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Joined 6 months ago
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Cake day: May 29th, 2024

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  • This model isn’t “learning” anything in any way that is even remotely like how humans learn. You are deliberately simplifying the complexity of the human brain to make that comparison.

    I do think the complexity of artificial neural networks is overstated. A real neuron is a lot more complex than an artificial one, and real neurons are not simply feed forward like ANNs (which have to be because they are trained using back-propagation), but instead have their own spontaneous activity (which kinda implies that real neural networks don’t learn using stochastic gradient descent with back-propagation). But to say that there’s nothing at all comparable between the way humans learn and the way ANNs learn is wrong IMO.

    If you read books such as V.S. Ramachandran and Sandra Blakeslee’s Phantoms in the Brain or Oliver Sacks’ The Man Who Mistook His Wife For a Hat you will see lots of descriptions of patients with anosognosia brought on by brain injury. These are people who, for example, are unable to see but also incapable of recognizing this inability. If you ask them to describe what they see in front of them they will make something up on the spot (in a process called confabulation) and not realize they’ve done it. They’ll tell you what they’ve made up while believing that they’re telling the truth. (Vision is just one example, anosognosia can manifest in many different cognitive domains).

    It is V.S Ramachandran’s belief that there are two processes that occur in the Brain, a confabulator (or “yes man” so to speak) and an anomaly detector (or “critic”). The yes-man’s job is to offer up explanations for sensory input that fit within the existing mental model of the world, whereas the critic’s job is to advocate for changing the world-model to fit the sensory input. In patients with anosognosia something has gone wrong in the connection between the critic and the yes man in a particular cognitive domain, and as a result the yes-man is the only one doing any work. Even in a healthy brain you can see the effects of the interplay between these two processes, such as with the placebo effect and in hallucinations brought on by sensory deprivation.

    I think ANNs in general and LLMs in particular are similar to the yes-man process, but lack a critic to go along with it.

    What implications does that have on copyright law? I don’t know. Real neurons in a petri dish have already been trained to play games like DOOM and control the yoke of a simulated airplane. If they were trained instead to somehow draw pictures what would the legal implications of that be?

    There’s a belief that laws and political systems are derived from some sort of deep philosophical insight, but I think most of the time they’re really just whatever works in practice. So, what I’m trying to say is that we can just agree that what OpenAI does is bad and should be illegal without having to come up with a moral imperative that forces us to ban it.



  • While I agree that it’s somewhat bad that there is no distinction between lossless and lossy jxl in the file extension, I think it’s really not a big deal compared to the present situation with jpg/png.

    The reason being that if you download a png file you have no idea if its been converted from jpg, if it’s a screenshot of a jpg, or if it’s been subjected to lossy reencoding by a tool or a website upload process.

    The only thing you can really do to try and see if the file you’ve downloaded has suffered encoding loss is to do an image search on it and see if there are any better quality versions out there. You’d do the exact same thing with a jxl file.


  • CRI is defined as how closely a light source matches the spectral emission of a thing glowing at a specific temperature. So, for a light source with a 4000 k color temperature its CRI describes how closely its emission matches that of an object that’s been heated to 4000 k.

    Because incandescent bulbs emit light by heating a filament by definition they will have 100 CRI and its impossible to get any better than that. But the emission curve of incandescent lights doesn’t actually resemble that of sunlight at all (sorry for the reddit link). The sun is much hotter than any incandescent bulb and it’s light is filtered by our atmosphere, resulting in a much flatter more gently sloping emission curve vs the incandescent curve which is extremely lopsided towards the red.

    As you can see in the above link, there are certain high end LED bulbs that do a much better job replicating noon day sunlight than incandescents. And that flatter emissions profile probably provides better color rendering (in terms of being able to distinguish one color from another) than the incandescent ramp.

    Now, whether or not you want your bulbs to look like the noon day sun is another matter. Maybe you don’t want to disrupt your sleep schedule and you’d much rather their emissions resemble the sunset or a campfire (though in that case many halogen and high output incandescent lamps don’t do a great job either). Or maybe you’re trying to treat seasonal depression and extra sunlight is exactly what you want. But in any case I think CRI isn’t a very useful unit (another reddit link).



  • There is already a Chinese EV that uses a sodium ion battery, the JMEV EV3.

    It’s a tradeoff of range vs price. The EV3 only has 155 miles of range, but thanks in part to its sodium ion battery it costs only $9220 new. Which is a price that will probably drop even more as more sodium ion plants come online and economies of scale kick in.

    EDIT: even if your commute is 40 minutes long, driving 60 MPH the entire way, that range is enough to get you to work and back using a little more than half your charge. Given that it’s also generally cheaper to charge an EV than pump gas, and there’s less maintenance costs, I think there’s absolutely a market for such a car.