We already live in a post-GPT3 world, but one where all its power is the hands of a private company.

The conversation needs to move on whether making it open and democratic is a good idea, but the tech itself is here to stay.

EleutherAI’s unofficial motto is “anything safe enough for Microsoft to sell for profit is safe enough to release.” You’re kidding yourself if you think Microsoft cares who they sell it to.

There are worthwhile conversations to have about democratizing technology, but this stuff is already out there regardless of what you or I do.

Kemper is an amazing product, one of the few true innovations in guitar gear in ages.

However, it still fails to model the response of a nice tube amp to dynamics. It gets close, but not quite there.

This is why people like Paul Gilbert use it: he plays with so high gain and compression that dynamics would be basically flat.

That’s an interesting take for sure, and I think I read about this caveat elsewhere. Let me just add that Paul Gilbert has a very broad musical range - there surely is a lot of high gain shredding (at least in earlier days), but he‘s also doing amazing work with clean settings and acoustic guitars. His hearing is not the best though, so maybe subtle differences in dynamics escape him :)

Personally I think that most problems people report about Kemper‘s sound stem from their speaker setup. If you use it for audio recordings or for loud stage setups, you most likely won’t be able to tell any difference. There are lots of blind tests out there and people often think that the Kemper is the real amp.

Hi guys, I'm the person who wrote the article.

I perfectly know that the title is an exaggeration, but choosing an headline for medium is a tough job :)

The reason why I chose to call it like this, is not just to get a couple of clicks, but because while talking to companies that are not ML-aware I often get the question: "how the hell does X do that?!?!?", and the answer 80% of the time could be 4 lines of sklearn.

My goal is to spread awareness on the potential of ML among companies: my intended audience was not ML engineers, to whom this article looks more like "I spent 6 days cleaning data, 20 minutes plotting different clusters representations, and the rest of the day writing an article", but the business person that is not fully aware of what it means to use ML today, and to whom it looks like something amazing and extremely valuable.

Does it make more sense now? :D

As the top comment on this post (https://news.ycombinator.com/item?id=13965043) demonstrates, the title is misleading at best, and I do not believe you want to intentionally mislead your readers. Rhetorical smiley faces do not change that.

Keep in mind that clickbait titles do get penalized on Hacker News, as dang notes.

I didn't even post it on HN, you guys aren't my target as I explained.

I'm trying to make business execs more eager to experiment ML in their companies, and less afraid about the years of R&D and skynet scenarios they currently relate AI to.

The title was an hyperbole? Yes, but it worked in getting the attention of my target audience. Anyone trying to work as an ML engineer knows that what I did is simple and far from being worth $500M, but should still thank me for spreading awareness on the potential of this technology among who's still scared.