Cognitive Physics | Computational Minds

As weird as it may sound, we seem to be studying our brain in the same manner that we would study alien technology. Just as we are trying to imitate the fusion of stars for a source of power, we are also trying to imitate the computational capacity of our brain, and the pioneers of this field were not at all shy about these ambitions. In fact, long before “computers” were ever called “computers”, they were referred to as “electronic brains” when they were first being conceived of by the likes of Claude Shannon and Alan Turing, and by no means is this a coincidence. This should not come as a shock to anyone though, our brains happens to be the most potent computer known to exist. Why wouldn’t we imitate them? Like so many other forms of technology, computers seem to take their inspiration from nature, and matching its capability has been the holy grail of computer science since their inception.

Claude Shannon

Many have heard the term “bits” and have certainly heard of Bytes, Megabytes and Gigabytes, Terabytes and the like, but few seem understand the significance or impact of the underlying theory from which these terms have emerged. “Information Theory”, where the term ‘bits’ hails from, has not only made waves in the field of computer science, but has also made similar waves in the realm of biology and cognitive science just the same. Since its advent, Information Theory has even gone on to help form other emergent fields such as Computational Biology, and Computational Neuroscience. Because of fields such as this, it is commonplace to liken the brain to that of a computer, and most people wouldn’t even bat an eyelash at such notions in this day and age. When we advance our understanding of computers, it seems as if we also tend to advance our understanding of ourselves. However, it is equally important to acknowledge that not all computers are equal and there just as many differences as similarities between our brain and modern computers at present.

Alan Turing

Computers do seem to have their own teleology though, and they are optimized for or even dedicated to the types of algorithms that they tend to run. This understanding is part of what made Alan Turing immortal in the field of computation. As an example, quantum computers are optimal for quantum algorithms and classical computers are optimal for classical algorithms. Without getting into performance specs, let’s imagine for a moment that we simply had a quantum computer sitting next to a classical computer. If we were unable tell which computer was which for whatever reason, we could simply feed both of them a quantum algorithm and presume that the one which provided us an output the fastest is the one most likely quantum computer. Conversely, if we were to present these same computers with a classical algorithm, we should find that the classical computer edges out the quantum computer or have a comparable output time at the very least. As such and when looking at the types of algorithms that computer runs the most efficiently, doing so can help us gauge and identify the type of computer that we are working with.

Hypothetically² and just like any other computer, we too do not seem to run all algorithms equally. If our own brain were actually a computer, then it should also have its own teleology as well, and when looking at the types of algorithms which we seem to run best, we too may also be able to further deduce the type of computer that our brain may be. In order to better visualize this, it helps to consider the computational clout required to beat us.

For instance and in spite of our amazing brain which supposedly operates in the realm of petaflops or exaflops, a TI-84 operating at a measly 90 flops would humble the lot of us as far as mathematical calculations are concerned. Sure, some savants may be able to hang in some respects, but I highly doubt that they can categorically out-calculator a calculator. However, when it comes time to beat us at chess or Jeopardy, it takes a *tad* more than the 90 FLOPS of processing ability. In fact and when measured by FLOPS alone, it would require more TI-84’s (8.889×10¹¹) than neurons in our brain or stars in our own galaxy to beat us at trivia.

In order to beat us at Jeopardy, it required IBM and 7 tons of Watson operating at 80 teraflops. At the time, Watson was comprised of 90 IBM Power 750 servers, 720 processing cores, 2,880 processing threads, and 16 terabytes of RAM while consuming 20,000 watts of power. It was also preloaded with encyclopedias, dictionaries and news feeds with the capability to process roughly 1 million books or 500GB of data per second. In comparison to Watson, our brain supposedly consumes a paltry 20 watts of power or 1000x less than Watson, while also weighing only 3lbs or 4666x less.

While beating a human at trivia, let alone Ken Jennings, is a massive achievement for computer science, IBM, and Watson, this is still ultimately a feather in our cap when looking at what it takes to beat us. At present time and even if we strung together every server in the world, we lack both the computational and algorithmic understanding to mimic the cognition of a toddler in it’s entirety, let alone a sentient adult. On top of being a handful at trivia, our brain is subconsciously handling life support and motor functions while tying in all of our senses together with an 80ms delay between reality and cognition. Even if we could match our brain categorically with a supercomputer like Watson though, we would still have a long way to go before we could ever accomplish such a feat with 20 watts of power in a ‘electronic brain’ that weighs less than my MacBook Pro.

For reasons such as this, most people in the computer science world seem to agree that quantum computing is the only way that we see true artificial intelligence. As such and if it is going to take a quantum computer to match us, then I do not think that it is unreasonable to speculate that our brain may be a functional quantum computer instead of a classical system which it is presently believed to be. It takes one to know one in a sense, and if you’re going to beat a quantum computer, you’re going to have a rough time unless you’re also using a quantum computer. All of which may be part of the reason why the likes of Sir Roger Penrose, Eugene Wigner, Stuart Hameroff and Matthew Fisher have chosen to pose the question of whether or not our brain could be a quantum computer; although not without their critics.

Quantum computers are not advantageous for everything though, just as I am not of any help on matters pertaining to interior decorating. Where quantum computers truly set themselves apart and strut their stuff are on matters pertaining to polynomials, probability, speech recognition, optimization problems, and quantum algorithms, etc etc. If you would like a practical example, a D-Wave X2 quantum computer can run a quantum algorithm 10⁸ or 100,000,000x faster than a classical computer; and they are just getting warmed up. When compared to a an array of servers or supercomputer tasked with the same algorithms, even now, a D-Wave X2 will consume significantly less power and less space while still outperforming them categorically, much like our own brain, and their size, energy consumption and performance will only become more efficient as time goes on.


In spite of having high profile proponents though, the notion of a quantum mind also has it’s opponents and they have not been coy with their opinions. For instance, Patricia Churchland likened it to “Pixie Dust in the synapses” while Victor Stenger, likened it to “Unicorns and Dragons”. While such notions seemed ludicrous to them and many others, they have also failed to realize that science is a body of knowledge comprised of facts which were initially deemed to be ludicrous; especially by the status quo. Even though, Stenger’s and Churchland’s opinions were accurate with regard Microtubules and the Quantum Mind debate at the time, neither of them were able to substantiate their opinions scientifically and authoritatively, and they had to wait for Max Tegmark to refute the notion of Microtubules years later.

Without the vitriol, Tegmark simply explained the problem, showed us the math and how such notions seem to be a violation of quantum decoherence; at least for the time being. While Tegmark was seemingly right in refuting the notion of a quantum mind with regard to microtubules, it’s important to acknowledge that he only refuted one hypothesis in the time that it was made, which by no means closes the door on this discussion of a quantum mind all together. Unfortunately and regardless of their background on quantum mechanics, this hasn’t stopped most people from leaving this inquiry with such impressions.

On a side note though and while I agree with Max Tegmark’s reasoning, I think that his findings pale in comparison to the example that he set during this debate by simply showing us that people do not have to resort to rhetoric and ad hominem when they know what they’re talking about. People who resort to such tactics only tend to do so because know more about ‘Pixie Dust’ and ‘Unicorns’ than the topic at hand. However, while I’m afraid such labels may have had undue consequences and this topic is undeservedly taboo in some conversations, I do not think that they realized they would make such topics much more enticing to a millennial, like me. Unicorns? Dragons? Pixie Dust? What’s next? Falkor? Where do I sign up?! Seriously.

In summary, whether the scientists are right or wrong, those speculating about a quantum mind are not wrong for inquiring and going where the facts take them. While this topic seems to be taboo for many, quantum computers were a fantasy 20 years ago and without knowing much about them, likening the brain to a quantum computer can be quite difficult and I cannot blame some for viewing it as impossible as Unicorns and Dragons as a result. Only decades ago, plenty of brilliant people also said that quantum computing was impossible, but where are they now? We have actual quantum computers working in production that are running circles around classical systems while they are still in their infancy; Why can’t we infer similar about the notion of a quantum mind?

Technology moves fast and what was true about computers 20+ years ago may not be the case today, especially with regard to their perceived limitations. In spite of a similar stigma surrounding a quantum mind, progress has also been made on the discussion in the past few years, which may overturn some of these decade old objections with the introduction of Posner Molecules to the discussion. Plenty of scientists have speculated about the possibility of a quantum mind and this is anything but irrational when you consider the steep compute requirements in order to mimic a fraction of what we are capable of. When considered in conjunction with the fact that most computer scientists agree that it’s going to take a quantum computer to match us, it’s incredibly compelling and anything but a pipe dream.

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