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Template:M intro technology rumours of our demise: Difference between revisions
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“Today,” he warned, “we have people doing work like robots. Tomorrow, we will have ''robots behaving like people''”. | “Today,” he warned, “we have people doing work like robots. Tomorrow, we will have ''robots behaving like people''”. | ||
You can see where he was coming from: what with high-frequency trading [[algorithm]]s, [[AI]] medical diagnosis, [[Alpha Go]], self-driving cars: the machines were coming for us. The machines have taken over our routine tasks; soon they will take the ''hard'' stuff, too | You can see where he was coming from: what with high-frequency trading [[algorithm]]s, [[AI]] medical diagnosis, [[Alpha Go]], self-driving cars: the machines were coming for us. And this was before GPT-3. It has only got worse since: The machines have taken over our routine tasks; soon they will take the ''hard'' stuff, too. | ||
Now. | Now. | ||
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But that’s an important condition: as George Gilder put it: | But that’s an important condition: as George Gilder put it: | ||
{{Quote|“The claim of superhuman performance seems rather overwrought to me. Outperforming unaided human beings is what machines are supposed to do. That’s why we build them.”<ref>{{br|Life After Google: The Fall of Big Data and the Rise of the Blockchain Economy}} (2018)</ref>}} | {{Quote|“The claim of superhuman performance seems rather overwrought to me. Outperforming unaided human beings is what machines are supposed to do. That’s why we build them.”<ref>{{br|Life After Google: The Fall of Big Data and the Rise of the Blockchain Economy}} (2018)</ref>}} | ||
===The [[division of labour]]=== | ===The [[division of labour]]=== | ||
Nowadays, we must distinguish between ''traditional'', obedient, rule-following machies, and ''randomly-make-it-up'' [[large language model]]s — unthinking, probabilistic, ''pattern-matching machines''. [[LLM]]s are the novelty act of 2023, at the top of their hype cycle right now, like [[Blockchain|blockchain]], was a year ago, and like [[DLT]] they will struggle to find an enduring use case. | Nowadays, we must distinguish between ''traditional'', obedient, rule-following machies, and ''randomly-make-it-up'' [[large language model]]s — unthinking, probabilistic, ''pattern-matching machines''. [[LLM]]s are the novelty act of 2023, at the top of their hype cycle right now, like [[Blockchain|blockchain]], was a year ago, and like [[DLT]] they will struggle to find an enduring use case. | ||