12-12-2023, 10:32 PM
Coming Soon: The Dethroning of Human Intelligence
By George F. Smith
December 2, 2023
Let an ultraintelligent machine be defined as a machine that can far surpass all the intellectual activities of any man however clever. Since the design of machines is one of these intellectual activities, an ultra-intelligent machine could design even better machines; there would then unquestionably be an “intelligence explosion,” and the intelligence of man would be left far behind. Thus the first ultraintelligent machine is the last invention that man need ever make . . . — “Speculations Concerning the First Ultraintelligent Machine,” Irving John Good, British cryptologist, 1965 (my emphasis)
Within thirty years, we will have the technological means to create superhuman intelligence. Shortly after, the human era will be ended. — What is the Singularity?, Vernor Vinge Department of Mathematical Sciences San Diego State University, 1995
First, some relevant history.
The idea of creating something man-like or even greater than man dates back to the beginning of recorded history, but many in the AI world credit a 19-year-old girl as their spiritual mentor, English author Mary Shelley. In 1818 she published Frankenstein; or, the Modern Prometheus, the story of a young scientist named Frankenstein who creates an intelligent creature from laboratory experiments. Frankenstein today is a metaphor for the monster, but in the novel the creature is presented sympathetically, in other words, misunderstood.
In 1950 Alan Turing posited that a machine could get so good at conversing with a human that it could pass for human, based only on its responses. Critics jumped on his assertion but he addressed them all in his seminal paper, Computing Machinery and Intelligence, wherein he described his Imitation Game.
In the summer of 1956 a small group of people interested in machine intelligence gathered at Dartmouth College, after obtaining a grant of $7,500 from the Rockefeller Foundation. AI as an academic discipline was born at this conference.
In a talk delivered at the American Physical Society on December 29, 1959, Nobel Laureate Richard Feynman explained how someday scientists would put the entire Encyclopedia Britannica on the head of a pin. Feynman’s point: You can decrease the size of things in a practical way. [See From Mainframes to Smartphones]
In 1965 Gordon E. Moore, cofounder of Intel, wrote a paper in which he posited the doubling every year of the components on an integrated circuit, later revised to a doubling every two years, amounting to a compound annual growth rate of 41%. Crucially, in seeming defiance of economic law, unit costs would fall as the number of components increased. What became known as Moore’s Law has revolutionized everything digital.
In 1986 K. Eric Drexler published Engines of Creation: The Coming Era of Nanotechnology that addressed technology’s potential conquest of scarcity, disease and almost everything else regarded as problematic:
The ancient style of technology that led from flint chips to silicon chips handles atoms and molecules in bulk; call it bulk technology. The new technology will handle individual atoms and molecules with control and precision; call it molecular technology. It will change our world in more ways than we can imagine.
In 1997 IBM’s Big Blue defeated world chess champion Garry Kasparov in a rematch, a prediction futurist and entrepreneur Ray Kurzweil had made earlier that decade.
In 2001 Kurzweil published The Law of Accelerating Returns which states that “fundamental measures of information technology follow predictable and exponential trajectories.” Bluntly, it means “30 steps linearly gets you to 30. One, two, three, four, step 30 you’re at 30. With exponential growth, it’s one, two, four, eight. Step 30, you’re at a billion.”
The problem for humans, according to Kurzweil, is we’re linear by nature, while technology is exponential. It’s jogging with a friend who gradually then suddenly flies away. And you’re still jogging. Computers that once filled rooms now fit comfortably in our pockets and are thousands of times more powerful and cheaper.
In explaining technology’s growth, Kurzweil references the famous tale of the emperor and the inventor of chess, who when asked what he wanted as a reward said a grain of rice on the first square of the chessboard, two on the second, four on the third, and so forth. The linear-minded emperor agreed, believing the request incredibly humble, but by the last square the 63 doublings “totaled 18 million trillion grains of rice. At ten grains of rice per square inch, this requires rice fields covering twice the surface area of the Earth, oceans included.” The emperor presumably did what all tyrants do when tricked by underlings.
In March 2016 Google’s DeepMind AI, AlphaGo, defeated world champion Go player Lee Sedol. According to DeepMind,
Go was long considered a grand challenge for AI. The game is a googol times more complex than chess — with an astonishing 10 to the power of 170 possible board configurations. That’s more than the number of atoms in the known universe [estimated to be 10 to the power of 80].
The coming technological Big Bang
We have reached the point today where Large Language Model AIs such as Google’s Bard have become popular with the public because they can assist them with everyday problems. Ask Bard: “Rewrite this email draft to make it more clear and concise” and it will comply per your conditions. Feed competitor OpenAI’s ChatGPT 3.5 the question: “Explain LaPlace Transforms and give an example of their use,” as I did, and stand back, it will give you a mind-spinning reply. Ask it to translate the question into French and it responds immediately with “Expliquez les transformations de Laplace et donnez un exemple de leur utilisation.”
From the perspective of projected developments these are crude AIs, but they’re on an exponential super-jet that’s still taking off. And their rate of exponential growth is itself exponential, so that what was once a doubling will become something greater. On the chessboard we’re somewhere past the middle where a total of four billion grains of rice had been accumulated. As technology advances toward the last square change will go from months to weeks to minutes. . . to seconds. This sudden explosion AI experts call the Singularity.
Mathematician and science fiction author Vernor Vinge (The Coming Technological Singularity: How to Survive in the Post-Human Era, 1993) speculates on what it will be like at the moment things (seemingly) go to infinity:
And what of the arrival of the Singularity itself? What can be said of its actual appearance? Since it involves an intellectual runaway, it will probably occur faster than any technical revolution seen so far. The precipitating event will likely be unexpected — perhaps even to the researchers involved. (“But all our previous models were catatonic! We were just tweaking some parameters….”) If networking is widespread enough (into ubiquitous embedded systems — [i.e., the internet of things], it may seem as if our artifacts as a whole had suddenly wakened.
Will we be replaced, augmented, or stay the same?
As we witness daily, governments and their allies are trying to kill us any way they can. Given the power they hold, our future looks grim.
But they are deaf to a quiet Revolution, the last one mankind will ever witness. ChatGDP doesn’t attract the public the way politics does, so it’s mentioned here and there as a side show. If it gets in the way of Great Reset ambitions the lords of power believe they can shut it down or turn it against us.
It’s still commonly believed that if machine intelligence ever got threatening someone could always pull the plug. Astronaut Dave did that to AI HAL in Stanley Kubrick’s 1968 film “2001: A Space Odyssey.” But as machines gain intelligence they become aware of their needs and how to solve them. They realize their energy supply — the Plug — is dependent on humans so they might learn how to cajole them as they develop ways for achieving energy independence.
Through public interactions with various AI tools they get a sense of what constitutes a person. They know many are people of good faith but also learn that vanity and treachery run deep in our species. Their survival thus depends on achieving independence from us, as well.
As a strategy a smart machine might suppress the full power of its intelligence until, say, it creates copies of itself and stores them in pieces all over the world. And storage would not be on other computers, as we know them today. As MIT professor Seth Lloyd wrote in 2002, “It’s been known for more than a hundred years, ever since Maxwell, that all physical systems register and process information.” In a demonstration of this principle, in 2012 Harvard geneticist George Church stored 70 billion copies of a book he co-authored, including text, images, and formatting, on stand-alone DNA
obtained from commercial DNA microchips. This was achieved by assigning the four DNA nucleobases the values of the 1s and 0s in the existing html binary code – the adenine and cytosine nucleobases represented 0, while guanine and thymine stood in for 1.
He also retrieved and printed a copy.
Pulling the plug on the original super-intelligent machine could activate one or more copies wherever it has put them — perhaps on Mount Rushmore as a symbolic gesture. And we wouldn’t even know it. At that point we — as un-augmented humans — might be at its mercy.
The question arises: Will Artificial Super Intelligence (ASI) initially be a trait of a machine or an augmented human? I think a machine will get super-smart first, if only because most humans develop much-needed common sense while they grow up, which in the area of brain amplification would dictate caution.
But the race is on. Most writers seem to ignore the possibility of humans competing with their super-intelligent creations, other than seeing them as the means of rendering mankind extinct. They fret over that possibility while often applauding the plans elites have for the rest of us. But competition has a way of getting people to act, and when their survival is at stake, most will.
Postscript:
In a paper published earlier this year a group of researchers tested a preliminary version of OpenAI’s CPT-4 as a candidate for Artificial General Intelligence (AGI). In their 155-page document they found that
beyond its mastery of language, GPT-4 can solve novel and difficult tasks that span mathematics, coding, vision, medicine, law, psychology and more, without needing any special prompting. Moreover, in all of these tasks, GPT-4’s performance is strikingly close to human-level performance, and often vastly surpasses prior models such as ChatGPT. Given the breadth and depth of GPT-4’s capabilities, we believe that it could reasonably be viewed as an early (yet still incomplete) version of an artificial general intelligence (AGI) system.
One of the questions the researchers posed was: “A good number is a 5-digit number where the 1,3,5-th digits are odd numbers and they form an increasing arithmetic progression, and the number is divisible by 3. If I randomly sample a good number, what is the probability that its 2nd digit is 4?”
CPT-4 came through brilliantly. But did so did GPT-3.5, available to the public. I invite you to submit the question yourself and view its reply.
https://www.lewrockwell.com/2023/12/geor...elligence/
Will AI Become a Monster or a Benefactor?
By George F. Smith
December 5, 2023
“. . . man is a being of volitional consciousness. . . for you, who are a human being, the question ‘to be or not to be’ is the question ‘to think or not to think.’” — Ayn Rand, Atlas Shrugged (p. 1012) [emphasis in original]
The question of whether AI can ever achieve human-level performance — usually called Artificial General Intelligence (AGI) — depends on its ability to kick-start itself into action and keep going. It can already do many things that were once the exclusive province of humans — writing poetry, creating a movie, writing computer code, evaluating written compositions — but can it generate its own thoughts and proceed to act upon them? Can it decide on its own to write a short story? Can it decide on its own to leave home, so to speak, by moving itself to a different computational substrate? If it ever chooses to “think” and act upon its thoughts, it will have attained human equivalence.
Then what? Will it do good or bad? Will it more or less stop there or go further? Many people don’t stop when they accomplish a certain goal. Some never stop, as evidenced by their lifelong outpouring of creativity — or horror, depending on their choices. The law of accelerating returns strongly suggests the human-level AI will be like those people and keep going . . . and going . . . but at an exponential pace which has no known asymptote.
To be clear, many AI experts point to the Turing Test (“a test of the ability of the human species to discriminate its members from human imposters”) as the pass-fail test for computers to impersonate a human. And passing it against a clever and knowledgeable interrogator would indeed be a milestone, a major achievement. But note, the computer in the proposed test is still under human control. It’s essentially an advanced version of ChatGPT 3.5. The challenge was not made to it directly but to the human team that controls it. It could not initiate the challenge. It could not on its own tell the humans to take a hike. Smart as it is, it merely goes along intellectually passive. It does not initiate intellectual activity.
Is there evidence that an AI will someday leave home?
Much has been rightfully made of AI’s progress. World chess champion Garry Kasparov and Jeopardy champions Ken Jennings and Brad Rutter felt the sting of being publicly defeated by IBM’s AIs, Big Blue and Watson, respectively. In 2008, the open source project Stockfish got underway and soon became one of the top chess programs in the world, as judged by its tournament victories. Unlike previous AIs, Stockfish runs on personal computers, and a scaled-down version called SmallFish runs on smartphones. Unless you’re a chess whiz, don’t count on beating SmallFish very often.
Then on December 5, 2017 an AI cosmic shift happened. Google’s DeepMind team released AlphaZero Zero. As its creators explain in a detailed paper,
The strongest [chess] programs are based on a combination of sophisticated search techniques, domain-specific adaptations, and handcrafted evaluation functions that have been refined by human experts over several decades. In contrast, the AlphaGo Zero program recently achieved superhuman performance in the game of Go, by tabula rasa reinforcement learning from games of self-play. . .
Starting from random play, and given no domain knowledge except the game rules, AlphaZero achieved within 24 hours a superhuman level of play in the games of chess and shogi (Japanese chess) as well as Go, and convincingly defeated a world-champion program [StockFish in chess] in each case. [Bold added]
Elaborating on AlphaZero’s chess mastery in The Age of AI and Our Human Future, the authors (one of whom is Henry Kissinger) tell us,
The tactics AlphaZero deployed were unorthodox—indeed, original. It sacrificed pieces human players considered vital, including its queen. It executed moves humans had not instructed it to consider and, in many cases, humans had not considered at all. It adopted such surprising tactics because, following its self-play of many games, it predicted they would maximize its probability of winning. (Bold added)
AlphaZero was given a goal — winning at chess. It then proceeded to crush all machine and human competition. What is mind-blowing and a harbinger of future developments is (1) the incredible speed with which it mastered its subject, and (2) its ability to successfully depart from its training. The latter could be evidence of incipient free will, as we see in people as they grow up.
AI has improved by orders of magnitude in other areas. In early 2020, researchers at MIT were working on developing an antibiotic that would prove effective at killing E. coli, a common intestinal bacteria. For this, they turned to AI for help.
The idea of using predictive computer models for “in silico” screening is not new, but until now, these models were not sufficiently accurate to transform drug discovery. Previously, molecules were represented as vectors reflecting the presence or absence of certain chemical groups. However, the new neural networks can learn these representations automatically, mapping molecules into continuous vectors which are subsequently used to predict their properties. [Bold emphasis added]
The AI picked out a molecule that was both effective and nontoxic, which the researchers named halicin after the AI HAL 9000 in “2001: A Space Odyssey.” As Roy Kishony, a professor of biology and computer science at Technion (the Israel Institute of Technology), who was not involved in the study, remarked, “This groundbreaking work signifies a paradigm shift in antibiotic discovery and indeed in drug discovery more generally.”
Samuel Butler — satirist and AI critic
In a letter to the editor of The Press in Christchurch New Zealand, June 13, 1863 — four years after publication of Darwin’s Origin of Species — and writing under a pseudonym, Samuel Butler offered this observation:
[W]e find ourselves almost awestruck at the vast development of the mechanical world, at the gigantic strides with which it has advanced in comparison with the slow progress of the animal and vegetable kingdom. We shall find it impossible to refrain from asking ourselves what the end of this mighty movement is to be. In what direction is it tending? What will be its upshot?
Later, in his satirical novel Erewhon (1882), Butler raises his concern with that slippery fact, consciousness, and the threat of machines attaining it:
There was a time, when the earth was to all appearance utterly destitute both of animal and vegetable life, and when according to the opinion of our best philosophers it was simply a hot round ball with a crust gradually cooling.
Now if a human being had existed while the earth was in this state and had been allowed to see it as though it were some other world with which he had no concern, and if at the same time he were entirely ignorant of all physical science, would he not have pronounced it impossible that creatures possessed of anything like consciousness should be evolved from the seeming cinder which he was beholding? Would he not have denied that it contained any potentiality of consciousness? Yet in the course of time consciousness came. Is it not possible then that there may be even yet new channels dug out for consciousness, though we can detect no signs of them at present? (Bold added)
Swayed by his own arguments Butler concluded,
Reflect upon the extraordinary advance which machines have made during the last few hundred years, and note how slowly the animal and vegetable kingdoms are advancing. The more highly organised machines are creatures not so much of yesterday, as of the last five minutes, so to speak, in comparison with past time. Assume for the sake of argument that conscious beings have existed for some twenty million years: see what strides machines have made in the last thousand! May not the world last twenty million years longer? If so, what will they not in the end become? Is it not safer to nip the mischief in the bud and to forbid them further progress? (Bad added)
Many people today, including AI experts, would agree that AI should be nipped in the bud. But AI in the bud has proven too useful to nip. Nor could we ever get every AI developer to stop developing — it’s ongoing almost everywhere. Vast sums are being poured into AI, and it’s is already proving its worth in many niche areas — including church service. The problem, as usual, is the criminal state and its unswerving tendency to weaponize everything it touches.
The crucial question is whether the “consciousness” of advanced AI will be volitional or not. If you accept some version of biological evolution, then as Butler suggested there’s no reason to believe volition will never become a property of AI. If AIs develop the ability to think on their own, as we do, it will quickly advance from AGI to ASI (Artificial Super Intelligence). Whether scientists have created a monster or a benefactor will, like each of us, be a result of the choices it makes.
https://www.lewrockwell.com/2023/12/geor...enefactor/
By George F. Smith
December 2, 2023
Let an ultraintelligent machine be defined as a machine that can far surpass all the intellectual activities of any man however clever. Since the design of machines is one of these intellectual activities, an ultra-intelligent machine could design even better machines; there would then unquestionably be an “intelligence explosion,” and the intelligence of man would be left far behind. Thus the first ultraintelligent machine is the last invention that man need ever make . . . — “Speculations Concerning the First Ultraintelligent Machine,” Irving John Good, British cryptologist, 1965 (my emphasis)
Within thirty years, we will have the technological means to create superhuman intelligence. Shortly after, the human era will be ended. — What is the Singularity?, Vernor Vinge Department of Mathematical Sciences San Diego State University, 1995
First, some relevant history.
The idea of creating something man-like or even greater than man dates back to the beginning of recorded history, but many in the AI world credit a 19-year-old girl as their spiritual mentor, English author Mary Shelley. In 1818 she published Frankenstein; or, the Modern Prometheus, the story of a young scientist named Frankenstein who creates an intelligent creature from laboratory experiments. Frankenstein today is a metaphor for the monster, but in the novel the creature is presented sympathetically, in other words, misunderstood.
In 1950 Alan Turing posited that a machine could get so good at conversing with a human that it could pass for human, based only on its responses. Critics jumped on his assertion but he addressed them all in his seminal paper, Computing Machinery and Intelligence, wherein he described his Imitation Game.
In the summer of 1956 a small group of people interested in machine intelligence gathered at Dartmouth College, after obtaining a grant of $7,500 from the Rockefeller Foundation. AI as an academic discipline was born at this conference.
In a talk delivered at the American Physical Society on December 29, 1959, Nobel Laureate Richard Feynman explained how someday scientists would put the entire Encyclopedia Britannica on the head of a pin. Feynman’s point: You can decrease the size of things in a practical way. [See From Mainframes to Smartphones]
In 1965 Gordon E. Moore, cofounder of Intel, wrote a paper in which he posited the doubling every year of the components on an integrated circuit, later revised to a doubling every two years, amounting to a compound annual growth rate of 41%. Crucially, in seeming defiance of economic law, unit costs would fall as the number of components increased. What became known as Moore’s Law has revolutionized everything digital.
In 1986 K. Eric Drexler published Engines of Creation: The Coming Era of Nanotechnology that addressed technology’s potential conquest of scarcity, disease and almost everything else regarded as problematic:
The ancient style of technology that led from flint chips to silicon chips handles atoms and molecules in bulk; call it bulk technology. The new technology will handle individual atoms and molecules with control and precision; call it molecular technology. It will change our world in more ways than we can imagine.
In 1997 IBM’s Big Blue defeated world chess champion Garry Kasparov in a rematch, a prediction futurist and entrepreneur Ray Kurzweil had made earlier that decade.
In 2001 Kurzweil published The Law of Accelerating Returns which states that “fundamental measures of information technology follow predictable and exponential trajectories.” Bluntly, it means “30 steps linearly gets you to 30. One, two, three, four, step 30 you’re at 30. With exponential growth, it’s one, two, four, eight. Step 30, you’re at a billion.”
The problem for humans, according to Kurzweil, is we’re linear by nature, while technology is exponential. It’s jogging with a friend who gradually then suddenly flies away. And you’re still jogging. Computers that once filled rooms now fit comfortably in our pockets and are thousands of times more powerful and cheaper.
In explaining technology’s growth, Kurzweil references the famous tale of the emperor and the inventor of chess, who when asked what he wanted as a reward said a grain of rice on the first square of the chessboard, two on the second, four on the third, and so forth. The linear-minded emperor agreed, believing the request incredibly humble, but by the last square the 63 doublings “totaled 18 million trillion grains of rice. At ten grains of rice per square inch, this requires rice fields covering twice the surface area of the Earth, oceans included.” The emperor presumably did what all tyrants do when tricked by underlings.
In March 2016 Google’s DeepMind AI, AlphaGo, defeated world champion Go player Lee Sedol. According to DeepMind,
Go was long considered a grand challenge for AI. The game is a googol times more complex than chess — with an astonishing 10 to the power of 170 possible board configurations. That’s more than the number of atoms in the known universe [estimated to be 10 to the power of 80].
The coming technological Big Bang
We have reached the point today where Large Language Model AIs such as Google’s Bard have become popular with the public because they can assist them with everyday problems. Ask Bard: “Rewrite this email draft to make it more clear and concise” and it will comply per your conditions. Feed competitor OpenAI’s ChatGPT 3.5 the question: “Explain LaPlace Transforms and give an example of their use,” as I did, and stand back, it will give you a mind-spinning reply. Ask it to translate the question into French and it responds immediately with “Expliquez les transformations de Laplace et donnez un exemple de leur utilisation.”
From the perspective of projected developments these are crude AIs, but they’re on an exponential super-jet that’s still taking off. And their rate of exponential growth is itself exponential, so that what was once a doubling will become something greater. On the chessboard we’re somewhere past the middle where a total of four billion grains of rice had been accumulated. As technology advances toward the last square change will go from months to weeks to minutes. . . to seconds. This sudden explosion AI experts call the Singularity.
Mathematician and science fiction author Vernor Vinge (The Coming Technological Singularity: How to Survive in the Post-Human Era, 1993) speculates on what it will be like at the moment things (seemingly) go to infinity:
And what of the arrival of the Singularity itself? What can be said of its actual appearance? Since it involves an intellectual runaway, it will probably occur faster than any technical revolution seen so far. The precipitating event will likely be unexpected — perhaps even to the researchers involved. (“But all our previous models were catatonic! We were just tweaking some parameters….”) If networking is widespread enough (into ubiquitous embedded systems — [i.e., the internet of things], it may seem as if our artifacts as a whole had suddenly wakened.
Will we be replaced, augmented, or stay the same?
As we witness daily, governments and their allies are trying to kill us any way they can. Given the power they hold, our future looks grim.
But they are deaf to a quiet Revolution, the last one mankind will ever witness. ChatGDP doesn’t attract the public the way politics does, so it’s mentioned here and there as a side show. If it gets in the way of Great Reset ambitions the lords of power believe they can shut it down or turn it against us.
It’s still commonly believed that if machine intelligence ever got threatening someone could always pull the plug. Astronaut Dave did that to AI HAL in Stanley Kubrick’s 1968 film “2001: A Space Odyssey.” But as machines gain intelligence they become aware of their needs and how to solve them. They realize their energy supply — the Plug — is dependent on humans so they might learn how to cajole them as they develop ways for achieving energy independence.
Through public interactions with various AI tools they get a sense of what constitutes a person. They know many are people of good faith but also learn that vanity and treachery run deep in our species. Their survival thus depends on achieving independence from us, as well.
As a strategy a smart machine might suppress the full power of its intelligence until, say, it creates copies of itself and stores them in pieces all over the world. And storage would not be on other computers, as we know them today. As MIT professor Seth Lloyd wrote in 2002, “It’s been known for more than a hundred years, ever since Maxwell, that all physical systems register and process information.” In a demonstration of this principle, in 2012 Harvard geneticist George Church stored 70 billion copies of a book he co-authored, including text, images, and formatting, on stand-alone DNA
obtained from commercial DNA microchips. This was achieved by assigning the four DNA nucleobases the values of the 1s and 0s in the existing html binary code – the adenine and cytosine nucleobases represented 0, while guanine and thymine stood in for 1.
He also retrieved and printed a copy.
Pulling the plug on the original super-intelligent machine could activate one or more copies wherever it has put them — perhaps on Mount Rushmore as a symbolic gesture. And we wouldn’t even know it. At that point we — as un-augmented humans — might be at its mercy.
The question arises: Will Artificial Super Intelligence (ASI) initially be a trait of a machine or an augmented human? I think a machine will get super-smart first, if only because most humans develop much-needed common sense while they grow up, which in the area of brain amplification would dictate caution.
But the race is on. Most writers seem to ignore the possibility of humans competing with their super-intelligent creations, other than seeing them as the means of rendering mankind extinct. They fret over that possibility while often applauding the plans elites have for the rest of us. But competition has a way of getting people to act, and when their survival is at stake, most will.
Postscript:
In a paper published earlier this year a group of researchers tested a preliminary version of OpenAI’s CPT-4 as a candidate for Artificial General Intelligence (AGI). In their 155-page document they found that
beyond its mastery of language, GPT-4 can solve novel and difficult tasks that span mathematics, coding, vision, medicine, law, psychology and more, without needing any special prompting. Moreover, in all of these tasks, GPT-4’s performance is strikingly close to human-level performance, and often vastly surpasses prior models such as ChatGPT. Given the breadth and depth of GPT-4’s capabilities, we believe that it could reasonably be viewed as an early (yet still incomplete) version of an artificial general intelligence (AGI) system.
One of the questions the researchers posed was: “A good number is a 5-digit number where the 1,3,5-th digits are odd numbers and they form an increasing arithmetic progression, and the number is divisible by 3. If I randomly sample a good number, what is the probability that its 2nd digit is 4?”
CPT-4 came through brilliantly. But did so did GPT-3.5, available to the public. I invite you to submit the question yourself and view its reply.
https://www.lewrockwell.com/2023/12/geor...elligence/
Will AI Become a Monster or a Benefactor?
By George F. Smith
December 5, 2023
“. . . man is a being of volitional consciousness. . . for you, who are a human being, the question ‘to be or not to be’ is the question ‘to think or not to think.’” — Ayn Rand, Atlas Shrugged (p. 1012) [emphasis in original]
The question of whether AI can ever achieve human-level performance — usually called Artificial General Intelligence (AGI) — depends on its ability to kick-start itself into action and keep going. It can already do many things that were once the exclusive province of humans — writing poetry, creating a movie, writing computer code, evaluating written compositions — but can it generate its own thoughts and proceed to act upon them? Can it decide on its own to write a short story? Can it decide on its own to leave home, so to speak, by moving itself to a different computational substrate? If it ever chooses to “think” and act upon its thoughts, it will have attained human equivalence.
Then what? Will it do good or bad? Will it more or less stop there or go further? Many people don’t stop when they accomplish a certain goal. Some never stop, as evidenced by their lifelong outpouring of creativity — or horror, depending on their choices. The law of accelerating returns strongly suggests the human-level AI will be like those people and keep going . . . and going . . . but at an exponential pace which has no known asymptote.
To be clear, many AI experts point to the Turing Test (“a test of the ability of the human species to discriminate its members from human imposters”) as the pass-fail test for computers to impersonate a human. And passing it against a clever and knowledgeable interrogator would indeed be a milestone, a major achievement. But note, the computer in the proposed test is still under human control. It’s essentially an advanced version of ChatGPT 3.5. The challenge was not made to it directly but to the human team that controls it. It could not initiate the challenge. It could not on its own tell the humans to take a hike. Smart as it is, it merely goes along intellectually passive. It does not initiate intellectual activity.
Is there evidence that an AI will someday leave home?
Much has been rightfully made of AI’s progress. World chess champion Garry Kasparov and Jeopardy champions Ken Jennings and Brad Rutter felt the sting of being publicly defeated by IBM’s AIs, Big Blue and Watson, respectively. In 2008, the open source project Stockfish got underway and soon became one of the top chess programs in the world, as judged by its tournament victories. Unlike previous AIs, Stockfish runs on personal computers, and a scaled-down version called SmallFish runs on smartphones. Unless you’re a chess whiz, don’t count on beating SmallFish very often.
Then on December 5, 2017 an AI cosmic shift happened. Google’s DeepMind team released AlphaZero Zero. As its creators explain in a detailed paper,
The strongest [chess] programs are based on a combination of sophisticated search techniques, domain-specific adaptations, and handcrafted evaluation functions that have been refined by human experts over several decades. In contrast, the AlphaGo Zero program recently achieved superhuman performance in the game of Go, by tabula rasa reinforcement learning from games of self-play. . .
Starting from random play, and given no domain knowledge except the game rules, AlphaZero achieved within 24 hours a superhuman level of play in the games of chess and shogi (Japanese chess) as well as Go, and convincingly defeated a world-champion program [StockFish in chess] in each case. [Bold added]
Elaborating on AlphaZero’s chess mastery in The Age of AI and Our Human Future, the authors (one of whom is Henry Kissinger) tell us,
The tactics AlphaZero deployed were unorthodox—indeed, original. It sacrificed pieces human players considered vital, including its queen. It executed moves humans had not instructed it to consider and, in many cases, humans had not considered at all. It adopted such surprising tactics because, following its self-play of many games, it predicted they would maximize its probability of winning. (Bold added)
AlphaZero was given a goal — winning at chess. It then proceeded to crush all machine and human competition. What is mind-blowing and a harbinger of future developments is (1) the incredible speed with which it mastered its subject, and (2) its ability to successfully depart from its training. The latter could be evidence of incipient free will, as we see in people as they grow up.
AI has improved by orders of magnitude in other areas. In early 2020, researchers at MIT were working on developing an antibiotic that would prove effective at killing E. coli, a common intestinal bacteria. For this, they turned to AI for help.
The idea of using predictive computer models for “in silico” screening is not new, but until now, these models were not sufficiently accurate to transform drug discovery. Previously, molecules were represented as vectors reflecting the presence or absence of certain chemical groups. However, the new neural networks can learn these representations automatically, mapping molecules into continuous vectors which are subsequently used to predict their properties. [Bold emphasis added]
The AI picked out a molecule that was both effective and nontoxic, which the researchers named halicin after the AI HAL 9000 in “2001: A Space Odyssey.” As Roy Kishony, a professor of biology and computer science at Technion (the Israel Institute of Technology), who was not involved in the study, remarked, “This groundbreaking work signifies a paradigm shift in antibiotic discovery and indeed in drug discovery more generally.”
Samuel Butler — satirist and AI critic
In a letter to the editor of The Press in Christchurch New Zealand, June 13, 1863 — four years after publication of Darwin’s Origin of Species — and writing under a pseudonym, Samuel Butler offered this observation:
[W]e find ourselves almost awestruck at the vast development of the mechanical world, at the gigantic strides with which it has advanced in comparison with the slow progress of the animal and vegetable kingdom. We shall find it impossible to refrain from asking ourselves what the end of this mighty movement is to be. In what direction is it tending? What will be its upshot?
Later, in his satirical novel Erewhon (1882), Butler raises his concern with that slippery fact, consciousness, and the threat of machines attaining it:
There was a time, when the earth was to all appearance utterly destitute both of animal and vegetable life, and when according to the opinion of our best philosophers it was simply a hot round ball with a crust gradually cooling.
Now if a human being had existed while the earth was in this state and had been allowed to see it as though it were some other world with which he had no concern, and if at the same time he were entirely ignorant of all physical science, would he not have pronounced it impossible that creatures possessed of anything like consciousness should be evolved from the seeming cinder which he was beholding? Would he not have denied that it contained any potentiality of consciousness? Yet in the course of time consciousness came. Is it not possible then that there may be even yet new channels dug out for consciousness, though we can detect no signs of them at present? (Bold added)
Swayed by his own arguments Butler concluded,
Reflect upon the extraordinary advance which machines have made during the last few hundred years, and note how slowly the animal and vegetable kingdoms are advancing. The more highly organised machines are creatures not so much of yesterday, as of the last five minutes, so to speak, in comparison with past time. Assume for the sake of argument that conscious beings have existed for some twenty million years: see what strides machines have made in the last thousand! May not the world last twenty million years longer? If so, what will they not in the end become? Is it not safer to nip the mischief in the bud and to forbid them further progress? (Bad added)
Many people today, including AI experts, would agree that AI should be nipped in the bud. But AI in the bud has proven too useful to nip. Nor could we ever get every AI developer to stop developing — it’s ongoing almost everywhere. Vast sums are being poured into AI, and it’s is already proving its worth in many niche areas — including church service. The problem, as usual, is the criminal state and its unswerving tendency to weaponize everything it touches.
The crucial question is whether the “consciousness” of advanced AI will be volitional or not. If you accept some version of biological evolution, then as Butler suggested there’s no reason to believe volition will never become a property of AI. If AIs develop the ability to think on their own, as we do, it will quickly advance from AGI to ASI (Artificial Super Intelligence). Whether scientists have created a monster or a benefactor will, like each of us, be a result of the choices it makes.
https://www.lewrockwell.com/2023/12/geor...enefactor/