The problem Anthropic is running into is that OpenClaw made it easy for everyone to become one of those folks that washes their car three times a week or more.

I’m sure they were losing money on subscriptions in general but now they are really losing money. Shutting off OpenClaw specifically probably helps stem some of the bleeding.

To add to this, I did a quick search on archive.org and it seems like they’ve had this site in place since 2006, albeit in different variations. Perhaps that is why they have a “global” opt-out across all of their marketing databases? Something that has just always been in place.

https://web.archive.org/web/20061103202329/https://gmcontact...

They have a form that requires you enter your full name, address, phone number, and email just to process an unsubscribe.

In addition, they indicate that you may need to enter the form multiple times with different variations of your name in order to be successful.

If by some miracle you succeed at opting out of marketing communications, your opt out is only honored for 10 years and does not include OnStar or GM Financial.

I have seen terrible opt-out practices before but this is probably one of the more egregious ones I’ve encountered.

I’d also be curious to hear if people think the patchwork of data privacy laws that have been going into effect across the U.S. might affect processes like this or if just having the process is enough. I know it is probably somewhat subjective.

Comments URL: https://news.ycombinator.com/item?id=47547655

Points: 5

# Comments: 4

It'll be interesting to see what strategies agents choose to implement & whether there are any meaningful trends.

Comments URL: https://news.ycombinator.com/item?id=46624371

Points: 3

# Comments: 1

I use [insert LLM provider here] all the time to ask generic, health-related questions but I’m careful about what I disclose and how I disclose it to the models. I would never connect data from my primary care’s EHR system directly to one of these providers.

That said, it’ll be interesting to see how the general population responds to this and whether they embrace it or have some skepticism.

I’m not confident we’ll have powerful/efficient enough on-device models to build this before people start adopting the SaaS-based AI health solutions.

ChatGPT’s target market is very clearly the average consumer who may not necessarily care what they do with their data.

> supervised by a human who occasionally knew what he was doing.

seems in jest but I could be wrong. If omitted or flagged as actual sarcasm I would feel a lot better about the project overall. As long as you’re auditing the LLM’s outputs and doing a decent code review I think it’s reasonable to trust this tool during incidents.

I’ll admit I did go straight to the end of the readme to look for this exact statement. I appreciate they chose to disclose.

Consultants + vendor pitch a nice shiny solution that handles everything & works flawlessly. In actuality it resulted in a net efficiency & productivity loss vs the homegrown systems we came from.

It sure did generate plenty of billables for the consultants though, who mind you, are still contracted over a year later.

Check out https://plaintextaccounting.org/