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Joined 2 years ago
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Cake day: August 11th, 2023

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  • Machine learning, renamed “AI” with the LLM boom, does not simulate intelligence. It integrates feedback loops, which is kind of like learning and it uses a network of nodes which kind of look like neurons if you squint from a distance. These networks have been around for many decades, I’ve built a bunch myself in college, and they’re at their core just polynomial functions with a lot of parameters. Current technology allows very large networks and networks of networks, but it’s still not in any way similar to brains.

    There is separate research into simulating neurons and brains, but that is separate from machine learning.

    Also we don’t actually understand how our brains work at the level where we could copy them. We understand some things and have some educated guesses on others, but overall it’s pretty much a mistery still.








  • It make sense for a wrapper layer to do this and I had to fight against APIs that didn’t. If I make a single HTTP call that wraps multiple independent API calls into one, then the overall HTTP code should reflect status of the wrapper service, and the individual responses should each have their own code as returned by the underlying services.

    For example on one app we needed to get user names by user id for a bunch of users. To optimize this, we batched calls into groups. The API would fail with an error code if one of the user ids in the batch was bad or couldn’t be found. That meant we wouldn’t be getting data for any of the users in the batch and we didn’t know which userId was bad either. Such a call should return 200 for the overall call and individual result for each id, some of which could be errors.