Seems a promising approach. Feedback at the bottom is (?) missing a submit button. Article was fine, but veered into overly verbose with redundant sections. A simplification pass, even on the outline, could help.
Wait staff paid directly by customers is different from payments processed opaquely by the employer. Consider if a server got paid tips based only on the number of customer smiles detected by the restaurant security cameras.
Tip amounts have always been about how much the customer enjoyed the service, hence the 10-25% tip ranges.
Customers have opaque expectations for service and pay their server based on the server’s gender, race, and age as well as quality of service that the server doesn’t even have control over (like if the kitchen was backed up).
A system counting smiles is basically what we currently have: instead of signaling with a smile, they signal with a tip amount.
I feel like these articles are just "tech company = bad" without recognizing that there are thousands of really smart people trying to create an equitable system that supports the needs of the drivers, passengers, and company.
1. Good wages for drivers means more drivers.
2. More drivers means better quality of service at lower cost for passengers.
3. Low cost and high quality service for passengers means more passengers.
4. More passengers means more rides and more money spent on platform.
More drivers and more passengers means more money for company. The argument that Uber/DD whatever is not incentivized to have high wages for drivers is ridiculous.
Now there is pre-tipping, tipping for no discernible service, fake tip jars in places that aren't licensed for it, etc.
More people are becoming aware that, in the US anyway, the wage is reduced commensurate with expected tips, and so customers are more or less obligated to supplement wages, and avoid offending servers, unless we don't want to be served at all.
I’m seeing a lot of meh products that take like 4 units of effort to integrate. I think multiple LLMs, deeply integrated into a cohesive product with 100+ effort units, that can be great. An AI that’s familiar with the use of every settings menu on windows would be awesome
I’ve heard this means: teams get several months to work on just security. A lot of the work is cleaning up internal tools, secrets in deployment pipelines, that kind of work.
Some can be constructed with varying levels of success. Default Golly comes with an “infinite novelty” scenario; it’s worth checking out for a couple hours.
Yup, it doesn't take a very big starting pattern to produce likely infinite novelty -- though it's not always easy to prove that any given pattern won't eventually unexpectedly "go boring" due to some kind of unexpected feedback effect.
Life being Turing complete, it's also not difficult to build a pattern with an unknown fate -- like a Fermat-prime calculator that will stop growing if it ever finds a sixth Fermat prime, or the Collatz-sequence simulator described here:
