I learnt orienteering in ninth grade because the outdoors demands to be taken seriously. My class quite enjoyed it. We hiked parts of the Appalachian Trail on our own without worry because we knew what to do and where we were at all times. None of this was difficult.
If/when it does there will be mass layoffs because the ideal business has no human employees.
The purpose of AI is to replace humans by facilitating legal constructive dismissal. Businesses are willing to invest enormous sums to be rid of workers.
No different than any other corporate spin about the inflexibility or uselessness of their platform. AWS does this quite well. "Undifferentiated heavy lifting" - while ignoring the absurd complexity and beta quality of their own services. Every issue I have with their shit, I experience a new and different bug or incorrectness in their documentation, and it takes years for it to get corrected. There are still bugs in Lambda that I discovered and reported 5+ years ago which haven't been resolved.
At every level. They must be using claude to make their business decisions, too.
It's not only being demonstrated, it's being reveled in. Astounding.
I don't know if this is just the symptom of the AI bubble, cronyism, or "late stage capitalism" (even though the resemblance to capitalism long since ceased). But it's a mess.
20 years ago, these guys would've been tried for criminality by now. Both Anthropic and OpenAI. They're making Enron look like amateurs.
I'm glad I am not the only one who found that film insufferable.
I'm glad the plague of 1990s "we're going to make a retard the hero" movies came to an end. Unfortunately, now we're plagued with them directing the films.
Still overkill but not remotely impractical. Sending a "whole computer" would be no more difficult than shipping tiny PCs to Ebay buyers who often buy several at once for our "home lab" style setups.
A typical tiny PC plus power brick and its cord easily fits in a flat rate box (though for Important Stuff best sent next day air).
Congratulations, you just reimplemented REST with additional steps.
explore practical ways to reduce our petroleum footprint beyond simply driving less or buying a more efficient vehicle. By looking at where petroleum is actually used—from transportation to food production—the discussion challenges conventional advice and highlights lifestyle changes that can have a far greater impact.
Instead of focusing on sacrifice, are there solutions that improve quality of life while dramatically reducing petroleum consumption? Sharing resources, growing food, shortening supply chains, and building stronger local communities can reduce thousands of gallons of petroleum use each year, demonstrating that regenerative living can be both more resilient and more rewarding.
What few manufacturing jobs are left in the United States are under threat from humanoid robots. Reducing the supply of cheap, subsidized exports slows the almost-inevitable process of replacing human workers with robots.
Why? China needs exports more than anyone else needs imports. Exports carry their entire economy. Domestic demand has collapsed.
That's a model specific problem, to a large degree.
The "AI assumed something stupid and destructive" problem went away when I started using better planning skills and models which were not anthropic's.
I've not had any of those "wild destructive hallucination reasoning" problems with GLM or Qwen models, even small versions, which I fought with regularly with opus.
Sure, you can do that. You can do that with buggy code that compiles, or python, too.
For AI, you can also have another agent and/or model review and fix it. You can ask it adversarial questions until you get it right. You can ask it to explain the architecture and design (or: you can plan it out ahead of time so that you know the design and then verify it).
It's no different than starting on an existing code base... just faster.
Whom the gods would destroy, they first teach BASIC.
