Absolutely unsurprising given the current state of hype. How to get rich: (A) Start a page that applies photoshop effects to user-uploaded pictures. (B) Secretly accomplish A using low-paid grunts. (C) Claim it's done with AI, obtain a billion dollars of VC money
At this rate every company should just start claiming their workers are human-lookalike cyborgs since being a plain-old honest company who doesn't lie about using human workers doesn't get the same boost as one using human workers but claiming the "AI" treatment.
AI is nonsense. Dijkstra was right. I'm not saying that silicon/mechanical intelligence isn't possible. I'm unaware of any physical law that precludes it. But what we currently call "AI" is just the pathetic fallacy run wild. All that said, multidimensional data-driven linear recognizers are pretty impressive.
> AI is nonsense. Dijkstra was right.
Define AI first.
One of the first few lines on Wikipedia about AI:
The scope of AI is disputed: as machines become increasingly capable, tasks considered as requiring "intelligence" are often removed from the definition, a phenomenon known as the AI effect, leading to the quip, "AI is whatever hasn't been done yet."
Absolutely unsurprising given the current state of hype. How to get rich: (A) Start a page that applies photoshop effects to user-uploaded pictures. (B) Secretly accomplish A using low-paid grunts. (C) Claim it's done with AI, obtain a billion dollars of VC money
At this rate every company should just start claiming their workers are human-lookalike cyborgs since being a plain-old honest company who doesn't lie about using human workers doesn't get the same boost as one using human workers but claiming the "AI" treatment.
What are some examples of companies claiming to use AI but instead actually using human workers?
AI is nonsense. Dijkstra was right. I'm not saying that silicon/mechanical intelligence isn't possible. I'm unaware of any physical law that precludes it. But what we currently call "AI" is just the pathetic fallacy run wild. All that said, multidimensional data-driven linear recognizers are pretty impressive.
> AI is nonsense. Dijkstra was right. Define AI first. One of the first few lines on Wikipedia about AI: The scope of AI is disputed: as machines become increasingly capable, tasks considered as requiring "intelligence" are often removed from the definition, a phenomenon known as the AI effect, leading to the quip, "AI is whatever hasn't been done yet."
AI is nonsense. Dijkstra was right. I'm not saying that silicon/mechanical intelligence isn't possible. I'm unaware of any physical law that precludes it. But what we currently call "AI" is just the pathetic fallacy run wild. All that said, multidimensional data-driven linear recognizers are pretty impressive.
> AI is nonsense. Dijkstra was right. Define AI first. One of the first few lines on Wikipedia about AI: The scope of AI is disputed: as machines become increasingly capable, tasks considered as requiring "intelligence" are often removed from the definition, a phenomenon known as the AI effect, leading to the quip, "AI is whatever hasn't been done yet."
I believe that intelligence is more than quantifiable. Von Neumann machines, no matter how complex, will never achieve intelligence. Again, to be completely clear, I’m not claiming machine intelligence is impossible, just that what we see presently isn’t it in any honest sense.
At this rate every company should just start claiming their workers are human-lookalike cyborgs since being a plain-old honest company who doesn't lie about using human workers doesn't get the same boost as one using human workers but claiming the "AI" treatment.
What are some examples of companies claiming to use AI but instead actually using human workers?
Mentioned in the article: Edison Software, Spinvox, X.ai, Clara, Expensify, Facebook.
Not sure guardian understands how training AI works.
There is a difference between labeling training data and just using humans to do the work. Some things cannot be achieved yet even with lots of labeled training data but companies are pretending they have solved hard ML problems at a high level of performance when the technology and research aren't there yet.
Absolutely unsurprising given the current state of hype. How to get rich: (A) Start a page that applies photoshop effects to user-uploaded pictures. (B) Secretly accomplish A using low-paid grunts. (C) Claim it's done with AI, obtain a billion dollars of VC money
You don't even need to do it secretly, just say it's the next step. See: Uber
Great to see the Guardian referencing back to Spinvox here, whose speech-to-text service turned out to be largely run be sweatshop workers in the Phillipines; and a warning from history: This shtick works as long as you can transition to AI. If not, then the service will become increasingly flaky until the business collapses.