Artificial Intelligence

There are two big goals, mind uploading (i.e. creating a backup) and to create human-level (speed) artificial intelligence. If the only way to do so is by reverse engineering the human brain, first of all, or at least we will have to develop the sufficient “hardware”, information processing capabilities to build a human equivalent computational substrate. The big questions here are about the nature of information processing and the neuronal information capacity of an average human brain.

Consequently two subquestions come up, of what importance are astrocytes and microtubule and are they involved in information processing, among other things?

Stuart Hameroff

The operations of microtubules are remarkably complex and their role pervasive in cellular operations; these facts led to the speculation that computation sufficient for consciousness might somehow be occurring there. These ideas are discussed in Hameroff’s first book Ultimate Computing (1987). The main substance of this book dealt with the scope for information processing in biological tissue and especially in microtubules and other parts of the cytoskeleton. Hameroff argued that the cytoskeleton components could be the basic units of processing rather than the neurons. The book was primarily concerned with information processing, with consciousness secondary at this stage.

Link: en.wikipedia.org/wiki/Stuart_Hameroff#Theories

Roger Penrose

Penrose presents the argument that human consciousness is non-algorithmic, and thus is not capable of being modeled by a conventional Turing machine-type of digital computer. Penrose hypothesizes that quantum mechanics plays an essential role in the understanding of human consciousness. The collapse of the quantum wavefunction is seen as playing an important role in brain function.

On the basis of Godel’s incompleteness theorems, he argued that the brain could perform functions that no computer or system of algorithms could. From this it could follow that consciousness itself might be fundamentally non-algorithmic, and incapable of being modelled as a classical Turing machine type of computer.

Penrose made Gödel’s theorem the basis of what quickly became an intensely controversial claim. He argued that the theorem showed that the brain had the ability to go beyond what could be achieved by axioms or formal systems. This would mean that the mind had some additional function that was not based on algorithms (systems or rules of calculation). A computer is driven solely by algorithms. Penrose asserted that the brain could perform functions that no computer could perform. He called this type of functioning non-computable.

Link: en.wikipedia.org/wiki/The_Emperor%27s_New_Mind / en.wikipedia.org/wiki/Orch-OR

Microtubule

Through the 1980s, colleagues and I developed models of microtubule information processing in which states of tubulin subunits were bits interacting with lattice neighbor tubulins. With about 10^7 (10 to the seventh) tubulins per neuron switching at 10^-9 seconds, we calculated a potential for 10^16 operations per second in each neuron. This was, and remains unpopular in AI/Singularity circles because it potentially pushes the goalpost for brain capacity significantly. Recent evidence has shown collective microtubule excitations at 10^-7 seconds (rather than the 10^-9 seconds we assumed), indicating a neuronal information capacity of ‘only’ 10^14 operations per second.

Link: lifeboat.com/blog/?p=587

Astrocytes

Meet the forgotten 90 percent of your brain: glial cells, which outnumber your neurons ten to one. And no one really knows what they do.

If the glial cells called astrocytes really do process information, that would be a major addition to the brain’s computing power.

For some brain scientists, these discoveries are puzzle pieces that are slowly fitting together into an exciting new picture of the brain. Piece one: Astrocytes can sense incoming signals. Piece two: They can respond with calcium waves. Piece three: They can produce outputs—neurotransmitters and perhaps even calcium waves that spread to other astrocytes. In other words, they have at least some of the requirements for processing information the way neurons do. Alfonso Araque, a neuroscientist at the Cajal Institute in Spain, and his colleagues make a case for a fourth piece. They find that two different stimulus signals can produce two different patterns of calcium waves (that is, two different responses) in an astrocyte. When they gave astrocytes both signals at once, the waves they produced in the cells was not just the sum of the two patterns. Instead, the astrocytes produced an entirely new pattern in response. That’s what neurons—and computers, for that matter—do.

If astrocytes really do process information, that would be a major addition to the brain’s computing power. After all, there are many more astrocytes in the brain than there are neurons. Perhaps, some scientists have speculated, astrocytes carry out their own computing. Instead of the digital code of voltage spikes that neurons use, astrocytes may act more like an analog network, encoding information in slowly rising and falling waves of calcium. In his new book, The Root of Thought, neuroscientist Andrew Koob suggests that conversations among astrocytes may be responsible for “our creative and imaginative existence as human beings.”

Link: mindhacks.com/blog/

More

The Blue Brain Project is the first comprehensive attempt to reverse-engineer the mammalian brain, in order to understand brain function and dysfunction through detailed simulations: bluebrain.epfl.ch

The point is that nobody knows how long it will take, since we don’t even know what we don’t know: scienceblogs.com/cortex/the_blue_brain.php

Orch OR (Orchestrated Objective Reduction) is a theory of consciousness, which is the joint work of theoretical physicist Sir Roger Penrose and anesthesiologist Stuart Hameroff. Mainstream theories assume that consciousness emerges from the brain, and focus particularly on complex computation at connections known as synapses that allow communication between brain cells (neurons). Orch OR combines approaches to the problem of consciousness from the radically different angles of mathematics, physics and anesthesia: en.wikipedia.org/wiki/Orch-OR

Minds, Machines, and Mathematics consc.net/papers/penrose.html

Even More

10 Important Differences Between Brains and Computers

Although the brain-computer metaphor has served cognitive psychology well, research in cognitive neuroscience has revealed many important differences between brains and computers. Appreciating these differences may be crucial to understanding the mechanisms of neural information processing, and ultimately for the creation of artificial intelligence. Below, I review the most important of these differences (and the consequences to cognitive psychology of failing to recognize them): similar ground is covered in this excellent (though lengthy) lecture.

Difference # 10: Brains have bodies

This is not as trivial as it might seem: it turns out that the brain takes surprising advantage of the fact that it has a body at its disposal. For example, despite your intuitive feeling that you could close your eyes and know the locations of objects around you, a series of experiments in the field of change blindness has shown that our visual memories are actually quite sparse. In this case, the brain is “offloading” its memory requirements to the environment in which it exists: why bother remembering the location of objects when a quick glance will suffice? A surprising set of experiments by Jeremy Wolfe has shown that even after being asked hundreds of times which simple geometrical shapes are displayed on a computer screen, human subjects continue to answer those questions by gaze rather than rote memory. A wide variety of evidence from other domains suggests that we are only beginning to understand the importance of embodiment in information processing.

Link: scienceblogs.com/developingintelligence/