Holloway: Neural networks get stymied by complex decisions due to the very processes that enable them to make any decisions at all. That’s a fundamental limitation.
Takehome: Humans can do things that AI cannot do, as we saw earlier, but those abilities are not due to the superior learning ability of a human neuron.
Holloway: : The human mind can do tasks that an artificial neural network (ANN) cannot. Because the brain works like an ANN, the mind cannot just be what the brain does.
Engineers doubt chance evolution because a computer using an evolution-based program to do simple tasks would be chugging away well past the heat death of our universe, as Eric Holloway demonstrates.
Eric Holloway looks at Richard Dawkins’ famous Darwinian evolution-only Weasel program in light of epigenetic information.
Rob Sheldon notes that the more real-world information we have, the less the bits weigh until, at very large amounts of information, they weigh almost nothing.
Holloway: If [Melvin] Vopson is correct we now have a mystery because his theory is in tension with the conservation of energy. The only solution is that the system is not closed. So where is the opening in the system? If the system is physically closed, then the influx of information must come from outside the physical realm.
Eric Holloway shows that, far from demonstrating evolution, Dawkins’ weasel program shows that natural selection prevents evolution from happening.
What is actually remarkable is the sheer amount of processing power needed to bring computers up to the level of even the most basic human player! This indicates the human mind is doing something totally different and extraordinarily more efficient than the best AI algorithms we have today.
Holloway: There are hard, practical reasons why computers cannot understand concepts like “infinity” and “truth” and therefore cannot be conscious.
Eric Holloway: A couple other interesting results from the research. First, human-derived organoids always outperform mouse-derived organoids in terms of volley length. Second, even without negative feedback, when the paddle missed the pong ball, the organoids still learn to increase volley length.
The Epicurean philosophy of pure physicalism is attractive to many but the logic of it, followed consistently, refutes itself.
The Turing test, and the Lovelace test, are attempts to determine if computers can show human-like intelligence. Holloway asks, what happens if researchers succeed in creating lifelike machines? in the sense of “wanting” things? “If we create an all-powerful artificial intelligence, we cannot assume it will be friendly. Thus, we need a Terminator test.”
After all, he argues, random processes are used all the time to model things in science: When we test a sequence of numbers for randomness, we are essentially testing how easy it is to predict the sequence of numbers. One of the simplest tests is to measure how frequently heads and tails occur during a Read More…
Eric Holloway: … randomness is unprovable, which was proven by three different computer scientists: Ray Solomonoff, Andrey Kolmogorov and Gregory Chaitin. The only thing we can know is that something is not random. Hence, we can never know that something originated from randomness.