Are you able to just re-run the data for the timeframe, or is "fixing it" a more manual process? And what observability are you working with into the process?
So if they played a short annoncement beforehand so people know its an Original, it would be fine? Originals get advertised heavily, next-movie, so I assume putting it in the same playlist is fine.
Amazon Originals, Netflix Originals. Disney Originals. Paramount Originals. I'm just wondering what is different between series and music, that for music its very bad morally to create your own and to put your own in the front row. While for other streaming its accepted.
> This time, I tried to learn from that: facts are stored as instants, reasoning happens in local days of the jurisdiction that cares.
I think that's how the JavaScript Temporal proposal works. Convert your instant to the timezone, make the comparisons/calculations, hope you didn't jump an hour due to summertime, convert back.
Making people able to sue for anyone feeling bad about not having gotten the job is a path you should not take. We have something similar in Germany and its horrible for companies. Leeches bleeding you dry.
How does an e2e test for less capable LLMs look like, you call each LLM one by one? Aren't these tests flaky by the nature of LLMs, how do you deal with that?
I've got a small question. How do you deal with people asking for open sourcing your product/code, claiming they don't want to use a product they don't control?
Every time I hear it contains AI it sounds like the features' outcome will be uncertain. Especially with more experience. If your feature were good you wouldn't have to mention AI to show it is awesome.
More than not AI is used as an excuse for the feature to be bad.
The UX is not good enough yet. We would have to 1) show that it is reserved to people going on the link and 2) offer good/enough ways to be notified once the link becomes online and 3) need to know the likelihood of the link to actually work in the future based on prior commitment.