Earlier quoted context omitted.
> The results are surprisingly good, I don't think I could've done better as a human I'm actually surprised that the performance is so poor and would expect a human to do much better. The GPT model has embedding PLUS a whole transformer model that can untangle the embedded structure. To clarify some of the issues: data is both singular and plural, being a mass noun[0,1]. Datum is something you'll find in the dictiona…
"King-crown=ruler" is IMO absolutely apt. Arguing that "crown" can be used metaphorically is a bit disingenuous because first, it's very rarely applied to non-monarchs, and is a very physical, concrete symbol of power that separates monarchs from other rulers. "King-princess=man" can be thought to subtract the "royalty" part of "king"; "man" is just as good an answer as any else. "King-queen=prince" I'd think of as s…
Show HN: Semantic Calculator (king-man+woman=?)
171–179 of 179 posts
Re: Show HN: Semantic Calculator (king-man+woman=?)
#172I've tried to get to "garage", but failed at a few attempts, ChatGPT's ideas also seemed reasonable, but failed. Any takers? :)
Re: Show HN: Semantic Calculator (king-man+woman=?)
#173LOL
Re: Show HN: Semantic Calculator (king-man+woman=?)
#174Earlier quoted context omitted.
Well when it works out it is quite satisfying India - Asia + Europe = Italy Japan - Asia + Europe = Netherlands China - Asia + Europe = Soviet-Union Russia - Asia + Europe = European Russia calculation + machine = computer
Interesting: Russia - Europe = Putin Ukraine + Putin = Russia Putin - Stalin = Bush Stalin - purge = Lenin That means Bush = Ukraine+Putin-Europe-Lenin-purge. However, the site gives Bush -4%, second best option (best is -2%, "fleet ballistic missile submarine", not sure what negative numbers mean).
Re: Show HN: Semantic Calculator (king-man+woman=?)
#175data + plural = number data - plural = research king - crown = (didn't work... crown gets circled in red) king - princess = emperor king - queen = kingdom queen - king = worker king + queen = queen + king = kingdom boy + age = (didn't work... boy gets circled in red) man - age = woman woman - age = newswoman woman + age = adult female body (tied with man) girl + age = female child girl + old = female child The other…
For fun, I pasted these into ChatGPT o4-mini-high and asked it for an opinion: data + plural = datasets data - plural = datum king - crown = ruler king - princess = man king - queen = prince queen - king = woman king + queen = royalty boy + age = man man - age = boy woman - age = girl woman + age = elderly woman girl + age = woman girl + old = grandmother The results are surprisingly good, I don't think I could've do…
Re: Show HN: Semantic Calculator (king-man+woman=?)
#176dog - cat = paleolith paleolith + cat = Paleolithic Age paleolith + dog = Paleolithic Age paleolith - cat = neolith paleolith - dog = hand ax cat - dog = meow Wonder if some of the math is off or I am not using this properly
Re: Show HN: Semantic Calculator (king-man+woman=?)
#177data + plural = number data - plural = research king - crown = (didn't work... crown gets circled in red) king - princess = emperor king - queen = kingdom queen - king = worker king + queen = queen + king = kingdom boy + age = (didn't work... boy gets circled in red) man - age = woman woman - age = newswoman woman + age = adult female body (tied with man) girl + age = female child girl + old = female child The other…
Can you elaborate on what the unsolved problem you're referring to is?
You can get some help in high dimensions when you're more concerned with (clearly disjoint) clusters. But this is akin to doing a dimensional reduction, treating independent clusters as individual points. (Say we have set S which has disjoint subsets {S_0,...,S_n}, your new set is now {a_0,...,a_n}, where each a_i is an element representing all elements in S_i. Think like "set of sets") But you do not get help with interrelationships (i.e. d(s_x,s_y) \in S_i \forall x≠y) and I think you can gather that when clusters are not clearly disjoint then we're in the same situation as trying to differentiate inter-cluster.
Understanding this can help you understand why these models (including LLMs) are good in broader concepts like differentiating between obvious things but struggle more in nuance. A good litmus test is to ask them about any subject you have good deep knowledge in. Essentially test yourself for Murray-Gelmann Amnesia. The things are designed for human preference. When they fail they're likely to fail without warning (i.e. in ways that are not so obvious)
Re: Show HN: Semantic Calculator (king-man+woman=?)
#178data + plural = number data - plural = research king - crown = (didn't work... crown gets circled in red) king - princess = emperor king - queen = kingdom queen - king = worker king + queen = queen + king = kingdom boy + age = (didn't work... boy gets circled in red) man - age = woman woman - age = newswoman woman + age = adult female body (tied with man) girl + age = female child girl + old = female child The other…
Re: Show HN: Semantic Calculator (king-man+woman=?)
#179I've tried to get to "garage", but failed at a few attempts, ChatGPT's ideas also seemed reasonable, but failed. Any takers? :)
"car + house + door" worked for me (interestingly "car + home + door" did not)
I've had some fun finding this:
car - move + shape = car wheel