☆ Yσɠƚԋσʂ ☆

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Joined 5 years ago
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Cake day: January 18th, 2020

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  • The perception of democracy by a country’s own people is likely the strongest indicator of its health. After all, what could be more relevant than the lived experience of the populace? If people don’t feel that their government serves them, then external ratings showing otherwise, however meticulously compiled, miss the core reality of the situation.

    Furthermore, coming up with a truly comprehensive and universally agreed-upon rating system for democracy is itself a non-trivial challenge. Would such a rating heavily weigh material conditions, levels of inequality, access to public services, or more abstract freedoms like speech and assembly? And crucially, who decides which of these aspects are the most important or hold the greatest weight in determining a nation’s democratic standing?



  • A more accurate conclusion would be: human-like object concept representations emerge when fed data collected by humans, curated by humans, annotated by humans, and then tested by representation learning methods designed for humans.

    Again, I’m not disputing this point, but I don’t see why it’s significant to be honest. As I’ve noted, human representation of the world is not arbitrary. We evolved to create efficient models that allow us to interact with the world in an effective way. We’re now seeing that artificial neural networks are able to create similar types of internal representations that allow them to meaningfully interact with the data organized in a way that’s natural for humans.

    I’m not suggesting that human style representation of the world is the one true way to build a world model, or that other efficient representations aren’t possible. However, that in no way detracts from the fact that LLMs can create a useful representation of the world, that’s similar to our own.

    Ultimately, the end goal of this technology is to be able to interact with humans, to navigate human environments, and to accomplish tasks that humans want to accomplish.



















  • I didn’t say they’re encoding raw data from nature. I said they’re learning to interpret multimodal representations of the encodings of nature that we feed them in human compatible formats. What these networks are learning is to make associations between visual, auditory, tactile, and text representations of objects. When a model recognizes a particular modality such as a sound, it can then infer that it may be associated with a particular visual object, and so on.

    Meanwhile, the human perspective itself isn’t arbitrary either. It’s a result of evolutionary selection process that shaped the way our brains are structured. This is similar to how brains of other animals encode reality as well. If you evolved a neural network on raw data from the environment, it would eventually start creating similar types of representations as well because it’s an efficient way to model the world.
















  • Democracy means a government that serves the majority, and answers to them. Its most important measure lies the steady rise in people’s living standards. But perception matters too, do citizens believe their government works for them?

    In the West, most don’t. And why would they? They watch their livelihoods shrink while oligarchs, the real rulers of capitalist regimes, gorge themselves on the exploitation of the working class. In China, people call their system democratic, because it is. They’ve witnessed the fastest improvement in living standards in human history. That’s not just democracy in theory. It’s democracy in practice.