APPLE DISCOVERS AI JUST AS DUMB AS YOUR EX-BOYFRIEND, ONLY MORE EXPENSIVE
In what experts are calling a “no-sh!t revelation of the f@#king century,” Apple researchers have confirmed that fancy AI systems suffer “complete accuracy collapse” when asked to do literally anything more complex than set a timer or misunderstand your text message.
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The “pretty devastating” paper, written by people who actually understand technology, revealed that Large Reasoning Models (LRMs) – the digital equivalent of that guy at parties who thinks he knows everything – immediately fall apart when presented with problems requiring actual thinking.
“We’ve spent billions creating systems that are essentially just very expensive Magic 8-Balls,” said Dr. Obvious Conclusion, lead researcher at Apple’s Department of Things We Already Suspected. “Ask them to solve a complex ethical dilemma, and you might as well consult a drunk fortune cookie writer with a gambling addiction.”
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Despite the research showing these systems are about as reliable as a weather forecast from your conspiracy-loving uncle, tech companies continue throwing money at AI development like divorced dads at a strip club on payday.
“We’re confident we can overcome these fundamental limitations by simply ignoring them completely,” said Professor Hugh R. Delusional, Chief Innovation Officer at CompuThink Industries. “Our shareholders demand growth, and acknowledging reality has never been good for quarterly profits.”
According to made-up statistics that feel eerily accurate, 87% of AI responses to complex questions are just rephrased versions of things the AI read on Reddit, while the remaining 13% are complete hallucinations that would get a human fired, divorced, or possibly arrested.
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“This is a crucial moment for humanity to reflect on whether we should continue developing technology that fundamentally cannot do what we’re claiming it can do,” said ethical technology expert Dr. Sellout McHypocrite, speaking from the deck of his newly purchased yacht, the “S.S. Tech Bubble.”
The paper, which most tech executives will pretend to have read, suggests that AI systems might never reach the fabled “human-level intelligence” that developers keep promising, raising serious questions about the estimated $125 trillion being invested in making chatbots that can write slightly better knock-knock jokes.
“We’ve created digital assistants that confidently tell you Paris is the capital of Germany, then write a 5,000-word essay defending that position,” noted computational linguist Jane Actualfacts. “It’s like hiring someone who lies on their resume, except this employee costs millions to run and occasionally threatens to destroy humanity.”
At press time, Apple executives were reportedly considering whether to issue a formal response to their own company’s research, or just release another slightly different iPhone that costs $200 more.
