AFAIK all efforts in that direction were way too costly a few years back and degraded models considerably. Spotify, for the longest time, only trained on an equivalent of manually curated playlists by experts and users to understand similarity.
There's good points the author makes about problems in interviews + some economical facts but pieces like:
> Sorry, you’re not qualified to be a professional software developer because you wore the wrong color shirt to the interview. You should know the color buleruplange is triggering to generation delta
Just make me feel like I wouldn't like to work with this person.
It's 6B down the drain. Saying grok 1.5 is competitive is a joke, if it was any good it would be ranked well in chatbot arena (https://chat.lmsys.org/). Elon is a master in hyping underperforming things and this is no exception.
How is it serious if money is the motor of freedom of speech? The suing culture in the US ensures freedom of speech up until you bother someone with money.
Quite frankly, I see a lot of text in this post and no numbers.
For something to be production-ready I'd expect you to at least cover major things like "latency to serve x in Elixir instead of lang y is k% better" or "EMFU we got when training x in Elixir was comparable to lang y".
These are two random metrics that are of course biased to my experience but the article just feels empty without numbers.
Absolutely would not work in the US (as, unfortunately, most public services). There's already a huge lobby from TurboTax and other players. All countries that got to this level of automation already had publicly developed, free software for tax payers previously.
Not everything has to be clear and to the point. The sentence's murkiness adds emotion to the text. I'm not a native speaker (just like the writer isn't) and maybe that's why we're not so bothered.
But this comment is exactly what I expected from HN.