Getting Billions, They Boasted They Would Get by 2025 a "Comprehensive Mechanistic Understanding of Mental Function"

 In recent years the two largest brain research projects have been a big US project launched in 2013 called the BRAIN Initiative, and a big European Union project launched in 2013 called the Human Brain Project. The BRAIN Initiative has received billions in funding, but has failed to fulfill the boasts it made about what it would do by the year 2025. 

More than seven years ago, the leaders of the BRAIN Initiative produced a document filled with hubris, one boasting about the grand and glorious things the project would achieve by the year 2025. The document was called Brain 2025: A Scientific Vision, and was offered at one of the project's two main web sites. You can read the document at the link here, and after going to that page you need to press on a + button (next to "Expand accordion content") to get the whole text. 

The “scientific vision” laid out in the document is largely an ideological vision, based on the unbelievable idea that the human mind is merely the product of the brain. The dubious ideology of the authors is made clear in the very first sentence of the document, in which the authors state, “The human brain is the source of our thoughts, emotions, perceptions, actions, and memories; it confers on us the abilities that make us human, while simultaneously making each of us unique.” It has certainly not been proven that any brain has ever generated a thought or stored a memory.

In fact, later in the document the authors confess, “We do not yet have a systematic theory of how information is encoded in the chemical and electrical activity of neurons, how it is fused to determine behavior on short time scales, and how it is used to adapt, refine, and learn behaviors on longer time scales.” This is certainly true. No one has anything like a systematic theory of how a brain could store memories as neural states, nor has anyone come up with anything like a systematic theory of how a brain could generate a thought. So why, then, did the document start out by stating that “the human brain is the source of our thoughts, emotions, perceptions, actions, and memories”? No one has any business making such a claim unless he first has “ a systematic theory of how information is encoded in the chemical and electrical activity of neurons.” But the document admits that no such theory exists.

But despite this one candid confession, the document was a writing of enormous hubris. The authors boasted that by the year 2025, the BRAIN Initiative would figure out how minds work. The document stated, "The most important outcome of the BRAIN Initiative will be a comprehensive, mechanistic understanding of mental function that emerges from synergistic application of the new technologies and conceptual structures developed under the BRAIN Initiative.” Notice how enormous is the predictive conceit of that statement, which sounds like a delusion of grandeur. The authors did not merely claim that they would "shed light" on how minds work, or that they would "get clues" as to how minds work. They boasted that their project would produce a  "comprehensive, mechanistic understanding of mental function." Making a boast as big as the sky. the authors predicted that their project would tell us how brains produce minds and their phenomena. 

What has been the result of the BRAIN Initiative? No great breakthroughs have occurred. The results (to use English slang) are "peanuts" or "chickenfeed." 

On the page here , we get a summary of the BRAIN Initiative's achievements in 2024.  None of it sounds like an achievement relevant to whether brains make minds, except for the claim that there was developed a " brain-computer interface that can convert brain waves into speech with minimal training."  We have a link to the page here, which makes the same claim. The claim is unfounded. The pages are referring to the study "Representation of internal speech by single neurons in human supramarginal gyrus." My post here explains why the study is not actually a demonstration of a "brain-computer interface that can convert brain waves into speech." 

What's going on in the study is a reading of brain waves during very rapid switching between "speak it" instructions and "think it" instructions, with no care being taken to prevent subjects from speaking during the very short "think it" periods lasting only a few seconds.  We should assume that during many of the claimed "internal speech" intervals there were actually "audible speech" events, because of a failure of subjects to follow a very hard-to-perform protocol, one seemingly designed to produce such "failure to follow instructions" events.  Under such an assumption, the results can easily be explained, without assuming that there was occurring "converting of brain waves into speech." The second of the BRAIN Initiative pages given above boasts that "For one of the two participants, the BCI [brain-computer interface] could decode several words of their inner dialogue with 79% accuracy during an online task." These are meager tiny-sample-size results easily explained by chance or by assuming a difference in muscle movements that produce different types of brain waves, with supposed "inner dialogue" events often being verbal speaking events, as users failed to follow perfectly the hard-to-follow instructions involving rapid switching between speech and pure thinking. 

On the same BRAIN Initiative page we have another similar boast of a "brain-computer interface."  It is a reference to a paper which makes no claim  of picking up an "inner dialogue" involving no muscle movements. Instead some patient with a speech problem had electrodes implanted in his brain, and some system is picking up his attempts to speak different words. Such an attempt can produce limited success mainly because different types of speech efforts (involving slightly different muscle movements) may produce different types of EEG waves. Muscle movements or attempted muscle movements show up very noticeably in EEG brain wave readings; and distinctive types of muscle movements corresponding to particular speech sounds (phonemes) may produce distinctive blips in EEG readings. 

Studies like this (hailed as examples of "mind reading" from brains) typically involve a variety of shady tricks, such as getting inputs from more than just brain wave inputs, such as inputs from eye tracking devices, which make it easy to determine what word or picture on a screen someone is focusing on. 

The reality is that the BRAIN Initiative has failed to produce any results backing up in any weighty way claims that brains make minds and that brains store memories. You cannot actually detect what someone is thinking from analyzing mere brain waves. Studies claiming to do such a thing typically involve various types of dubious methodology and objectionable techniques.  A well-designed, fairly conducted and well-analyzed study will always show a failure to detect from brain waves alone what someone is thinking.

These were additional unfulfilled boasts of the document entitled Brain 2025: A Scientific Vision:

• "We expect to discover new forms of neural coding as exciting as the discovery of place cells, and new forms of neural dynamics that underlie neural computations." So-called "place cells" were never actually discovered. The claim that they were discovered is one of the many groundless triumphal legends of neuroscientists, who have a high tendency to repeat "old wives' tales" of the belief community they belong to. Read my post here for a debunking of claims that "place cells" were ever observed  All that happened was that scientists observed some cells, and claimed that some cells were more active when some rats were in certain places. The studies were never examples of robust science, because they were guilty of various methodological sins such as using way-too-small study group sizes. No actual new form of neural coding was ever discovered by the BRAIN Initiative or any other scientific project or scientific study. And no one ever discovered "neural dynamics that underlie neural computations."
• "Through deepened knowledge of how our brains actually work, we will understand ourselves differently, treat disease more incisively, educate our children more effectively, practice law and governance with greater insight, and develop more understanding of others whose brains have been molded in different circumstances." No such bonanza of benefits resulted from the BRAIN Initiative. Neuroscience has done nothing to improve the education of children, and done nothing to improve the practice of law or government.
• "We must understand how circuits give rise to dynamic and integrated patterns of brain activity, and how these activity patterns contribute to normal and abnormal brain functions. Our expectation is that this approach will answer the deepest, most difficult questions about how the brain works, providing the basis for optimizing the health of the normal brain and inspiring novel therapies for brain disorders." The BRAIN Initiative wasted billions floundering around in this dead end, but did not answer any of the "most difficult questions about how the brain works," or any of the "most difficult questions about how the mind works."  Scientists still have no credible tale to tell of how a brain could think, imagine, instantly learn or instantly recall. 
• " We expect The BRAIN Initiative® to develop new biological reagents, possibly including genetically-modified strains of rodents, fish, invertebrates, and non-human primates; recombinant viruses targeted to different brain cell types in different species; genetically-encoded indicators of different forms of neural activity; and genetic tools for modulating neuronal activity."  Here the scientists (sounding like eugenics enthusiasts) fall into Frankenstein folly by boasting about how they will monkey with the genes of various organisms, including rodents and primates. The hubris involved here should provoke the gravest concerns.  And anyone familiar with the very substantive suspicions that the COVID-19 virus might have arose from a lab leak should shudder at the proposed gene fiddling. 

The Reason You Will Never Be Able to Upload Your Mind Is the Same Reason You Won't Ever Need To

A very accomplished technologist and inventor, Ray Kurzweil has become famous for his prediction that there will before long be a “Singularity” in which machines become super-intelligent (a prediction make in his 2005 book The Singularity Is Near). In his 1999 book The Age of Spiritual Machines,  Ray Kurzweil made some very specific predictions about specific years: the year 2009, the year 2019, the year 2029, and the year 2072. Let's look at how well his predictions for the year 2019 hold up to reality. 

Prediction #1: “The computational ability of a $4,000 computing device (in 1999 dollars) is approximately equal to the computational capability of the human brain (20 million billion calculations per second)."

Reality: A $4000 computing device in 1999 dollars is equivalent to about a  7700 dollar computing device today. There is no $7700 computing device that can compute even a hundredth as fast as 

20 million billion calculations per second. The fastest current processor for a machine under $8000 is the Intel Core i9-14900KS, with a clock speed of about 6 gigahertz, only about 6 billion operations per second. If you shell out about 8000 dollars for a high-end gaming computer, you can get a few teraflops of floating point calculations per second.  Even if we use that figure rather than the clock speed, we still have computing capability more than 1000 times smaller than the computing capability predicted by Kurzweil for such a device in 2019. 

Prediction #2: “Computers are now largely invisible and are embedded everywhere – in walls, tables, chairs, desks, clothing, jewelry, and bodies.” 

Reality: Nothing like this has happened, and while computers are smaller and thinner, they are not at all "largely invisible."

Prediction #3: “Three-dimensional virtual reality displays, embedded in glasses and contact lenses, as well as auditory 'lenses,' are used routinely as primary interfaces for communication with other persons, computers, the Web, and virtual reality.” 

Reality: Such things are not at all used “routinely,” and I am aware of no cases in which they are ever used. There is very little communication through virtual reality displays, and when it is done it involves bulky apparatus like the Occulus Rift device, which resembles a scuba mask.

Prediction #4: “People routinely use three-dimensional displays built into their glasses,  or contact lenses. These 'direct eye' displays create highly realistic, virtual visual environments overlaying the "real" environment.

Reality: Very few people use any such technology, even in the year 2025. 

Prediction #5: “High-resolution, three dimensional visual and auditory virtual reality and realistic all-encompassing tactile environments enable people to do virtually anything with anybody, regardless of physical proximity." 

Reality: This sounds like a prediction of some reality similar to the Holodeck first depicted in the TV series Star Trek: The New Generation, or a prediction that realistic virtual sex will be available by 2019. Alas, we have no such things.

Prediction #6: “Paper books or documents are rarely used and most learning is conducted through intelligent, simulated software-based teachers.”

Reality: Paper books and documents are used much less commonly than in 1999, but it is not at all true that most learning  occurs through “intelligent, simulated software-based teachers.” 

Prediction #7: “The vast majority of transactions include a simulated person.”

Reality: A large percentage of transactions are electronic, but very few of them involve a simulated person.

Prediction #8: “Automated driving systems are now installed on most roads.”

Reality: Although there are a few self-driving cars on the road, 99% of traffic is old-fashioned traffic with human drivers.

Prediction #9: "Most flying weapons are small -- some as small as insects -- with microscopic flying weapons being researched."

Reality: The public has not yet even heard of tiny flying weapons.

Prediction #10: "The expected lifespan...has now substantially increased again, to over one hundred." 

Reality: A November 2023 article is entitled "Life expectancy for men in U.S. falls to 73 years — six years less than for women, per study."

Prediction #11: "Keyboards are rare."

Reality: No, keyboards were not rare either in 2019 or today. 

Prediction #12: "The majority of 'computes' of computers are now devoted to massively parallel neural nets and genetic algorithms."

Reality: Not true. So-called genetic algorithms are pretty useless as a computing methodology.  Software is not significantly developed through any Darwinian means, because random mutations with survival of the luckier results is not a workable method for creating very complex systems or very complex functional innovations, contrary to the claims of Darwinist biologists. Darwinism has flunked the software test.  

So Kurzweil's predictions for 2019 were very far off the mark. But Kurzweil is still playing the role of Grand Techno-Prophet. In a Freethink.com article last year, Kurzweil predicted that in the 2030's nanobots (microscopic robots injected into the body) will produce a great increase in lifespan. In the same article he predicted that the uploading of human minds into computers will occur by the 2040's.  Are there any reasons to think that his predictions for the 2030's and 2040's are unlikely to be correct? There certainly are. 

One reason is that Kurzweil never did much to prove his claim that there is a Law of Accelerating Returns causing the time interval between major events to grow shorter and shorter. On page 27 of The Age of Spiritual Machines he tries to derive this law from evolution, claiming that natural evolution follows such a law.  But we don't see such a law being observed in the history of life.  Not counting the appearance of humans, by far the biggest leap in biological order occurred not fairly recently, but about 540 million years ago, when almost all of the existing animal phyla appeared rather suddenly during the Cambrian Explosion.  No animal phylum has appeared in the past 480 million years. So we do not at all see such a Law of Accelerating Returns in the history of life.  There has, in fact, been no major leap in biological innovation during the past 30,000 years. 

Kurzweil's logic on page 27 contains an obvious flaw. He states this:

"The advance of technology is inherently an evolutionary process.  Indeed, it is a continuation of the same evolutionary process that gave rise to the technology-creating species. Therefore, in accordance with the Law of Accelerating Returns, the time interval between salient advances grows exponentially shorter as time passes." 

This is completely fallacious reasoning, both because the natural history of life has not actually followed a Law of Accelerating Returns, and also because the advance of technology is not a process like the evolutionary process postulated by Darwin.  The evolutionary process imagined by Darwin is blind, unguided, and natural, but the growth of technology is purposeful, guided and artificial.

On the same page, Kurzweil cites Moore's Law as justification for the Law of Accelerating Returns.  For a long time, this rule-of-thumb held true, that the speed of a transistor doubled every two years. But in 2015 Moore himself said, "I see Moore's law dying here in the next decade or so."  In the Wikipedia.org article on Moore's Law, we read, "Some forecasters, including Gordon Moore,[122] predict that Moore's law will end by around 2025." It is now clear that fundamental limits of making things smaller will cause Moore's Law to stop being true before long. 

 Machines smarter than humans would require stratospheric leaps forward in computer software, but computer software has never grown at anything like an exponential pace or an accelerating pace.  Nothing like Moore's Law has ever existed in the world of software development.  Kurzweil has occasionally attempted to suggest that evolutionary algorithms will produce some great leap that will speed up the rate of software development. But a 2018 review of evolutionary algorithms concludes that they have been of little use, and states: "Our analysis of relevant literature shows that no one has succeeded at evolving non-trivial software from scratch, in other words the Darwinian algorithm works in theory, but does not work in practice, when applied in the domain of software production." 

Page 256 of the document here refers to problems with software which throw cold water on hopes that progress with computers will be exponential:

"Lanier discusses software 'brittleness,'  'legacy code,' 'lock-in,' and 'other perversions' that work counter to the logic of Kurzweil’s exponential vision. It turns out there is also an exponential growth curve in programming and IT support jobs, as more and more talent and hours are drawn into managing, debugging, translating

incompatible databases, and protecting our exponentially better, cheaper, and more connected computers. This exponential countertrend suggests that humanity will

become 'a planet of help desks' long before the Singularity."

We already have something like this with so-called artificial intelligence systems, which by now involve databases and code so complex that no one adequately understands them. We hear talk of AI "hallucinations" that sound unfixable because the AI systems are "black boxes" that humans cannot dive in and debug as they would some code written by humans. 

As for Kurzweil's predictions about nanobots producing a surge in lifespan during the 2030's, there are strong reasons for doubting it.   Futurists have long advanced the idea that tiny nanobots might be injected into people, to circulate through the human body to repair its cells. But there may be technical reasons why such things are technically unfeasible. Nobel Prize winner Richard Smalley argued that the molecular assemblers imagined by nanotechnology enthusiast Eric Drexler were not feasible, because of various scientific reasons such as what he called the “fat fingers” problem.

There is another strong reason for rejecting the idea that nanobots will be able to produce some great increase in human lifespan. The reason is the stratospheric complexity of human biology and the vast levels of organization in human bodies.  Transhumanists have generally tended to  fail to understand the stratospheric amount of organization and functional complexity in living things.  An objective and very thorough scholar of biological complexity will be very skeptical of any claim that devices that humans manufacture will be able to make humans live very much longer. There is so very much about the fundamentals of human life that biologists still don't understand.  The visual below illustrates the situation. The problems listed are problems a hundred miles over the heads of scientists. 

While scientists can list stages in cell reproduction, scientists are unable to even explain the marvel of cell reproduction, which for many cells is a feat as impressive as an automobile splitting up to become two separate working automobiles. Scientists cannot even explain how protein molecules are able to fold into the three-dimensional shapes needed for their functions, shapes not specified by DNA.  Without resorting to lies such as the lie that DNA is a body blueprint, no scientist can credibly explain how a speck-sized zygote (existing just after female impregnation) is able to progress over nine months to become the vast hierarchical  organization of the human body.  No scientist has  a decent physical explanation of how memories can form, or how they can persist for a lifetime. No scientist has a decent explanation of how humans are able to instantly recall lots of detailed relevant information as soon as they hear a name mentioned, or see of photo of someone, a feat that should be impossible using a brain that is completely lacking in sorting, indexes and addresses (the type of things that make instant recall possible).  

With human knowledge being so fragmentary, and so many basic problems of explaining humans and their minds being so far over the heads of scientists, how improbable is it that humans will be able to overhaul their biology on the microscopic level by using microscopic robots called nanobots, or any other technology we can envision in the next fifty years?

The biggest reason for doubting Kurzweil's predictions beyond 2019 is that they are based on assumptions about the brain and mind that are incorrect. Kurzweil is an uncritical consumer of neuroscientist dogmas about the brain and mind. He assumes that the mind must be a product of the brain, and that memories must be stored in the brain, because that is what neuroscientists typically claim. If he had made an adequate study of the topic, he would have found that the low-level facts collected by neuroscientists do not support the high-level claims that neuroscientists make about the brain, and frequently contradict such claims. To give a few examples:

• There is no place in the brain suitable for storing memories that last for decades, and things like synapses and dendritic spines (alleged to be involved in memory storage) are unstable, "shifting sands" kind of things which do not last for years, and which consist of proteins that only last for weeks.
• The synapses that transmit signals in the brain are very noisy and unreliable,  in contrast to humans who can recall very large amounts of memorized information without error.
• Signal transmission in the brain must mainly be a snail's pace affair, because of very serious slowing factors such as synaptic delays and synaptic fatigue (wrongly ignored by those who write about the speed of brain signals), meaning brains are too slow to explain instantaneous human memory recall.
• The brain seems to have no mechanism for reading memories.
• The brain seems to have no mechanism for writing memories, nothing like the read-write heads found in computers.
• The brain has nothing that might explain the instantaneous recall of long-ago-learned information that humans routinely display, and has nothing like the things that allow instant data retrieval in computers.
• Brain tissue has been studied at the most minute resolution, and it shows no sign of storing any encoded information (such as memory information) other than the genetic information that is in almost every cell of the body.
• There is no sign that the brain or the human genome has any of the vast genomic apparatus it would need to have to accomplish the gigantic task of converting learned conceptual knowledge and episodic memories into neural states or synapse states (the task would presumably require thousands  of specialized proteins, and there's no real sign that such memory-encoding proteins exist)
• No neuroscientist has ever given a detailed explanation of how such a gigantic translation task of memory encoding could be accomplished (one that included precise, detailed examples).
• Contrary to the claim that brains store memories and produce our thinking, case histories show that humans can lose half or more of their brains (due to disease or hemispherectomy operations), and suffer little damage to memory or intelligence (as discussed here). 

Had he made a study of paranormal phenomena, something he shows no signs of having studied, Kurzweil might have come to the same idea suggested by the neuroscience facts above: that the brain cannot be an explanation for the human mind and human memory, and that these things must be aspects of some reality that is not neural, probably a spiritual dimension of humanity.

Since he believes that our minds are merely the products of our brains, Kurzweil thinks that we will be able to make machines as intelligent as we are, and eventually far more intelligent than we are, by somehow leveraging some "mind from matter" principle used by the human brain. But no one has any credible account of what such a principle could be, and certainly Kurzweil does not (although he tried to create an impression of knowledge about this topic with his book How to Create a Mind).   We already know the details of the structure and physiology of the brain, and what is going on in the brain in terms of matter and energy movement.  Such details do nothing to clarify any "mind from matter" principle that might explain how a brain could generate a mind, or be leveraged to make super-intelligent machines. 

In general, transhumanists tend to be poor scholars of four very important topics:

(1) Transhumanists tend to be poor scholars of biological complexity and the vast amount of organization and fine-tuned functionality in human bodies. So they make naive claims such as that injected microscopic robots will soon be able to fix your cells and double your lifespan, failing to realize the unlikelihood of that, given the vast complexity of interdependent components in the human body and the vast complexity of human cells and the biochemistry of human bodies. 

(2) Transhumanists tend to be poor scholars of genetics and human DNA. A proper study of the topic will help you realize that genes do not explain either the origin of the human body or the characteristics of the human mind. DNA merely has low-level chemical information, not high-level anatomical information, and not any information that can explain mind or memory.  We have an example of very bad transhumanist misunderstanding of DNA on page 2 of Kurzweil's book "How to Create a Mind" where he incorrectly states, "A billion years later a complex molecule called DNA evolved, which could 

precisely encode lengthy strings of information and generate organisms described by these 'programs.' " DNA has no specification of how to make an organism or any of its organs or any of its cells. There are no programs in DNA, but merely lists of chemical ingredients, such as which amino acids make up a particular protein.  The idea that an organism is built by DNA is childish nonsense. DNA has no blueprint for constructing an organism, and even if it did, it would not explain how organisms get built, because blueprints don't build things. Things get built with the help of blueprints only when intelligent agents read blueprints to get ideas about how to build things. 

(3) Transhumanists tend to be poor scholars of human minds,  and the vast diversity of human experiences, normal and paranormal. A proper study of two hundred years of evidence for paranormal phenomena leads to the conclusion that humans are souls, not products of brains. 

(4) Transhumanists tend to be poor scholars of human brains and their physical shortfalls which rule out brains as a credible explanations for human minds.  Ask a transhumanist about things such as the average lifetime of brain proteins or the transmission reliability rate of chemical synapses, and you won't be likely to get the right answer.  

Last year Kurzweil made this very glaring misstatement:

"I’m really the only person that predicted the tremendous AI interest that we’re seeing today. In 1999 people thought that would take a century or more." 

Not true at all. Countless writers predicted that we would have machines as smart as people by the year 2000, and in 1999 futurists were typically predicting that this would happen by about this year (2025). Page 12 of the paper here gives a graph showing that 8 experts predicted that computers would have human level intelligence by about the year 2000, that 9 other experts predicted that computers would have human level intelligence by the year 2025, and that 12 other experts predicted that computers would have human level intelligence by the year 2030. In the same interview, Kurzweil makes the gigantically false claim that our understanding of biology is progressing exponentially. To the contrary, biologists are stuck from an explanatory standpoint, still light-years away from credibly explaining  how there occurs the most basic aspects of biology such as consciousness, cell reproduction, morphogenesis, human self-hood, human understanding,  instant human recall, the creation and formation of memories by humans, and the progression from a speck-sized zygote to a full human body. Biologists cannot credibly explain the origin of life or the origin of any type of protein molecule or any type of cell in the human body, such things being vastly too complex and vastly too organized to be credibly explained by Darwinian ideas. From an explanatory standpoint, neuroscientists are stuck in the mud, and getting nowhere, as they have been for decades. You might think otherwise from all the press releases about low-quality experimental studies guilty of defects such as way-too-small study group sizes. 

On page 4 of his 2013 book "How to Create a Mind" Kurzweil stated most incorrectly, "We are rapidly reverse-engineering the information processes that underlie biology including that of our brains." Nothing of the sort was being done then, and nothing of the sort is being done now. Biologists lack any understanding of how a human can think or learn or recall by any brain mechanism, and when they try to sound like they have some knowledge of such things, we usually get nothing but vacuous hand-waving. There are some very successful types of computer programs that have misnomer biological-sounding names such as "neural nets," but such programs do not actually have characteristics matching those of the brain or any part of the brain. 

The main reason you will not ever be able to upload your mind into a computer is that such an idea is based on the assumption that your brain creates your mind and that your brain stores your memories: an assumption that is not correct.  You are not your brain, but a soul. But you need not worry a bit about the impossibility of uploading minds into computers. The very reality that makes such a thing impossible is a reality that makes such a thing unnecessary. You do not need to upload your mind into a computer, because your mind is a soul reality that will not die when your brain and body dies.  One of the main types of evidence for this are out-of-body experiences, with quite a few features beyond any credible explanation of neuroscientists (as discussed here).