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The biggest drawback of LLM is that it never answers with "I don't know" (unless it is some quote) and it just brings bullshit hallucinations which human has to reject as wrong. Thus it is mostly useless for anything serious. Personally I use it to beautify some text, but still have to do a bit of correction to fix b/s or missed context.
The biggest drawback of LLM is that it never answers with "I don't know" (unless it is some quote) and it just brings bullshit hallucinations which human has to reject as wrong. Thus it is mostly useless for anything serious. Personally I use it to beautify some text, but still have to do a bit of correction to fix b/s or missed context.
I will be doing some testing of this against the base davinci model over the next few weeks.
Earlier quoted context omitted.
The only issue with the math example would be that we don't do complex math in English. Of course it can learn other "languages" but as you said there is less "written" complex math It probably also contains true generalizations that humanity hasn't thought of before, as well as specializations of those generalizations that could be immensely useful. I thought this is quite exciting, I actually think this will become…
Borges, of course, kind of skewered your hopes about 80 years ago.
I don't quite understand how it can produce rhyming poetry if it's building the output one word at a time.
At the point it’s generating the next word, it knows what its preceding words were. With a conceptual representation of various rhyme schemes, subsequent words will (probably) fit that form.
Earlier quoted context omitted.
“Translate: to transfer or turn from one set of symbols into another” – Merriam-Webster No, “translate” still works here, regardless of Pig Latin not being a language. And I agree with the GP that it’s more intuitively understandable word than “transform.”
You can call it both a transformation or a translation, but that doesn't make 'translation' more appropriate of a term. It is a procedural transformation that can be expressed entirely in a one line function of pseudo-code. translation from one real language to another is so complex that it cannot even be represented in a hash table. Notably, the elements of grammar and syntax are not present in this naive form of tr…
The fact that it is an invented, derivative, isomorphic language doesn't mean it loses any properties of being a language.
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Being precise in mathematical or technical terms to a non-technical newbie makes no sense. They need to grasp some basic concepts of what its all about first, in terms that will make immediate sense to them.
Only introduce formalisms when the need for them arises. That way, the reader is not only prepared for them, but can understand the motivation for learning them.
Unless the intro is going to go long and deep, as in the reader is going to become a practitioner, overly precise formalism or language may not add anything at all - because they won't be ready to understand the nuance.
One novel step at a time.
It ends up being easier for the reader, gives them a series of rewarding light-bulb experiences, and requires less explanation in then end. Win-win-win.
I don't quite understand how it can produce rhyming poetry if it's building the output one word at a time.
Previously generated words are added to the input token window. At the point it’s generating the next word, it knows what its preceding words were. With a conceptual representation of various rhyme schemes, subsequent words will (probably) fit that form.
I feel like as an intro aimed at "normies" it still manages to communicate in a more abstract and overthinky way than necessary. People often find it difficult to intuit examples from abstract descriptions. BUT, people are great at intuiting abstractions from concrete examples. You rarely need to explicitly mention abstractions, in informal talk. People's minds are always abstracting. > If I’m relating the collection…
Gag.
edit- and then he just casually starts talking about collapsing wave functions and hermeneutics. With no explanations, just assuming the reader knows it. (I had to look up both those concepts) So who exactly is he writing to here?
I get the sense that ChatGPT crosses a complexity threshold where there’s no good way to describe how it works that satisfies everybody, and that’s leading to cyclical stories of the form “everyone else describes it wrong, so here’s my take.” As a heuristic, I see descriptions falling into simple buckets: - stories that talk about tokens - stories that don’t talk about tokens Anything discussing technical details suc…