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

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  • Whilst it’s true solar is growing, it is not likely to be the silver bullet you make out.

    Another way to look at the source you linked is that despite the ongoing climate catastrophe the US is still planning to add 4% more fossil fuel sources to their grid next year.

    It also leaves out the fact that 84% of the current US power is generated by fossil fuels and that figure is not being reduced.

    The source is also very US-centric. If we take the IEA’s projections, only 25% of the world’s new energy will be from renewable sources in 2024.

    Then there’s the weird choice of counting battery storage as energy generation. At the end of 2022 half of the battery storage was being powered by fossil fuels so should probably be left out of any statistics.

    We need people to understand the true scale of the problem rather than generating more hopium. The energy companies have teams of people for that.




  • Mmmmm fresh pasta.

    For me it is very weird, no one introduced me formally to Lemmy(no one I knew run or heard of it), it felt like it was a legend. I never really got to know how good it was and always felt Reddit and Twitter were lacking, never really in control of your memes, never happy with my content, always downvoting stuff. The years went by and my curiosity only became larger as Reddit and Twitter experience was getting worse and worse. I already had experience shit posting and trolling on 4chan since my school days, so last year I signed up to Lemmy and posted my first meme. Next thing I know my feed is breathing again, the grass was definitely greener here. So I switched for both reasons.











  • You posted the article rather than the research paper and had every chance of altering the headline before you posted it but didn’t.

    You questioned why you were downvoted so I offered an explanation.

    Your attempts to form your own arguments often boil down to “no you”.

    So as I’ve said all along we just differ on our definitions of the term “understanding” and have devolved into a semantic exchange. You are now using a bee analogy but for a start that is a living thing not a mathematical model, another indication that you don’t understand nuance. Secondly, again, it’s about definitions. Bees don’t understand the number zero in the middle of the number line but I’d agree they understand the concept of nothing as in “There is no food.”

    As you can clearly see from the other comments, most people interpret the word “understanding” differently from yourself and AI proponents. So I infer you are either not a native English speaker or are trying very hard to shoehorn your oversimplified definition in to support your worldview. I’m not sure which but your reductionist way of arguing is ridiculous as others have pointed out and full of logical fallacies which you don’t seem to comprehend either.

    Regarding what you said about Pythag, I agree and would expect it to outperform statistical analysis. That is due to the fact that it has arrived at and encoded the theorem within its graphs but I and many others do not define this as knowledge or understanding because they have other connotations to the majority of humans. It wouldn’t for instance be able to tell you what a triangle is using that model alone.

    I spot another apeal to authority… “Hinton said so and so…” It matters not. If Hinton said the sky is green you’d believe it as you barely think for yourself when others you consider more knowledgeable have stated something which may or may not be true. Might explain why you have such an affinity for AI…



  • I question the value of this type of research altogether which is why I stopped following it as closely as yourself. I generally see them as an exercise in assigning labels to subsets of a complex system. However, I do see how the COT paper adds some value in designing more advanced LLMs.

    You keep quoting research ad-verbum as if it’s gospel so miss my point (and forms part of the apeal to authority I mentioned previously). It is entirely expected that neural networks would form connections outside of the training data (emergent capabilities). How else would they be of use? This article dresses up the research as some kind of groundbreaking discovery, which is what people take issue with.

    If this article was entitled “Researchers find patterns in neural networks that might help make more effective ones” no one would have a problem with it, but also it would not be newsworthy.

    I posit that Category Theory offers an explanation for these phenomena without having to delve into poorly defined terms like “understanding”, “skills”, “emergence” or Monty Python’s Dead Parrot. I do so with no hot research topics at all or papers to hide behind, just decades old mathematics. Do you have an opinion on that?