plibither8

Did you just learn this word too from another recent thread on HN? I did, haha!

You're getting downvoted, but I was thinking the same thing. Could someone explain why that might not be the case?

> India has half-hour timezones

If that's messy, consider Nepal's timezone that's on the 45-minute mark (UTC+5:45).

Whatever happened to their Android plans?

Yes, netdata FTW! You might need to perform some manual configuration to enable sensor data collection though, like installing `lm-sensors`.

> Here if I understand you don’t get access to support but to an interpreter who will call the support for you. It’s of no interest if you don’t know ASL

I might receive some slack here, but I gave it a try (I don't know ASL). Within 5 seconds of clicking the button, I was connected to a live human, with both my video and sound, as well as the other person's, turned on (although I did have the ability to switch them off). There was no intermediate step to filter out spam calls. I did cut the call quickly though to avoid wasting their time!

Agreed! However, I also wonder what their ratio of spam vs. actual ASL-requiring-customer calls is. Since it's so easy and quick to connect to a real human with comolete audio and video enabled on both ends, won't it be prone to abuse?

The more such a service gets attention from regular media (instead of the niche, targeted audience it aims to serve), I fear it'll be another case of "why we can't have good things".

Yep, that's one of its deficiencies! For me, something like GPT helps in triaging and "cleaning up" bulk of the transactions, with little micro-categorization left to be manually done.

> What software have you used that does this?

I wrote my own script that uses the GPT API. For automating bank transcation downloads, it's just a cronjob that runs ever X hours and scrapes the information from the banking website.

Not to be that guy that tries to force LLMs into everything, but after automatically importing bank transactions, LLMs like GPT are very powerful in extracting information from the ill-formed, non-standard, transaction description, and subsequently classifying it. You can help train it by manually identifying and classifying the first few, and let it do the rest of the job. I've tried it out myself and works well for me!

Interesting. I have an inherent distrust with reviews and descriptions on Google Maps, at least for where I live (India). I usually resort to other services to look for good restaurant/hotel recommendations.