This is simply not true. In South Africa, one of the largest African economies, you cannot hold foreign currency unless you are traveling and then you have to sell it back within 30 days of returning to the country. You can open a foreign currency account with a minimum of eg R1500 which is half the monthly minimum wage. Then there are the exchange fees to talk about. You are oversimplifying.
Crypto is not as reliably anonymous as cash. Anything with a distributed ledger is pseudonymous so if one transaction can on your wallet can be linked to you, so can all other transactions, including historical ones, to that wallet.
... and I suppose the solution for these particular conditions is.... drumrolls... stablecoins? They are allowed? Available everywhere? Accepted everywhere? Totaly safe from disappearing overnight?
I taught myself assembly language from a book on a 286, I cracked games with SoftICE as a teenager, tried out every Linux distribution in the 90s, and have been developing software professionally for 2 decades. I prefer Cursor.
Am I an outlier or do you just judge people for weird reasons? I’ve never seen an IDE person judge a terminal person, it’s always the other way around - what’s up with that?
Where else are you going to get access to a real-time fresh high quality stream of human intelligence to grow your baby AGI? You can’t buy Codex, Claude, Copilot, so what’s left?
I find it gets you past the starting line but when you dig into the code it’s a mess of duplicated code, muddled responsibilities, poor architecture, 10k line files that eat your tokens, etc.
I’m building something using LLMs to scrape websites/socials for unstructured event data from combined text/images and the only way I’ve managed to get 100% consistent results for a reasonable cost is to break the task down into very small pieces that reduce the scope of mistakes significantly.
At present, for reasonable complex tasks, Codex/Claude will happily code you into an expensive corner.
Indeed. To add to this, the obvious solution (ask the AI to break down the tasks to whatever METR says they'd be capable of 80% of the time) is of limited utility, as the AI are only so-so at estimating task complexity.
(Even when they're getting the planning part right, I do also recommend checking the LLM-generated unit tests, because in my experience some of those are "regex the source code" not "execute functions and check outputs").
