Is Google's Chatbot BARD Failing in Public Testing?

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Google's chatbot BARD has demonstrated significant shortcomings in public testing, particularly highlighted by its performance on practice SAT questions where it answered incorrectly 50% to 75% of the time. In a written language test, BARD achieved only 30% accuracy, often requiring repeated questions for comprehension. Despite its confident tone, frequently asserting "The correct answer is," BARD's reliability is questioned, especially when addressing niche subjects, leading to hallucinations and inaccuracies. These findings underscore the current limitations of BARD compared to its competitors like ChatGPT.

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After an inauspicious debut by Google last month (Feb. 8th), where BARD (Alphabet's rival chatbot to Microsoft/C3.ai's Chat GPT) gave an incorrect answer to an "astronomy-related" question, BARD again seems to flop with its abilities in public testing the past week:
https://fortune.com/2023/03/28/google-chatbot-bard-would-fail-sats-exam/

Fortune sourced practice SAT math questions from online learning resources and found that Bard got anywhere from 50% to 75% of them wrong—even when multiple-choice answers were provided.

Often Bard gave answers which were not even a multiple-choice option, though it sometimes got them correct when asked the same question again. . .

Bard’s first written language test with Fortune came back with around 30% correct answers, often needing to be asked the questions twice for the A.I. to understand.

Even when it was wrong, Bard’s tone is confident, frequently framing responses as: “The correct answer is”—which is a common feature of large language models.

The more Bard was asked language-based questions by Fortune—around 45 in total—the less frequently it struggled to understand or needed the question to be repeated.

On reading tests, Bard similarly performed better than it did in math—getting around half the answers correct on average.
 
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No idea about math problems, but in my experience the best way to make AI hallucinate is to ask a question on some niche subject, that is discussed only in some obscure sources. As you probably don't know I am author of the first commercial Polish video game, Puszka Pandory (Pandora's Box), for ZX Spectrem. That was in 1986, so the sources are scarce, but they do exist. We were playing with ChatGPT last week and for fun asked about the game. Before we got bored ChatGPT listed at least four different authors, each time starting with "I am sorry, you are right I was wrong, the correct answer is XXXX". It never named me as the author :biggrin:

That was in Polish, I suppose if you will ask about details of something like FIDO net technology or BBS software it will give similarly nonsensical answers.
 
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Borek said:
No idea about math problems, but in my experience the best way to make AI hallucinate is to ask a question on some niche subject, that is discussed only in some obscure sources. As you probably don't know I am author of the first commercial Polish video game, Puszka Pandory (Pandora's Box), for ZX Spectrem. That was in 1986, so the sources are scarce, but they do exist. We were playing with ChatGPT last week and for fun asked about the game. Before we got bored ChatGPT listed at least four different authors, each time starting with "I am sorry, you are right I was wrong, the correct answer is XXXX". It never named me as the author :biggrin:

That was in Polish, I suppose if you will ask about details of something like FIDO net technology or BBS software it will give similarly nonsensical answers.

It may not be a good test to check authorship errors because they deliberately scrub datasets of authorship information and personal information, to an extent. They want to avoid legal issues pertaining to privacy, copyright/attribution, defamation, or whatever else.
 
Jarvis323 said:
It may not be a good test to check authorship errors because they deliberately scrub datasets of authorship information and personal information, to an extent. They want to avoid legal issues pertaining to privacy, copyright/attribution, defamation, or whatever else.
It is perfectly good test to prove why GPT in its current state is unreliable and can't be trusted.
 

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