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Joined 1 year ago
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Cake day: June 15th, 2023

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  • I’ve thought about this a bit (but by no means extensively) and I feel like the stakes are different for tech companies because growth doesn’t require as much capital as a non-tech business.

    For a SaaS tech company to scale from 10 users to 1000 users doesn’t mean a bunch more sales people and a new factory, it means having a great product and turning on new servers, likely only incurring a higher hosting bill from AWS (or similar).

    In that sense, I feel like it’s easier for the sentiment to be “we’ll be better off with 1000 more users” over and over again until people start to want to optimize the business. Which means doing more traditional “shareholder value creation” that big companies do today.

    Don’t get me wrong, I would love to see it happen, but i think tech just scales so differently and easier than other business types.





  • I feel like this section is rather disingenuous for the article author to just drop without mentioning that this is how all machine learning models are trained. The idea is that now (and for the next year or whatever) it’s trained manually until the system is good enough to do it on its own with a good enough accuracy rating to not lose money.

    Now, since Amazon is shuttering this, it’s totally possible that they determined they’d need too many years of training data to break even, but at the very least this is standard industry practice for any machine learning model.