That's a good hypothesis! But I have a strong preference for email over SMS for communication from companies, so I receive almost no texts from credit card companies. It's pretty much limited to an occasional authentication code for logging in (since TOTP-based two-factor is so unfortunately rare).
I imagine it's not, but can also see automated systems flagging the number as being the recipient of messages for over a hundred different financial institutions.
Maybe not but I bet that this many unique credit card emails eventually tripped over some threshold in a risk model. It’s too hard to adjust the model for one person, and putting in an exception for this one person means they take on additional risk if that person then goes on to actually do bad things.
To be clear I’m not saying it’s ok. Google should make it right and then invest in a scalable way to not keep doing this.
I made a video showcasing some advanced techniques to use fonts on the web, without compromising performance. Covers interesting font metrics like ascenders and descenders. Fascinating to see how much information is contained within a font file!
Yes! We’re in the middle of cleaning things up, just need to make the Loops a bit more portable/easy to run, but finally happy with the state of the tool.
This is a tutorial I wrote for Firebase. It shows how to build three different AI-related web apps: A chatbot, a review summariser, and a video summariser.
Video here: https://www.youtube.com/watch?v=RIjz9w77h1Q