A degree was never supposed to make someone instantly productive on day one. It was supposed to be paired with junior roles, mentoring, code review

I had a similar experience with unfamiliar frameworks. The less you understand the domain, the easier it is to accept clean-looking but wrong code

Good test actually : try explaining the solution without any hints. If you can't walk through why the code is structured that way, then the review was superficial

Ooh that's good advice! Very useful for everyone in my team. Appreciate it!

That's probably one of the most sustainable approaches. Queries like show me where to look for the problem often turn out to be more useful than just fix it for me, because they leave the most valuable part of the work to the engineer

Hardware scarcity and cloud incentives are real, but they're also part of the same broader trend: more dependency on centralized providers, less control for the buyer

Just don't design the game so that, when the business model stops working, every paid copy becomes a brick

i remember when multiplayer games could be connected to a user operated server.

the basic function of a multiplayer server is to keep the players game state synched, large numbers of players, and very fast gameplay vs connection rate and jitter is fly in ointment.

This is exactly what is happening right now. Models are becoming more efficient but at the same time users are starting to tackle tasks they previously didn’t even try to automate.

But Jevons paradox explains the increase in consumption, but it does not necessarily answer the question of business profitability

Maybe, maybe not. But his argument here is about cost, not profit. And on the cost front he is objectively wrong, and could easily see this if he cared to look. But he won’t since that would prevent him from making his bombastic content.

Well, the history of cloud computing shows that infrastructure usually becomes cheaper over time. But it’s still unclear whether this rule applies to reasoning models.

It seems to me that both sides are starting to drift into extremes. Some promised the replacement of half of office workers, while others are now saying that AI doesn’t create any value at all. The reality is somewhere in between

Also the article seems to be mixing two different things. The pricing as in

>allowed to burn thousands of dollars of tokens on a $39-a-month subscription

and whether the AI is worth it if you do pay what it costs.

I always thought the burn thousands of dollars of tokens without paying bit was unsustainable and harmful for the environment, electricity bills, investors and the like.

But I think it can do worthwhile stuff even if you pay. Like a small job I did was to get the emails of conference attendees off a website. It was tricky as they didn't want to be scrapped so I chatted to gemini and it helped figure out how to use tampermonkey and wrote a script. It was probably <$1 tokens and saved a couple of hours of mucking around. There must be a lot of things like that.

Sadly not quite one per wheel, though that would make the title even better

Self-balancing bicycles, sure. Self-driving bicycles that navigate city streets safely are a much larger problem.