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Cake day: July 11th, 2023

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  • A vector space is a collection of vectors in which you can scale vectors and add vectors together such that the scaling and addition operations satisfy some nice relationships. The 2D and 3D vectors that we are used to are common examples. A less common example is polynomials. It’s hard to think of a polynomial as having a direction and a magnitude, but it’s easy to think of polynomials as elements of the vector space of polynomials.



  • It’s crazy how most of those programs work. The way my insurance handles it is way better. For example, no matter how bad you are at driving, they never raise the premiums above the normal rate, so it almost always makes sense to get the tracker from a finance perspective. (The only exception is that they will raise your rates if you drive farther in 6 months than you estimated on your initial application. The flip side is that they lower your rates if you don’t drive very much. I only drive about 1000 miles every 6 months, so my premium is really low.) They also have a Bluetooth device that stays in your car that your phone must be connected to in order for it to record trip data, and if you happen to be riding as the passenger in the car, the app has an option that allows you to clarify for each trip that you weren’t the driver. I was surprised to learn they aren’t all like that.


  • Language parsing is a routine process that doesn’t require AI and it’s something we have been doing for decades. That phrase in no way plays into the hype of AI. Also, the weights may be random initially (though not uniformly random), but the way they are connected and relate to each other is not random. And after training, the weights are no longer random at all, so I don’t see the point in bringing that up. Finally, machine learning models are not brute-force calculators. If they were, they would take billions of years to respond to even the simplest prompt because they would have to evaluate every possible response (even the nonsensical ones) before returning the best answer. They’re better described as a greedy algorithm than a brute force algorithm.

    I’m not going to get into an argument about whether these AIs understand anything, largely because I don’t have a strong opinion on the matter, but also because that would require a definition of understanding which is an unsolved problem in philosophy. You can wax poetic about how humans are the only ones with true understanding and that LLMs are encoded in binary (which is somehow related to the point you’re making in some unspecified way); however, your comment reveals how little you know about LLMs, machine learning, computer science, and the relevant philosophy in general. Your understanding of these AIs is just as shallow as those who claim that LLMs are intelligent agents of free will complete with conscious experience - you just happen to land closer to the mark.



  • It’s only controversial because the way the therapy has been implemented in the past (and unfortunately in some places still today) is similar to what you describe. However, modern practices don’t try to train their clients to act like “normal people” and any serious technician or analyst will only use punishment (or threats of punishments) as a last resort in programs written to target the most imperative behaviors (like running into traffic). Instead, they focus on the use of reinforcement to teach their clients skills that help them to become self sufficient. Following your metaphor, it would be like offering a depressed person $10 for every chore they complete that day rather than holding a gun to their head. The goal is to establish a foundation for life outside of therapy, not to reduce the presentation of autism.


  • CompassRed@discuss.tchncs.detoScience Memes@mander.xyzgatekeeping
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    11 months ago

    You have the spirit of things right, but the details are far more interesting than you might expect.

    For example, there are numbers past infinity. The best way (imo) to interpret the symbol ∞ is as the gap in the surreal numbers that separates all infinite surreal numbers from all finite surreal numbers. If we use this definition of ∞, then there are numbers greater than ∞. For example, every infinite surreal number is greater than ∞ by the definition of ∞. Furthermore, ω > ∞, where ω is the first infinite ordinal number. This ordering is derived from the embedding of the ordinal numbers within the surreal numbers.

    Additionally, as a classical ordinal number, ω doesn’t behave the way you’d expect it to. For example, we have that 1+ω=ω, but ω+1>ω. This of course implies that 1+ω≠ω+1, which isn’t how finite numbers behave, but it isn’t a contradiction - it’s an observation that addition of classical ordinals isn’t always commutative. It can be made commutative by redefining the sum of two ordinals, a and b, to be the max of a+b and b+a. This definition is required to produce the embedding of the ordinals in the surreal numbers mentioned above (there is a similar adjustment to the definition of ordinal multiplication that is also required).

    Note that infinite cardinal numbers do behave the way you expect. The smallest infinite cardinal number, ℵ₀, has the property that ℵ₀+1=ℵ₀=1+ℵ₀. For completeness sake, returning to the realm of surreal numbers, addition behaves differently than both the cardinal numbers and the ordinal numbers. As a surreal number, we have ω+1=1+ω>ω, which is the familiar way that finite numbers behave.

    What’s interesting about the convention of using ∞ to represent the gap between finite and infinite surreal numbers is that it renders expressions like ∞+1, 2∞, and ∞² completely meaningless as ∞ isn’t itself a surreal number - it’s a gap. I think this is a good convention since we have seen that the meaning of an addition involving infinite numbers depends on what type of infinity is under consideration. It also lends truth to the statement, “∞ is not a number - it is a concept,” while simultaneously allowing us to make true expressions involving ∞ such as ω>∞. Lastly, it also meshes well with the standard notation of taking limits at infinity.