It's hard to explain, but AI mostly doesn't get the nuance of my thinking right. I'll read a response and right away know it's a non-answer for my purposes. If I get a "hit" then it's often by luck. And so, I use it mostly for anything other than direct answers, such as research, etc. Beyond that, it's not much different than old school Google result. So, no, I don't offload my thinking.

Hand wavy list just to get a general idea...

1) Give me a condensed summary 2) Is this adding anything to what we already have? (I save good articles along with annotations and whatever notes I may write to go along with it.) 3) Locate any upstream ideas on this (often AI articles are rehashing much better written ideas.) ...

Something like that. Not that I have some great system for it. I find these articles are so full of fluff that I have lost patience to attempt to get through them. So, I pull out the AI to parse the AI. I know that the AI may miss some hidden gems, but I'm okay with that.

1) A lot of companies simply won't trust Chinese models

2) These companies will still trust a direct frontier provider over a non Chinese company hosting Chinese models.

3) Frontier model providers working with cloud hosting providers for data residency.

4) Hosting your own models is expensive (hardware, people to setup and maintain, risk of little to no return.) And smaller companies likely won't go this route.

5) As mentioned in the article, a good but cheap model can still be expensive if it takes longer to do a task. I imagine I could save days doing work with Fable vs using Chinese models.

ETA: And loads of demand. Not sure the pricing situation is yet settled. As Chinese models get more popular, they may have to raise their prices as well. US models may struggle more with meeting demand rather than getting margins squeezed.

https://om.co/2018/01/18/dean-allen-rest-in-peace/

Edit to add: Just use Deepseek Flash 4. You can hit those servers all day for next to nothing and still scratch the itch to build useless things. ;)

This is also why it's difficult to make money selling to consumers. They run different calculations than enterprise buyers.

I imagine a huge number of people were just browsing for quick answers and then bailed as I did.

And how many years have we had capable AI? Maybe it's going to take a similar timeline for people to figure out how to be good with an AI assisted workflow (if not fully automated.)

ETA: It's interesting how the bottleneck may reveal the real skill in the thing. Architecting the code. Having a eye for interestingness in creating an image / painting of something, etc.

https://en.wikipedia.org/wiki/Explorers_(film)

Tariffs

War in the Middle East

US economy that would likely be in recession if not for massive datacenter spend

Oil at ~$100

But we're laying people off because... AI

SO... a map is static reference. A calculator is deterministic computation. An LLM is probabilistic generation

In high-stakes environments like military planning, tools that generate new claims rather than reference known data introduce a different class of risk.

Yes, everyone is responsible for their own decisions. But then circle back to risk. How can the planners be sure they aren't dealing with hallucinations, questionable data, differing outputs based on prompts, and a long list of other things...