Bard is much worse at puzzle solving than ChatGPT(twofergoofer.com)
twofergoofer.com
Bard is much worse at puzzle solving than ChatGPT
https://twofergoofer.com/blog/bard
85 comments
Wow I had hoped for a more productive discussion than these 1-1 comparisons of Bard vs ChatGPT that I'm seeing everywhere. The model deployed with this version of Bard is clearly a smaller model than the biggest LaMDA/PaLM models Google has been working on for ages. Which, according to their publications, show unprecedented results on _proof writing_ of all things (see Minerva). While their strategic decisions may be questionable (or they're just trying to quantize the model for mass deployment without burning billions per month in compute costs), its almost silly to question Google's ability to build useful LLMs.
At the moment unless we get more information about what metric you're supposed to evaluate it on, you could probably simplify the headline to just "Bard is much worse than chatgpt" without any loss of accuracy.
It's not really realistic to expect people to give Google credit for these amazing models they have published results about but haven't let people play with - they have given people Bard and people are evaluating it based on the criteria most obvious to them - a comparison to a very similar product that has just been released.
It's not really realistic to expect people to give Google credit for these amazing models they have published results about but haven't let people play with - they have given people Bard and people are evaluating it based on the criteria most obvious to them - a comparison to a very similar product that has just been released.
They knew the war they were entering, they knew their enemies, they knew how they'd get evaluated and still decided to get this model out in its current state, leading to the conclusion: Yes, this is really the best they can do and it's much worse than the state of the art.
In any case, it's a massive marketing blunder, the public opinion formed within the last hours was overwhelmingly "Bard sucks compared to ChatGPT."
In any case, it's a massive marketing blunder, the public opinion formed within the last hours was overwhelmingly "Bard sucks compared to ChatGPT."
>Yes, this is really the best they can do and it's much worse than the state of the art.
This is the best they can do under pressure.
ChatGPT surprised the world with how good it was, then Google scrambled to get something out quick.
A project like this is a massive undertaking, the first mover has the advantage that they can calmly refine their model until they find it presentable.
The question is, is what Google is delivering good for the timeframe since OpenGPT exploded in popularity enough for Google leadership to take note. Since that moment, realistically, is when they put pressure on their devs to push something out the door.
I think we'll see a better iteration soon. Not only from Google, but from other competitors.
This is the best they can do under pressure.
ChatGPT surprised the world with how good it was, then Google scrambled to get something out quick.
A project like this is a massive undertaking, the first mover has the advantage that they can calmly refine their model until they find it presentable.
The question is, is what Google is delivering good for the timeframe since OpenGPT exploded in popularity enough for Google leadership to take note. Since that moment, realistically, is when they put pressure on their devs to push something out the door.
I think we'll see a better iteration soon. Not only from Google, but from other competitors.
> its almost silly to question Google's ability to build useful LLMs.
Unless they release a model one can "use" and verify their claims it's literally silly to make this statement.
Unless they release a model one can "use" and verify their claims it's literally silly to make this statement.
There are useful open source LLMs. Or are you questioning their ability to configure; make install?
> its almost silly to question Google's ability to build useful LLMs.
It's almost silly to presume anything without proofs. People are judging Google based on what Google has shown.
It's almost silly to presume anything without proofs. People are judging Google based on what Google has shown.
It seems like they don't want to be the best, just good and cheap enough that they don't lose users therefore ad revenue.
They behave like Yahoo when Google took over.
They behave like Yahoo when Google took over.
Even the best Google models seem to be lagging for reasoning tasks vs OpenAI ones at the moment - see the graphs at https://github.com/suzgunmirac/BIG-Bench-Hard
Everyone’s gonna have bigger models. Where are their useful models?
Thats like saying car brand X is more reliable than car brand Y, because brand X won formula one.
you can always go back to reddit
Am I missing something? Most of TFA is about Bard failing to answer with rhyming words, but in the only prompts shown the author doesn't actually ask for rhyming words. He just says the hint and the name of the puzzle.
Is this not simply: "Bard is worse than ChatGPT at having seen the 'how-to-play' page for my side project during its training"?
Is this not simply: "Bard is worse than ChatGPT at having seen the 'how-to-play' page for my side project during its training"?
Clicking through to the link next to 'last week's text' and then to 'full rules', it looks like the author is starting the chat sessions with a full explanation that isn't included in the screenshots. (Also, the last screenshot shows the author explicitly asking about rhymes.)
Ah thanks - for others here is the link, though TFA may not necessarily have used the same prompt: https://docs.google.com/document/d/1_eg_jiUE5y8e5zeiz5HCGDc2...
Based on that it looks like the author asked all 25 test puzzles in one big prompt, which one supposes would favor larger models. To compare "puzzle solving" you'd think it would make more sense to ask one puzzle at a time?
Based on that it looks like the author asked all 25 test puzzles in one big prompt, which one supposes would favor larger models. To compare "puzzle solving" you'd think it would make more sense to ask one puzzle at a time?
I tried it both ways; with individual prompts and prompts in bulk. I ran both tests the same way. There's a tradeoff in writing a legible/interesting blog post and relating step-by-step the way the evaluation was ran! Appreciate you reading and the feedback :)
How is this possible? Google makes people do 8 rounds of leetcode. How could they be beaten? Nothing makes sense anymore.
People from Google have argued that's exactly why they're failing.
Personally, as someone who worked at a company that was up over 500% during the pandemic, shipped absolutely nothing during that spike, and then deflated below their pre-pandemic pricing, I saw the foley in hiring smart people first hand.
It's not enough to hire the smartest people, and in fact it can be a competitive disadvantage. The smartest people often want their piece of the product to reflect their ingenuity no matter how ancillary it is to the core mission. Unfortunately that often precludes the kind of agility that businesses need to stay competitive.
OpenAI managed to poach Googlers by simply not having fiefdoms built by smart people™. I imagine if Google had built GPT-4, it wouldn't be having downtime today. Because it wouldn't be public. And it might never be public because it doesn't scale for Google scale yet, and the ethicists want their say, and we need to integrate it into Borg and the front end hasn't passed through enough layers of design and...
Personally, as someone who worked at a company that was up over 500% during the pandemic, shipped absolutely nothing during that spike, and then deflated below their pre-pandemic pricing, I saw the foley in hiring smart people first hand.
It's not enough to hire the smartest people, and in fact it can be a competitive disadvantage. The smartest people often want their piece of the product to reflect their ingenuity no matter how ancillary it is to the core mission. Unfortunately that often precludes the kind of agility that businesses need to stay competitive.
OpenAI managed to poach Googlers by simply not having fiefdoms built by smart people™. I imagine if Google had built GPT-4, it wouldn't be having downtime today. Because it wouldn't be public. And it might never be public because it doesn't scale for Google scale yet, and the ethicists want their say, and we need to integrate it into Borg and the front end hasn't passed through enough layers of design and...
I think they just got lazy and entitled. Maybe ChatGPT will be the scare they need. It feels bad though; they almost don’t deserve the energy this fight will give them.
It's so sad to me to see the downfall of google from the absolute coolest company on the planet to the one that's now trying to keep up.
s/Microsoft/Google/
http://www.paulgraham.com/microsoft.html
http://www.paulgraham.com/microsoft.html
> Microsoft
Good joke. MS has always been in the 'incompetent evil' quadrant, Newcomers just keep inexplicably giving them the benefit of the doubt or assuming/insisting they've "changed".
Good joke. MS has always been in the 'incompetent evil' quadrant, Newcomers just keep inexplicably giving them the benefit of the doubt or assuming/insisting they've "changed".
But was Microsoft ever cool in the sense that Google was circa 2005? (Asking honestly, I'm too young to remember that period.)
No, not really. They were seen as a serious business used by other serious businesses. IMO google pioneered the "cool tech company" with their 20% time, "don't be evil", unique campus life, etc.
No. I'm an old-timer, and there has not been one picosecond since the moment of its founding when Microsoft was cool.
They were cool for these 10 seconds
https://youtu.be/KxaCOHT0pmI
Flight Simulator 1995
Yes, somehow.
https://rarehistoricalphotos.com/windows-95-launch-day-1995/
I remember people commenting "never seen such a thing before, for a computer OS!"
"Many electronics stores held midnight launches for the product, with thousands of people waiting in line to be the first to get their hands on the operating system.
The release was a tremendous success. Microsoft sold 7 million copies in the first five weeks, and Windows 95 was soon the most popular operating system on the market."
https://rarehistoricalphotos.com/windows-95-launch-day-1995/
I remember people commenting "never seen such a thing before, for a computer OS!"
"Many electronics stores held midnight launches for the product, with thousands of people waiting in line to be the first to get their hands on the operating system.
The release was a tremendous success. Microsoft sold 7 million copies in the first five weeks, and Windows 95 was soon the most popular operating system on the market."
I know that at that time I used to be like "what kind of pleb uses anything other than Windows? Get off your high horse and use the OS that actually works", because well... Windows XP was pretty good, and games worked on it.
Need you even ask?
https://www.youtube.com/watch?v=IY2j_GPIqRA
Funny, cause Microsoft didn't die. They're doing great. More than that, they're the ones behind OpenAI.
s/IBM/Microsoft/
History rhymes with itself.
History rhymes with itself.
That's a clever game to get it to play. Today I asked ChatGPT to give me 1000 Fibonacci numbers starting with the 2000th number and it crashed. Later I asked it the same prompt and it repeatedly gave me code to calculate the Fibonacci numbers in Python.
> and it crashed
I hope you understand that it's only because of inability of OpenAI's servers to keep up with demand or some issue in their backend code - language models themselves can't "crash" like normal programs on some kind of input, because they "just" generate new tokens.
I hope you understand that it's only because of inability of OpenAI's servers to keep up with demand or some issue in their backend code - language models themselves can't "crash" like normal programs on some kind of input, because they "just" generate new tokens.
I know little more than what I've read about LLMs and other models. I just got it to do them again and it output them rather quickly: https://imgur.com/a/jfviCCe
are the numbers correct?
I spot checked an random assortment of them and so far yes, but it only takes one wrong one to set every subsequent number off.
> it only takes one wrong one to set every subsequent number off.
Except its not actually doing that calculation, so one wrong one shouldn't truly affect the rest like "Real" math.
Except its not actually doing that calculation, so one wrong one shouldn't truly affect the rest like "Real" math.
> language models themselves can't "crash"
That is like saying the Excel document didn't crash, but Excel did when it tried to parse it. As far as I know there is no proof that you can't cause a LLM to crash with user input.
> because they "just" generate new tokens.
I can write a program that counts to 100 that crashes reliably.
That is like saying the Excel document didn't crash, but Excel did when it tried to parse it. As far as I know there is no proof that you can't cause a LLM to crash with user input.
> because they "just" generate new tokens.
I can write a program that counts to 100 that crashes reliably.
> As far as I know there is no proof that you can't cause a LLM to crash with user input.
Well, then you simply don't understand how they work.
Well, then you simply don't understand how they work.
It's a fixed number of matrix multiplications. You can't make matrix multiplication crash by feeding it any sort of strange numbers (unless they haven't handled their Infs and NaNs).
> You can't make matrix multiplication crash by feeding it any sort of strange numbers
Matrices don't multiply themselves. You need hardware and software. As I pointed out the LLM is effectively just data that is being processed by a program. It is silly to assume you have no bugs in that software or the underlying operating system.
Matrices don't multiply themselves. You need hardware and software. As I pointed out the LLM is effectively just data that is being processed by a program. It is silly to assume you have no bugs in that software or the underlying operating system.
The type of bug the first comment was discussing, where recursion could cause it to crash (out of memory? stack overflow?) is categorically impossible based on how the model works, and a bug in the software running it would not change that.
What would be more interesting is to see Bard vs ChatGPT debating various topics.
> Twofer Goofer HQ's adherence to strict "perfect" rhyme can be tricky for those slant rhyme-inclined.
And yet one puzzle they hammer Bard for failing is "Cactus Practice". What accent do you have to have for that to be a perfect rhyme?
And yet one puzzle they hammer Bard for failing is "Cactus Practice". What accent do you have to have for that to be a perfect rhyme?
From Chicago ... and with more than a thousand solves on that puzzle we've never received a single complaint about the rhyme on that one (plus the stats say users find it an extremely easy rhyme to solve)! Curious how you pronounce that one such that they don't rhyme?
According to the dictionary (and matching my own non-native pronunciation), cactus is /ˈkæktʌs/, practice is /ˈpɹæktɪs/
The terminal /tʌs/ is not quite the same thing as /tɪs/; since they are both unstressed, the difference can be hard to notice in fast speech, but becomes clear when enunciating.
The terminal /tʌs/ is not quite the same thing as /tɪs/; since they are both unstressed, the difference can be hard to notice in fast speech, but becomes clear when enunciating.
Dictionaries often neglect common mergers like the weak vowel merger https://en.wikipedia.org/wiki/Phonological_history_of_Englis... where unstressed /ʌ/, /ə/ and /ɪ/ all end up being pronounced the same.
There are differing definitions of “rhyme” in popular usage. See: https://youtu.be/_kQBVneC30o
A lot of “does this rhyme with that?” depends on the context in terms of how strict the rhyming must be or not.
A lot of “does this rhyme with that?” depends on the context in terms of how strict the rhyming must be or not.
In standard Australian English, this is a perfect rhyme.
Offtopic - have you seen Phind?
https://www.phind.com/
It is very fast and wins the search benchmarks here:
https://twitter.com/vladquant/status/1638305110869807104
https://www.phind.com/
It is very fast and wins the search benchmarks here:
https://twitter.com/vladquant/status/1638305110869807104
Can your source be not someone with an animated profile picture?
Source's source: https://blog.kagi.com/kagi-ai-search#aitest
If I understand how Large Language models work, they don't actually know about spelling.... they are given tokens that represent words, and can only infer things from the context of those tokens across terabytes of data that they're given.
Any rhyming done is an impressive result.
Any rhyming done is an impressive result.
I mean, English spelling certainly doesn't free you from the need to figure rhyming out from context.
It is amazing, but somewhat explicable as an emergent effect.
Dont forget that the model has seen all the poems and raps on the internet. It built some latent space where certain words always cluster together in the context of poems, and in which location.
In this case it really has the best database available to say, what next word would slot in nicely here - as that is precisely what it was trained to do.
It is amazing, but somewhat explicable as an emergent effect.
Dont forget that the model has seen all the poems and raps on the internet. It built some latent space where certain words always cluster together in the context of poems, and in which location.
In this case it really has the best database available to say, what next word would slot in nicely here - as that is precisely how it was trained.
I find it more amazing tbh that you can ask for a poem about something, and that it then sticks to the plot, makes references to the start etc than the actual rhyming.
Dont forget that the model has seen all the poems and raps on the internet. It built some latent space where certain words always cluster together in the context of poems, and in which location.
In this case it really has the best database available to say, what next word would slot in nicely here - as that is precisely what it was trained to do.
It is amazing, but somewhat explicable as an emergent effect.
Dont forget that the model has seen all the poems and raps on the internet. It built some latent space where certain words always cluster together in the context of poems, and in which location.
In this case it really has the best database available to say, what next word would slot in nicely here - as that is precisely how it was trained.
I find it more amazing tbh that you can ask for a poem about something, and that it then sticks to the plot, makes references to the start etc than the actual rhyming.
Well the nature of byte pair encoding has a side effect of encoding sounds as well. I briefly explored it here: https://youtu.be/fTDQUxha9qU?t=480
"Bard is much worse than ChatGPT at solving an obscure word game I invented" would have been a more honest title, but would probably generate less clicks for the author.
Bard may still be much worse than ChatGPT at solving all kinds of puzzles, but the article is click bait for promoting the author's word game, not an actual investigation that warrants that conclusion.
Bard may still be much worse than ChatGPT at solving all kinds of puzzles, but the article is click bait for promoting the author's word game, not an actual investigation that warrants that conclusion.
Having read through the word game, I agree with others that it's good that the game is less likely to be in the corpus. I think rhyming, while a challenging task, may be a poor benchmark for ability. The author doesn't seem to understand rhyming too well (cactus practice is a weak rhyme at best)
I completely disagree with the "hasty rhyming test" - Skeleton and Gelatin don't rhyme (-ton vs -tin), and rhyme worse than protein and poutine (-een vs --een).
I completely disagree with the "hasty rhyming test" - Skeleton and Gelatin don't rhyme (-ton vs -tin), and rhyme worse than protein and poutine (-een vs --een).
> The author doesn't seem to understand rhyming too well (cactus practice is a weak rhyme at best)
cactus / practice ?
they rhyme to my mind
skeleton / gelatin ?
also rhyme to my ears
protein / poutine
also rhyme enough to be considered to rhyme
You appear to be operating under the impression that the every syllable of a rhyming couplet has to rhyme exactly for it to be considered a rhyme. This is an incorrect assumption. In fact, the above rhymes are arguably more pleasing because they are inexact rhymes rather than being exact forced rhymes.
In your world the only actual rhymes would be
bold / cold / gold
and
double / trouble / bubble
types of rhymes but the world considers the following to be perfectly acceptable
sent to meet her / centimetre
and so on
cactus / practice ?
they rhyme to my mind
skeleton / gelatin ?
also rhyme to my ears
protein / poutine
also rhyme enough to be considered to rhyme
You appear to be operating under the impression that the every syllable of a rhyming couplet has to rhyme exactly for it to be considered a rhyme. This is an incorrect assumption. In fact, the above rhymes are arguably more pleasing because they are inexact rhymes rather than being exact forced rhymes.
In your world the only actual rhymes would be
bold / cold / gold
and
double / trouble / bubble
types of rhymes but the world considers the following to be perfectly acceptable
sent to meet her / centimetre
and so on
What most people consider a rhyme is that the vowel and coda of the last syllable match (of course we don't mostly reach for the technical definition).
I guess the examples there might be accent dependent. Protein/poutine is the only one of those first examples that really rhymes to me; skeleton/gelatin and cactus/practice both have different vowels. Maybe different for you though.
I guess the examples there might be accent dependent. Protein/poutine is the only one of those first examples that really rhymes to me; skeleton/gelatin and cactus/practice both have different vowels. Maybe different for you though.
> What most people consider a rhyme is that the vowel and coda of the last syllable match
??? Oh yeah, says who?
protein / poutine
p[]oh teen / poo teen => both start with a p, then there's an oh or oo (which are similar) and both end the same way – disyllabic rhyme
cactus / practice ?
[]ah ck təss / []ah ck tiss => ignoring the first consonant (cluster) which anchors the rhyme and pronouncing the u as a schwa (which it is), the ck's are the same and təss and tiss are totes similar – disyllabic rhyme
skeleton / gelatin ?
trisyllabic goodness – again, the way we pronounce the on in first word is not like the on in frond but like the ən in motion (UHn) and the way we pronounce the at in the second word is not like the at in bat or cat but like the ət in … hmm, none spring to mind but it's an UHt sound here if you listen to it – sgɛ́lɪtən or ˈskelɪtən – ˈʤelətɪn – so you've k vying with g (both hard), e with e, l with l, ɪ with ə (close sounding!), t with t, ə with ɪ (close sounding!), n with n
===
listen with your ears, not with your eyes
??? Oh yeah, says who?
protein / poutine
p[]oh teen / poo teen => both start with a p, then there's an oh or oo (which are similar) and both end the same way – disyllabic rhyme
cactus / practice ?
[]ah ck təss / []ah ck tiss => ignoring the first consonant (cluster) which anchors the rhyme and pronouncing the u as a schwa (which it is), the ck's are the same and təss and tiss are totes similar – disyllabic rhyme
skeleton / gelatin ?
trisyllabic goodness – again, the way we pronounce the on in first word is not like the on in frond but like the ən in motion (UHn) and the way we pronounce the at in the second word is not like the at in bat or cat but like the ət in … hmm, none spring to mind but it's an UHt sound here if you listen to it – sgɛ́lɪtən or ˈskelɪtən – ˈʤelətɪn – so you've k vying with g (both hard), e with e, l with l, ɪ with ə (close sounding!), t with t, ə with ɪ (close sounding!), n with n
===
listen with your ears, not with your eyes
Protein and poutine do not rhyme if you pronounce poutine the proper way in Canadian French.
And you are right of course that gelatin and practice have the short "ee" sound at the end whereas skeleton and and cactus have the "uh" sound.
And you are right of course that gelatin and practice have the short "ee" sound at the end whereas skeleton and and cactus have the "uh" sound.
> Protein and poutine do not rhyme if you pronounce poutine the proper way in Canadian French.
I looked it up, and sure, it sounds about the same in Canadian French as someone saying Vladimir Putin[1]. But I've never heard anyone say it that way myself, and in neutral French (according to the linked video, at least), it's pronounced 'pooh-teen', which sounds exactly like protein (I don't know if you pronounce protein different, but for me it's 'pro-teen').
[1]: https://youtu.be/yyis4TgmXYg
I looked it up, and sure, it sounds about the same in Canadian French as someone saying Vladimir Putin[1]. But I've never heard anyone say it that way myself, and in neutral French (according to the linked video, at least), it's pronounced 'pooh-teen', which sounds exactly like protein (I don't know if you pronounce protein different, but for me it's 'pro-teen').
[1]: https://youtu.be/yyis4TgmXYg
There's a funny restaurant called Vladimir Poutine in Montréal lol:
https://www.vice.com/en/article/vb7qwb/inside-vladimir-pouti...
https://www.vice.com/en/article/vb7qwb/inside-vladimir-pouti...
> You appear to be operating under the impression that the every syllable of a rhyming couplet has to rhyme exactly for it to be considered a rhyme
I'm not operating under that impression, but the author is [1].
To me, the final "sounds" should match - not every syllable, an end rhyme according to wiki [0]. Specifically I would consider a rhyme to require matching sounds "at least from last vowel to end", but I don't think of rhymes first from the strict definition. Perhaps it's an accent thing but "-us" in cactus is not the same sound as "-ice" in practice. If a child made a poem with these sounds I would tell them "good job, it's a rhyme", and perhaps for the purpose of a silly word game too. But I would not use it as a passing case for a test of any sort like the author.
What's more pleasing is irrelevant, what is relevant is if its a true rhyme.
[0] https://en.wiktionary.org/wiki/end_rhyme#English
[1] https://news.ycombinator.com/reply?id=35258385&goto=item%3Fi...
I'm not operating under that impression, but the author is [1].
To me, the final "sounds" should match - not every syllable, an end rhyme according to wiki [0]. Specifically I would consider a rhyme to require matching sounds "at least from last vowel to end", but I don't think of rhymes first from the strict definition. Perhaps it's an accent thing but "-us" in cactus is not the same sound as "-ice" in practice. If a child made a poem with these sounds I would tell them "good job, it's a rhyme", and perhaps for the purpose of a silly word game too. But I would not use it as a passing case for a test of any sort like the author.
What's more pleasing is irrelevant, what is relevant is if its a true rhyme.
[0] https://en.wiktionary.org/wiki/end_rhyme#English
[1] https://news.ycombinator.com/reply?id=35258385&goto=item%3Fi...
> Perhaps it's an accent thing but "-us" in cactus is not the same sound as "-ice" in practice.
Indeed, it's an accent thing. In America at least, pronouncing "cactus" with an "is" or an "us" sound are both valid.
I think that given that the author provided a working definition, and your provided failure example is actually passing that definition (just only for the author's dialect), and given that you are now essentially trying to change the subject to "my definition of rhyme is the correct one"; well, you're just being...pedantic? argumentative? I'm not sure.
Indeed, it's an accent thing. In America at least, pronouncing "cactus" with an "is" or an "us" sound are both valid.
I think that given that the author provided a working definition, and your provided failure example is actually passing that definition (just only for the author's dialect), and given that you are now essentially trying to change the subject to "my definition of rhyme is the correct one"; well, you're just being...pedantic? argumentative? I'm not sure.
In the article, I mention that Twofer Goofer requires perfect or strict rhyme. Perfect and strict rhyme require that all syllables are pronounced identically in the speaker's tongue (for me, American Midwest accent), except for the first sound of the word which can vary.
Hence pooh-teen and proh-tein do not rhyme. Skell-ih-tin and Gell-ih-tin do rhyme.
A game like this requires a pretty tight rhyming definition to not annoy players in a given day!
Thanks for reading: https://www.masterclass.com/articles/perfect-vs-imperfect-rh...
Hence pooh-teen and proh-tein do not rhyme. Skell-ih-tin and Gell-ih-tin do rhyme.
A game like this requires a pretty tight rhyming definition to not annoy players in a given day!
Thanks for reading: https://www.masterclass.com/articles/perfect-vs-imperfect-rh...
what's wrong with that?
the use of novel puzzles is frankly awesome because there's a much lower chance of contamination from previous puzzles so we get a chance to see how much generalization they've achieved.
the use of novel puzzles is frankly awesome because there's a much lower chance of contamination from previous puzzles so we get a chance to see how much generalization they've achieved.
I'm complaining about the title writing a check that the blog post can't cash.
GPT-4 says: A more accurate and balanced title might be: "Comparing Bard and ChatGPT in Puzzle Solving: An Examination within the Context of a Word Game"
Sounds like GPT-4 will save us from clickbait
Fair! But if I wrote Twofer Goofer in the title it would not resonate at at all. Alas, tradeoffs.
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How do you navigate this blog to read the other articles? I couldn't find any way to read the one on gpt4 (clicking the underlined "wrote about" does nothing) and twofergoofer.com/blog goes to a 404.
I was curious to read it, too, so I googled to find the article.
It's located at https://twofergoofer.com/blog/gpt-4
It's located at https://twofergoofer.com/blog/gpt-4
Hah - we only made the blog over the weekend and don't have any nav or menu for now. But yep we link the prior article a few times in this article, that article goes into more detail!
It is interesting how lackluster the reactions are about Bard, when it would have been jaw-gapping amazing just a year ago.
Bard is basically trash
I tried to play hangman with it, but it was on crack.
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