• 27 Posts
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Joined 2 years ago
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Cake day: June 15th, 2023

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  • Not OP, but having files and folder structures accessible in the OS helps with a lot of tasks and interoperability.

    If I want to add media files to Jellyfin, etc, I can’t just drop them into the video folder remotely because I have it mapped to a particular folder on the drive. If I want to make a copy of a large folder, I first have to mount the cloud as a “remote” drive, then do the operation from there.

    It’s much easier to access files and folders outside of a database if they are needed for anything outside of the cloud service. I know that there may also be some security and efficiency factors that make a database favorable, but in terms of ease of use, it is just more effort to use a fileserver that operates through a database.









  • You’ve just described the post-scarcity economy.

    I think of the two possible trajectories as the Star Wars universe and the Star Trek universe. Both have fully automated supply chains through droids/replicator technology. However, in Star Wars, only the elite few have access to that technology. Hence, the economy is still centered around trade and, well, as the title would suggest — wars. In Star Trek, that technology is democratized and made available to everyone to create a world in which money has no meaning, and everyone has access to technology and meeting their basic needs.

    It all depends on what kind of society we decide to build from here on out.







  • Here’s an interesting post that gives a pretty good quick summary of when an LLM may be a good tool.

    Here’s one key:

    Machine learning is amazing if:

    • The problem is too hard to write a rule-based system for or the requirements change sufficiently quickly that it isn’t worth writing such a thing and,
    • The value of a correct answer is much higher than the cost of an incorrect answer.

    The second of these is really important.

    So if your math problem is unsolvable by conventional tools, or sufficiently complex that designing an expression is more effort than the answer is worth… AND ALSO it’s more valuable to have an answer than it is to have a correct answer (there is no real cost for being wrong), THEN go ahead and trust it.

    If it is important that the answer is correct, or if another tool can be used, then you’re better off without the LLM.

    The bottom line is that the LLM is not making a calculation. It could end up with the right answer. Different models could end up with the same answer. It’s very unclear how much underlying technology is shared between models anyway.

    For example, if the problem is something like, "here is all of our sales data and market indicators for the past 5 years. Project how much of each product we should stock in the next quarter. " Sure, an LLM may be appropriately close to a professional analysis.

    If the problem is like “given these bridge schematics, what grade steel do we need in the central pylon?” Then, well, you are probably going to be testifying in front of congress one day.