Stephen Hawking was a genius in theoretical physics but he did not know much about computers and his fears of an AI takeover were unfounded.
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Dawkins thinks we didn’t evolve so as to understand consciousness. But that our odd situation points nowhere. Isn’t all this past its sell-by date?
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The United States has formally accused China of both funding and operating cells of hackers who infiltrate research labs working on responses to COVID-19.
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Turing thought that computers could be got to think. Thus he had to address Lovelace’s objection from a century earlier, that they could not be creative.
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Many high tech companies, including Microsoft, are headquartered near the coast in the state of Washington. The executives must have been terrified when they read the headline: “Tuna Biting Off Washington Coast” But wait. Tuna are not chomping on Seattle beaches. The headline, meant to convey good news for fishermen, can be read that way of course. We use common sense to identify the intended meaning and the incorrect interpretation makes us smile. But AI has trouble doing this because it lacks common sense. To solve the problem of AI’s lack of common sense, Microsoft’s co-founder Paul Allen (1953–2018) poured big bucks into Seattle’s Allen Institute for Artificial Intelligence. “To make real progress in A.I., we have to overcome the Read More ›
Neuroscientists used to think that each neuron was as complex as a switch. But newer research shows that each neuron is more similar to a microprocessor. Musk’s 3,000 Neuralink electrodes controlled by a single processor does not remotely match your brain’s 80 billion processors, all linked together.
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While many are concerned about all the jobs that AI will eliminate, no one is talking about the fact that AI needs humans. Information is the fuel that powers AI, and only humans can create this information. So, the real revolution that AI will bring is not data exploitation, but the empowering of people all around the world to power our economy through creation of information. What’s bad news for authoritarian groups like the Chinese Communist party is good news for everyone else.
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Findings patterns in data is easy. Finding meaningful patterns that have a logical basis and can be used to make accurate predictions is elusive. We can see this from 18th-century attempts to cure scurvy through 21st century claims about the stock market or history.
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In an unsanitized, politically incorrect (but factual) history, Selmer Bringsjord talks about how the tormented genius Kurt Gödel took up a quest that dated back a thousand years to prove the existence of God by formal logic. His original version didn’t quite work but his editor’s version passed an important logic test.
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Like Excel, AI assists programmers in their design work. AI can search through trillions of possibilities, using data from a million sources, to find a successful design. But the structure of the search and the source of the data is the choice of the programmer. A look at how famous inventors developed products that changed the world sheds some light on the process.
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The basic problem is that accepting on faith what we can’t ever hope to understand is not a traditional stance of science. Thus it’s a good question whether science could survive such a transition and still be recognizable to scientists. But does turning things over to incomprehensible algorithms, as Krakauer proposes, really work anyway? Current results from a variety of areas give pause for thought.
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Jonathan Bartlett agrees with Valley pioneers Davidow and Malone, authors of The Autonomous Revolution (2020) that there are real problems with the misuse of AI. But, he says, that’s because we treat it as powerful. It is a servant but we make it a master.
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AI sifts enormous amounts of accumulated data. But successful military strategy often depends on creating a new approach to a problem, one that lies outside the historical data available to the opposing forces. Muhammad Ali and Hannibal were famous for using such strategies.
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An issue left untouched is whether AI can, in principle, be creative in any event. There is no real evidence for that. The big worry, perhaps, is not being replaced by one’s tools but being ruled by them.
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Experts list various problems, including the fact that AI is vulnerable to failure due to unforeseen problems, including problems with data (too sparse, too noisy, too many outliers, etc.). It also doesn’t learn as well from experience as humans do.
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According to researchers, Ian Burkhart, whose hands and legs were paralyzed in a diving accident in 2010, has regained the sense of touch,, through a brain implant, as opposed to simply the ability to move a hand: The breakthrough came from analysis of years of data collected from NeuroLifeTM program study participant Ian Burkhart, who suffered a spinal cord injury in 2010 when diving into the ocean, and now lives with paralysis in his hands and legs. “When the chip was placed on the surface of Ian’s motor cortex in 2014, it was not known that the signals related to object touch could be observed because of the paralysis,” said lead author and Battelle Principal Research Scientist Patrick Ganzer. “Furthermore, Read More ›
If Alphabet’s Deep Mind or Microsoft had successfully data mined the 29,000 papers and found useful coronavirus information, that would be pretty impressive. But they appear to be giving others a chance to try instead, raising issues once again about the value of data mining in medicine.
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The underlying problem with creating immortality by uploading our minds to computers is that people are conscious and even the most sophisticated foreseeable computers are not. And we are not at all sure what consciousness even IS.
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At first, “shirts without stripes” might not seem like much of an issue but it turns out that many important and interesting problems for computers fundamentally reduce to this “halting problem.” And understanding human language is one of these problems.
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Computer scientist Selmer Bringsjord recalls, “I remember asking James Moor, the Dartmouth professor who’s written quite a bit on AI: “You know. Jim, you really are a true believer in this stuff but can you tell me how much time you’re willing to give these AI people? I mean, if we give them another thousand years, and we still don’t have cognition as I’ve characterized it… Are you going to be skeptical now?” He was, I suppose, as an academic, predictably clever and evasive, but the bottom line is, we don’t have this cognition captured.
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