokens and time outputting polite language. 

Chatbots don’t actually exist. No, we’re not trying to create a conspiracy theory. What we mean is this: large language models (LLMs) aren’t “entities” or “beings.”

A team of researchers at RespAI Lab, KIIT Bhubaneswar, KIMS Bhubaneswar, and Monash University, Australia today published a fascinating preprint research paper that takes a mighty bludgeon to the notion that AI can predict medical diagnosis. 

LLMs are too stupid to be useful for professional work, but that won’t stop content creators from shooting themselves in the foot with it.

Here’s a fun way to spend 10 minutes: try to think of something ChatGPT, Gemini, Claude, or Grok might output to convince you they’re capable of thought, agency, or sentience. 

The American Enterprise Institute, a conservative think tank, recently joined the chorus of economists who believe Donald Trump’s global trade tariffs were calculated wrong. According to multiple sources, the formula used contains a math error that exaggerates its effectiveness by a factor of four.

In two new papers, Anthropic describes a new methodology by which developers are attempting to peek under the models’ hoods to discern exactly what’s occurring inside.

Recent comments from world-renowned British computer scientist Stuart Russell indicates that the sector of AI developers and organizations dedicated to scaling large language models to “human-level” may have reached that point, financially speaking.