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Joined 3 years ago
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Cake day: June 12th, 2023

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  • Think of the universe not as objects flying apart, but as the fabric of space itself stretching. The more distance there is between two objects, the more ‘new space’ is generated every second, across that entire distance.

    Light travels 9.461 × 1015 meters per year. At a certain distance (the Hubble limit), more than 9.461 × 1015 meters of new space is created in a year. So for stars beyond the Hubble limit, the light sent from those stars actually ends up further from us after a year than when it started. That’s what “moving away from us faster than light” means.



  • If you take data, and effectively do extremely lossy compression on it, there is still a way for that data to theoretically be recovered.

    This is extremely wrong and your entire argument rests on this single sentence’s accuracy so I’m going to focus on it.

    It’s very, very easy to do a lossy compression on some data and wind up with something unrecognizable. Actual lossy compression algorithms are a tight balancing act of trying to get rid of just the right amount of just the right pieces of data so that the result is still satisfactory.

    LLMs are designed with no such restriction. And any single entry in a large data set is both theoretically and mathematically unrecoverable. The only way that these large models reproduce anything is due to heavy replication in the data set such that, essentially, enough of the “compressed” data makes it through. There’s a reason why whenever you read about this the examples are very culturally significant.




  • It sounds like you’re asking why local hidden variables can’t explain the experimental results? But a huge part of the video is spent explaining this so I’m assuming that isn’t what you mean. So I’m not sure what it is exactly that you’re asking. Could you elaborate on how what you’re suggesting differs from the local hidden variable explanation?

    ETA: I think you are asking about hidden variables but maybe don’t realize it because it was brushed over in the video. When she’s discussing the possible strategies for how the particles would decide their orientation, she says there are only 2 strategies that work. Your strategy is one that doesn’t and here’s why I think that is.

    Say your electron is created with 0 degree spin. When deflected with a 0 degree detector, the electron goes up and the positron goes down 100% of the time. Great. But what about the 120 degree detector? Well the electron goes up 3/4 of the time and down 1/4. The positron goes up 1/4 and goes down 3/4. But this can’t be. If the electron goes up, the positron must go down. So in order for it to work, they’d need to pick one of the strategies she talks about in the video. They need to agree on how they’d respond to each of the orientations separately, rather than just agree on a spin direction at creation.


  • Yes, but this is assuming an objective, universal frame of reference, and that’s not really a thing.

    Not really. Nothing I said has any dependence on a universal clock.

    It’s true that there could be some alien halfway across the observable universe that could observe the stars that have exited our observable universe. But, we could not observe the alien observing them, because information still can’t travel faster than the speed of light.

    Right and this is my point. Any philosophical theory that has anything to do with the observable universe is inherently self-centered. Not even Earth centered. Not even conscious-being centered. Literally self-centered. The observable universe is subjective. And so that puts it in the class of philosophies that insist that the universe arises from your own consciousness.

    Which is not to invalidate it, but it’s not objective, and it has nothing to do with science.



  • What? I’ve already written the design documentation and done all the creative and architectural parts that I consider most rewarding. All that’s left for coding is answering questions like “what exactly does the API I need to use look like?” and writing a bunch of error handling if statements. That’s toil.


  • Definitely depends on the person. There are definitely people who are getting 90% of their coding done with AI. I’m one of them. I have over a decade of experience and I consider coding to be the easiest but most laborious part of my job so it’s a welcome change.

    One thing that’s really changed the game recently is RAG and tools with very good access to our company’s data. Good context makes a huge difference in the quality of the output. For my latest project, I’ve been using 3 internal tools. An LLM browser plugin which has access to our internal data and let’s you pin pages (and docs) you’re reading for extra focus. A coding assistant, which also has access to internal data and repos but is trained for coding. Unfortunately, it’s not integrated into our IDE. The IDE agent has RAG where you can pin specific files but without broader access to our internal data, its output is a lot poorer.

    So my workflow is something like this: My company is already pretty diligent about documenting things so the first step is to write design documentation. The LLM plugin helps with research of some high level questions and helps delve into some of the details. Once that’s all reviewed and approved by everyone involved, we move into task breakdown and implementation.

    First, I ask the LLM plugin to write a guide for how to implement a task, given the design documentation. I’m not interested in code, just a translation of design ideas and requirements into actionable steps (even if you don’t have the same setup as me, give this a try. Asking an LLM to reason its way through a guide helps it handle a lot more complicated tasks). Then, I pass that to the coding assistant for code creation, including any relevant files as context. That code gets copied to the IDE. The whole process takes a couple minutes at most and that gets you like 90% there.

    Next is to get things compiling. This is either manual or in iteration with the coding assistant. Then before I worry about correctness, I focus on the tests. Get a good test suite up and it’ll catch any problems and let you reflector without causing regressions. Again, this may be partially manual and partially iteration with LLMs. Once the tests look good, then it’s time to get them passing. And this is the point where I start really reading through the code and getting things from 90% to 100%.

    All in all, I’m still applying a lot of professional judgement throughout the whole process. But I get to focus on the parts where that judgement is actually needed and not the more mundane and toilsome parts of coding.