Why Some Economists Say A.I. Is Essentially Doomed
There’s been a lot of talk lately about A.I. – what it can do, what it’s doing poorly, and whether or not we’re all eventually going to lose our jobs to computer programs.
That said, there are people out there who say we don’t have to worry, because the people who believe A.I. is the wave of the future are far too confident.
Despite the recent success, and the competition between Silicon Valley giants and OpenAI, experts call the hype “a bubble.”
They argue that if and when it pops, the Language Learning Model will be revealed to be mostly smoke and mirrors.
“The undeniable magic of the human-like conversations generated by GPT will undoubtedly enrich many who peddle the false narrative that computers are now smarter than us and can be trusted to make decisions for us.”
They also say the bubble is “inflating rapidly,” which is typically not a great sign.
The investors seem to misunderstand the technology they’re so excited about, acting as if the ChatBots are actually synthesizing information instead of just doing their best to mimic human responses.
The bots are essentially predicting what response is probably expected, and has no real understanding of what they’re replying with or why. Experts say this makes the tech a failure, and the fact that it will become combative and overconfident – even when it’s wrong – compounds the issue.
“Trained on unimaginable amounts of text, they string together words in coherent sentences based on statistical probability of words following other words. But they are not ‘intelligent’ in any real way – they are just automated calculators that spit out words.”
Others argue these are merely growing pains, and the A.I. will learn and improve as a result of more interactions with actual humans.
The authors of the article linked above, though, think more data will only serve to illuminate the severity of the issues.
“Training it on larger databases will not solve the inherent problem: LLMs are unreliable because they do not know what words mean. Period. In fact, training on future databases that increasingly include the BS spouted by LLMs will make them even less trustworthy.”
Despite all of the doom and gloom talk from some experts, there are certainly plenty of other tech insiders out there who disagree – and who are putting their money where their mouths are.
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You’ll have to decide for yourself whether or not the confidence in the tech is misplaced or not.
Or maybe the rest of us regular people will just wait it out.
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