smart guy
genius actually
chatGPT welcome to the future
- ben ttech
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chatGPT welcome to the future
Harry R. Lewis has been a Harvard CS professor — teaching both Bill Gates and Mark Zuckerberg — and the dean of Harvard college. Born in 1947, Lewis remembers flipping the 18 toggle switches on Harvard's PDP-4 back in 1966 — up ("click!") or down ("CLACK"). And he thinks there's a lesson for today from a time when "Computers were experienced as physical things."
[T]he machine had a personality because it had a body you could feel and listen to. You could tell whether it was running smoothly by the way it sounded...
Unlike the unreliable mechanical contraptions of yore, today's computers — uninteresting though they may be to look at if you can find them at all — mostly don't break down, so we have fewer reasons to remember their physicality. Does it matter that the line between humans and the machines we have created has so blurred? Of course it does. We have known for a long time that we would eventually lose the calculation game to our creations; it has happened. We are likely to lose Turing's "Imitation Game" too, in which a computer program, communicating with a human via typed text, tries to fool the user into confusing it with a human at another keyboard. (ChatGPT and its ilk are disturbingly convincing conversationalists already.)
Our challenge, in the presence of ubiquitous, invisible, superior intelligent agents, will be to make sure that we, and our heirs and successors, remember what makes us human... All computers can do is pretend to be human. They can be, in the language of the late philosopher Daniel Dennett '63, counterfeit humans... The first error is suggesting that computers can be digitally trained to be superior versions of human intellects. And the second is inferring that human judgment will not be needed once computers get smart enough...
[N]o AI system can be divorced from the judgments of the humans who created it... Only hubristic humans could think that their counterfeits might completely substitute for human companionship, wisdom, curiosity, and judgment.â
Even back in 1966, Lewis says he learned two lessons that "have stood the test of time. Be careful what you ask them for. And it can be hard to tell what they are doing."
One example? "In those pre-miniaturization days, the ordinary operation of the central processor generated so much radiation that you would put a transistor radio on the console and tune it in between AM stations. From the other side of the room, the tone of the static indicated whether the machine had crashed or not."
https://www.harvardmagazine.com/2024/07 ... s-humanity
[T]he machine had a personality because it had a body you could feel and listen to. You could tell whether it was running smoothly by the way it sounded...
Unlike the unreliable mechanical contraptions of yore, today's computers — uninteresting though they may be to look at if you can find them at all — mostly don't break down, so we have fewer reasons to remember their physicality. Does it matter that the line between humans and the machines we have created has so blurred? Of course it does. We have known for a long time that we would eventually lose the calculation game to our creations; it has happened. We are likely to lose Turing's "Imitation Game" too, in which a computer program, communicating with a human via typed text, tries to fool the user into confusing it with a human at another keyboard. (ChatGPT and its ilk are disturbingly convincing conversationalists already.)
Our challenge, in the presence of ubiquitous, invisible, superior intelligent agents, will be to make sure that we, and our heirs and successors, remember what makes us human... All computers can do is pretend to be human. They can be, in the language of the late philosopher Daniel Dennett '63, counterfeit humans... The first error is suggesting that computers can be digitally trained to be superior versions of human intellects. And the second is inferring that human judgment will not be needed once computers get smart enough...
[N]o AI system can be divorced from the judgments of the humans who created it... Only hubristic humans could think that their counterfeits might completely substitute for human companionship, wisdom, curiosity, and judgment.â
Even back in 1966, Lewis says he learned two lessons that "have stood the test of time. Be careful what you ask them for. And it can be hard to tell what they are doing."
One example? "In those pre-miniaturization days, the ordinary operation of the central processor generated so much radiation that you would put a transistor radio on the console and tune it in between AM stations. From the other side of the room, the tone of the static indicated whether the machine had crashed or not."
https://www.harvardmagazine.com/2024/07 ... s-humanity
"disaster is the mother of necessity" rSin
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chatGPT welcome to the future
Gonna drop this video here...interesting, scary, and already in use...
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chatGPT welcome to the future
you can now get ChatGPT as an app for the smartphone, and you can talk to it no typing is involved,
really interesting i told it to switch languages and it did, really impressive..
https://www.youtube.com/watch?v=mxwpMrg ... el=LilyJay
really interesting i told it to switch languages and it did, really impressive..
https://www.youtube.com/watch?v=mxwpMrg ... el=LilyJay
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chatGPT welcome to the future
hey dill
ask the AI to generate an image
the christian 'NOFW' symbol
confined on all sides by a barbed wire fence,
with the word MORALITY used to illistrate the confinement
ive the image ive thought of in mind
curious what IT will come up with...
ask the AI to generate an image
the christian 'NOFW' symbol
confined on all sides by a barbed wire fence,
with the word MORALITY used to illistrate the confinement
ive the image ive thought of in mind
curious what IT will come up with...
"disaster is the mother of necessity" rSin
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chatGPT welcome to the future
Tech behemoth OpenAI has touted its artificial intelligence-powered transcription tool Whisper as having near "human level robustness and accuracy." But Whisper has a major flaw: It is prone to making up chunks of text or even entire sentences, according to interviews with more than a dozen software engineers, developers and academic researchers. Those experts said some of the invented text -- known in the industry as hallucinations -- can include racial commentary, violent rhetoric and even imagined medical treatments. Experts said that such fabrications are problematic because Whisper is being used in a slew of industries worldwide to translate and transcribe interviews, generate text in popular consumer technologies and create subtitles for videos.
The full extent of the problem is difficult to discern, but researchers and engineers said they frequently have come across Whisper's hallucinations in their work. A University of Michigan researcher conducting a study of public meetings, for example, said he found hallucinations in eight out of every 10 audio transcriptions he inspected, before he started trying to improve the model. A machine learning engineer said he initially discovered hallucinations in about half of the over 100 hours of Whisper transcriptions he analyzed. A third developer said he found hallucinations in nearly every one of the 26,000 transcripts he created with Whisper. The problems persist even in well-recorded, short audio samples. A recent study by computer scientists uncovered 187 hallucinations in more than 13,000 clear audio snippets they examined. That trend would lead to tens of thousands of faulty transcriptions over millions of recordings, researchers said. Further reading: AI Tool Cuts Unexpected Deaths In Hospital By 26%, Canadian Study Finds
https://m.slashdot.org/story/434823
The full extent of the problem is difficult to discern, but researchers and engineers said they frequently have come across Whisper's hallucinations in their work. A University of Michigan researcher conducting a study of public meetings, for example, said he found hallucinations in eight out of every 10 audio transcriptions he inspected, before he started trying to improve the model. A machine learning engineer said he initially discovered hallucinations in about half of the over 100 hours of Whisper transcriptions he analyzed. A third developer said he found hallucinations in nearly every one of the 26,000 transcripts he created with Whisper. The problems persist even in well-recorded, short audio samples. A recent study by computer scientists uncovered 187 hallucinations in more than 13,000 clear audio snippets they examined. That trend would lead to tens of thousands of faulty transcriptions over millions of recordings, researchers said. Further reading: AI Tool Cuts Unexpected Deaths In Hospital By 26%, Canadian Study Finds
https://m.slashdot.org/story/434823
"disaster is the mother of necessity" rSin
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