Counting the Multitude of Processes Your Brain is Currently Handling
The human brain, often celebrated as a cutting-edge parallel processing system, handles a plethora of tasks concurrently - memory, learning, and bodily functions, to name a few. However, the question of its true multitasking capacity has puzzled scientists for quite some time.
Recently, a study by neuroscientist Harris Georgiou from the National Kapodistrian University of Athens claims the brain processes approximately 50 independent tasks in parallel, even during complex activities. At first glance, this figure may seem modest given the brain's vast potential, boasting a whopping 100 billion neurons, each capable of forming up to 10,000 connections.
So why does our multitasking ability seem so limited if we have such immense neural power?
To shed light on this matter, Georgiou turned to functional magnetic resonance imaging (fMRI). This technology maps brain activity by tracking oxygen levels in blood flow, pinpointing active regions, and dividing the brain into three-dimensional pixels called voxels. Each voxel, around five cubic millimeters in size, served as a unit of analysis for the study.
Participants were asked to perform two tasks: complete a complex visuo-motor task (identifying a red or green box on a screen and responding by raising a specific finger) and a recognition task (spotting repeated images of objects like faces, houses, and chairs).
Remarkably, as tasks became more complex, more processes were engaged. During the visuo-motor task, up to 50 independent processes were identified, while the recognition task, a simpler task, required fewer.
This finding challenges the long-standing assumption that parallel processing occurs at the level of individual neurons. Instead, Georgiou's research suggests that neurons cooperate in highly structured groups, forming distinct processing units, much like the CPU cores of a computer.
The question lingers, though: Are we running on 50 processing cores, and that's it? Or is the human brain's computing power far beyond our current understanding?
A Cautious Look at the Capacity Limit
It's essential to approach this research with a critical eye. Characterizing the brain as having 50 processing units raises several questions. For instance, how can we be certain that this isn't merely an estimate, considering the complexity and fluidity of brain activity?
Moreover, the brain doesn't operate in isolation. It interacts with other organs and systems, transforming the debate from pure computation to a multidimensional interplay of biological processes.
Despite the controversy, the research shifts the conversation surrounding the brain's computational capacity and sheds light on an intriguing possibility: the brain may not be the supercomputer we once thought it was.
shifting the conversation surrounding the brain's computational capacity and shedding light on an intriguing possibility: the brain may not be the supercomputer we once thought it was.
If true, this realization could impact the AI and computing industries. While AI researchers aim to build neuromorphic processors that mimic brain function, scalability might not be the key to achieving human-like cognition. Instead, future AI models could focus on strategic, hierarchical processing that emulates the brain's computational limitations.
Georgiou himself speculates that an artificial equivalent of a brain-like cognitive structure might not require a massively parallel architecture. Instead, a well-designed set of limited processes running in parallel on a smaller scale could mimic the elegance and efficiency of human cognition.
Such findings could revolutionize AI efficiency, making future models more practical and energy-efficient, as they would require significantly less energy and computing power than today's deep learning systems.
The Human Brain Remains an Enigma
The human brain's complexity and adaptability still baffle scientists, even amid rapid technological advancements. Even though computers surpass us in sheer speed and scale, they are yet to replicate the adaptive, power-efficient intelligence that has nurtured human progress for millennia.
For budding AI engineers and neuroscientists alike, Georgiou's research is a call to further explore the intricacies of the human brain and the possibilities of artificial intelligence. The future of AI may lie not in brute-force computing, but in understanding and mirroring the elegant constraints of human cognition.
And as we continue to unravel the mysteries of the human brain, evolution remains the reigning champion of intelligent design.
Sources:
- MIT Technology Review
- io9
The study by neuroscientist Harris Georgiou suggests that the human brain's computing power might not be as vast as previously thought, challenging the idea of the brain as a supercomputer. This finding could have significant implications for the AI and computing industries, potentially leading to more practical and energy-efficient AI models that focus on hierarchical, strategic processing.
On the other hand, the human brain's complexity and adaptability still puzzle scientists, underscoring the need for further exploration of its intricacies and the possibilities of artificial intelligence. As we continue to unravel the mysteries of the human brain, the future of AI may lie in understanding and mirroring the elegant constraints of human cognition rather than relying on brute-force computing.
