Amount of computing power needed for whole-brain emulation?

In summary, the amount of computing power required for real-time emulation of the entire human brain is currently unknown and far beyond our current capabilities. There have been some attempts at simulating parts of the brain on supercomputers, but a full-brain simulation is still a distant possibility.
  • #1
ElliotSmith
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What is the approximate amount of computing power that is required for real-time emulation of the entire human brain?

Such computing power would be necessary for theorized AI systems in the future.

From my understanding, no computer that exists in the world today can do this, yet...
 
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  • #3
ElliotSmith said:
What is the approximate amount of computing power that is required for real-time emulation of the entire human brain?
I believe that our current understanding of the complexities of the human brain is FAR from adequate to even think about being able to know what a full-brain simulation would take.
 
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Related to Amount of computing power needed for whole-brain emulation?

1. How much computing power is needed for whole-brain emulation?

The amount of computing power needed for whole-brain emulation is a highly debated topic and can vary greatly depending on the approach used. Some experts suggest that it could require as much as 10^18 FLOPS (floating-point operations per second), while others estimate that it could be accomplished with 10^14 FLOPS. Ultimately, the exact amount of computing power needed will depend on various factors such as the level of detail and accuracy desired, the complexity of the brain's structure, and the efficiency of the emulation process.

2. Is it possible for current technology to achieve the necessary computing power for whole-brain emulation?

At the moment, we do not have the technology to achieve the necessary computing power for whole-brain emulation. However, with the rapid advancements in computing technology, it is possible that we may reach the required level of computing power in the future. Some experts believe that it could be achieved within the next few decades.

3. How does the amount of computing power needed for whole-brain emulation compare to the human brain's computing power?

The human brain is estimated to have a computational capacity of around 10^16 FLOPS, which is significantly higher than the current computing power available. This means that we would need a significant increase in computing power to achieve whole-brain emulation. However, it is important to note that the brain and computers process information differently, so a direct comparison may not be accurate.

4. Can we use parallel processing to achieve the necessary computing power for whole-brain emulation?

Parallel processing, which involves breaking down a complex task into smaller parts and processing them simultaneously, is a promising approach for achieving the necessary computing power for whole-brain emulation. However, it is still unclear how effective this method would be and whether it would be enough on its own to achieve whole-brain emulation.

5. Are there ethical concerns surrounding the amount of computing power needed for whole-brain emulation?

There are several ethical concerns surrounding whole-brain emulation, including the amount of computing power needed. Some argue that the resources and energy required for such a massive computing project could be better used for other purposes, while others worry about the implications of creating artificial minds that could potentially surpass human intelligence. These ethical concerns need to be carefully considered and addressed before pursuing whole-brain emulation.

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