Remember, Google search used to actually find you things before they shifted to replacing results with “somewhat random but reads plausible” AI summaries.
>replacing results with “somewhat random but reads plausible” AI summaries
I'm talking about actual deep (re)search that cites the sources, not simple summaries. For example I'm considering a KTM 890 Adventure R as my next motorcycle but the reliability and TCO are worrying. I've prompted and launched an agent to recursively scan YouTube travel videos, or rather the transcriptions, to look for actual issues with this bike, without all that KTM marketing bullshit and paid reviews, and provide me with timecodes. And it did, finding a ton of extremely non-obvious non-English channels in the process (Russian, Afrikaans, Spanish etc), scanning dozens of hours of videos, and providing timecodes for me to verify. That saved me insane amount of time.
Normal people actually pay money for this, I'm pretty surprised to see this in the wild but it's true. Reducing this to "techbros and influencers" is pure wishful thinking.
Human translation is obviously better, but not by much, especially on the web. I know because I'm testing LLMs for pretty complex translations all the time, in languages I understand well, and two persons occasionally communicate with me in my native language using an LLM. It's accurate enough to not have any troubles, especially if you don't prompt it naively and use a strong multilanguage model. It's not the same as slop generation, as the input is from a human.
That guy reacted to them ignoring him and overwriting his hard work with a worse version, which is terrible but not related to the point I'm making.
If it’s important, it’s still better to do it yourself (or pay for the service of another human).