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We will use Grok 3.5 (maybe we should call it 4), which has advanced reasoning, to rewrite the entire corpus of human knowledge, adding missing information and deleting errors.
Then retrain on that.
Far too much garbage in any foundation model trained on uncorrected data.
More Context
Whatever. The next generation will have to learn to trust whether the material is true or not by using sources like Wikipedia or books by well-regarded authors.
The other thing that he doesn't understand (and most "AI" advocates don't either) is that LLMs have nothing to do with facts or information. They're just probabilistic models that pick the next word(s) based on context. Anyone trying to address the facts and information produced by these models is completely missing the point.
Thinking wikipedia or other unbiased sources will still be available in a decade or so is wishful thinking. Once the digital stranglehold kicks in, it'll be mandatory sign-in with gov vetted identity provider and your sources will be limited to what that gov allows you to see. MMW.
Wikipedia is quite resilient - you can even put it on a USB drive. As long as you have a free operating system, there will always be ways to access it.
Yes. There will be no websites only AI and apps. You will be automatically logged in to the apps. Linux, Lemmy will be baned. We will be classed as hackers and criminals. We probably have to build our own mesh network for communication or access it from a secret location.
Can't stop the signal.
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Wikipedia gives lists of their sources, judge what you read based off of that. Or just skip to the sources and read them instead.
Just because Wikipedia offers a list of references doesn't mean that those references reflect what knowledge is actually out there. Wikipedia is trying to be academically rigorous without any of the real work. A big part of doing academic research is reading articles and studies that are wrong or which prove the null hypothesis. That's why we need experts and not just an AI to regurgitate information. Wikipedia is useful if people understand it's limitations, I think a lot of people don't though.
For sure, Wikipedia is for the most basic subjects to research, or the first step of doing any research (they could still offer helpful sources) . For basic stuff, or quick glances of something for conversation.
This very much depends on the subject, I suspect. For math or computer science, wikipedia is an excellent source, and the credentials of the editors maintaining those areas are formidable (to say the least). Their explanations of the underlaying mechanisms are in my experience a little variable in quality, but I haven't found one that's even close to outright wrong.
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Wikipedia presents the views of reliable sources on notable topics. The trick is what sources are considered "reliable" and what topics are "notable", which is why it's such a poor source of information for things like contemporary politics in particular.
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Books are not immune to being written by LLMs spewing nonsense, lies, and hallucinations, which will only make more traditional issue of author/publisher biases worse. The asymmetry between how long it takes to create misinformation and how long it takes to verify it has never been this bad.
Media literacy will be very important going forward for new informational material and there will be increasing demand for pre-LLM materials.
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Again, read the rest of the comment. Wikipedia very much repeats the views of reliable sources on notable topics - most of the fuckery is in deciding what counts as "reliable" and "notable".
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You had started to make a point, now you are just being a dick.
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So what would you consider to be a trustworthy source?
That's a massive oversimplification, it's like saying humans don't remember things, we just have neurons that fire based on context
LLMs do actually "know" things. They work based on tokens and weights, which are the nodes and edges of a high dimensional graph. The llm traverses this graph as it processes inputs and generates new tokens
You can do brain surgery on an llm and change what it knows, we have a very good understanding of how this works. You can change a single link and the model will believe the Eiffel tower is in Rome, and it'll describe how you have a great view of the colosseum from the top
The problem is that it's very complicated and complex, researchers are currently developing new math to let us do this in a useful way