88 karma · joined September 16, 2024
Why would it be massive? The application layer typically compacts a profile of information about the users financial situation when offered. I doubt many of us have financial situations that would exceed the context window.
> Third, you would need a training dataset of all those input variables and their outcomes to be able to provide any sort of useful output. The first set of people to share everything wouldn't be able to derive any value from the tool, and I think you'd be hard pressed to convince enough people to do it to get a useful dataset.
Would you 'need' a training dataset of input variables and their outcomes for an LLM? Certainly for traditional ML, but the LLM toolcalling can simulate what an astute user should statistically do in their situation based on information on the internet and reason about the different constraints.
I love aviation, but I also don't see air travel as being a scalable/affordable solution to this problem. Then again, it's only meant to alleviate traffic burden for a certain segment of the population.
They have done more targeted layoffs as well like the FAIR layoffs in 2025 and the RL layoffs in January 2026, as well as the 5% performance cut in February 2025.
I know it's not the same thing as enshitification, and I don't know if the diaper industry is even vulnerable to enshitification, but it would be such a nice play on words if the diaper industry had enshitification.
They don't even seem to serve as visual cues.
The company I reviewed didn't seem like a great investment, but I don't even think that matters right now.