#aihype — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #aihype, aggregated by home.social.
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CW: AI, books
@anthropy Not weird at all. I’ve looked but not found any *direct* evidence at all of book shredding, not even Amazon which was widely re-reported. No photos. No identified whistleblower. BBC followup reported a secondhand shop selling 3 boxes of books - which is evidence of what exactly? I posted once on #AmazonVGT3. The book shredding story had people justly riled, but is it a story intended to rile people? Apparently Musk said people shouldn’t shred books. Is it all part of an #AIHype machine?
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We are not getting "Artificial General Intelligence" from anything like the current systems (or ever, probably). This from Marty Hart-Landsberg:
"All multimodal generative AI systems are built using the same basic architecture, one based on largescale pattern recognition shaped by training data and statistical prediction, which makes it incapable of serving as a bridge to anything resembling AGI. This structure also limits its usefulness. Among the most serious problems: the amplification of biases and falsehoods contained in the training data and the tendency to hallucinate or present incorrect or entirely fabricated information as factual. These problems are a major reason why AI developers felt it necessary to pursue a growth strategy that relied on heavily subsidizing the cost of using their systems."
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We are not getting "Artificial General Intelligence" from anything like the current systems (or ever, probably). This from Marty Hart-Landsberg:
"All multimodal generative AI systems are built using the same basic architecture, one based on largescale pattern recognition shaped by training data and statistical prediction, which makes it incapable of serving as a bridge to anything resembling AGI. This structure also limits its usefulness. Among the most serious problems: the amplification of biases and falsehoods contained in the training data and the tendency to hallucinate or present incorrect or entirely fabricated information as factual. These problems are a major reason why AI developers felt it necessary to pursue a growth strategy that relied on heavily subsidizing the cost of using their systems."
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We are not getting "Artificial General Intelligence" from anything like the current systems (or ever, probably). This from Marty Hart-Landsberg:
"All multimodal generative AI systems are built using the same basic architecture, one based on largescale pattern recognition shaped by training data and statistical prediction, which makes it incapable of serving as a bridge to anything resembling AGI. This structure also limits its usefulness. Among the most serious problems: the amplification of biases and falsehoods contained in the training data and the tendency to hallucinate or present incorrect or entirely fabricated information as factual. These problems are a major reason why AI developers felt it necessary to pursue a growth strategy that relied on heavily subsidizing the cost of using their systems."
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We are not getting "Artificial General Intelligence" from anything like the current systems (or ever, probably). This from Marty Hart-Landsberg:
"All multimodal generative AI systems are built using the same basic architecture, one based on largescale pattern recognition shaped by training data and statistical prediction, which makes it incapable of serving as a bridge to anything resembling AGI. This structure also limits its usefulness. Among the most serious problems: the amplification of biases and falsehoods contained in the training data and the tendency to hallucinate or present incorrect or entirely fabricated information as factual. These problems are a major reason why AI developers felt it necessary to pursue a growth strategy that relied on heavily subsidizing the cost of using their systems."
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We are not getting "Artificial General Intelligence" from anything like the current systems (or ever, probably). This from Marty Hart-Landsberg:
"All multimodal generative AI systems are built using the same basic architecture, one based on largescale pattern recognition shaped by training data and statistical prediction, which makes it incapable of serving as a bridge to anything resembling AGI. This structure also limits its usefulness. Among the most serious problems: the amplification of biases and falsehoods contained in the training data and the tendency to hallucinate or present incorrect or entirely fabricated information as factual. These problems are a major reason why AI developers felt it necessary to pursue a growth strategy that relied on heavily subsidizing the cost of using their systems."