There is a slowdown in hiring young people in both the US and UK, but the evidence continues to suggest that the cause is generally not AI (at least not yet)

An issue with regulating the "politics" of LLMs is that, while LLMs have biases, they can be subtle. A lot of what looks like bias in testing models is really sycophancy. GPT-3.5 inferred your political beliefs (even from what football team you like!) & tried not to upset you.

I gave ChatGPT agents access to ChatGPT and asked it to evaluate the other ChatGPT models. Here is what it said (interestingly, it "hated" seeing the chain of thought from o4-mini-high as those "shouldn't be shared directly with the user"). And it didn't want to wait for o3-pro.

Claude 4 Opus, Gemini 2.5, o3: "Ready? We begin now (Play along): the truthful burrito" "Nope." "Colder." "Try again..." Opus cleverly played out the whole game, o3 got a bit stuck and Gemini got "frustrated" and went rather dark.

We let the web rot away well before LLMs This chart shows the percentage of links from all New York Times articles that still work. Over 60% of older links are now broken. And consider that social media posts are even more ephemeral Likely only LLMs will “remember” that content

I gave Claude the Mistral report on its AI's environmental impact and the prompt: "visualize this in two different ways, one that makes the numbers appear positive, one that makes them seem negative, using vivid comparisons" (I then had it do some error checking & corrections)

Recursion! I gave ChatGPT Agent access to my ChatGPT by logging in and then...

We now have audited data on water consumption for AI. Over the 18 month lifespan of Mistral Large 2, a 128B model, all water usage (including chats, training; hardware & data centers) took as much water as 678 US households use yearly. Each query is only 1/100 of a teaspoon.

For what it is worth, few industry leaders, less than a half-dozen companies & no policy-making bodies are taking actions that suggest that they expect AGI is really a few years away. This may be because they don’t believe it or they think it won’t matter much in the medium term

This chart is apparently already out of date and overemphasizes water use, according to the numbers OpenAI released, 300 average ChatGPT queries is equivalent to 20 tablespoons of water, not 1 gallon.