Submitted by vampiire t3_zb7umk in deeplearning
> ANNs have various differences from biological brains. Specifically, artificial neural networks tend to be static and symbolic, while the biological brain of most living organisms is dynamic (plastic) and analog.
ELI5 or ELI am a non-ML dev.
Thank you. This explains static vs dynamic. But what does symbolic vs analog mean in this context?
To be fair, there is research into ANNs that adapt their architectures over time or dynamically adapt the plasticity of certain weights while engaged in “lifelong learning”, and groups have built such networks, but these are the exceptions and almost always the architecture gets fixed and weights are just updated with some standard backprop that can lead to the so-called “catastrophic forgetting” when a dataset shifts it’s PDF if you don’t do anything more advanced than the “vanilla” NN setup.
Ask the question here. It gives good results, and can do follow ups if you ask it.
I got this answer plotting in your question:
>Artificial neural networks (ANNs) are computational models that are inspired by the structure and function of the biological brain. While they share some similarities with the brain, there are also some important differences between the two.
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>One of the key differences between ANNs and biological brains is that ANNs are typically static and symbolic, while the brain is dynamic and analog. This means that ANNs are typically designed to perform a specific set of tasks, and their structure and function remain the same throughout their use. In contrast, the brain is constantly changing and adapting to new information and experiences. It is able to learn and adapt to new situations, and it uses continuous, analog signals to process information.
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>Another key difference between ANNs and the brain is that ANNs are designed to process information in a highly parallel and distributed manner, while the brain uses a more hierarchical and sequential processing approach. In ANNs, many simple processing units (neurons) are connected together to form a network, and information is processed by the network as a whole. In the brain, on the other hand, information is processed by distinct brain regions, and there is a hierarchical organization of brain regions, with higher-level regions receiving input from lower-level regions.
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>Despite these differences, ANNs have been able to achieve impressive performance on a wide range of tasks, such as image and speech recognition, language translation, and even playing complex games like chess and Go. While ANNs may not be perfect models of the brain, they continue to be an important tool for researchers and developers who are working on developing intelligent systems.
Analog means it operates with some form of continuity. Your nervous system (which your brain, and thus, your neurons, is part of) is operates thru the passing of continuous electrical signals.
Symbolic just means that is serves as a representation. I.e. the "neuron" in an ANN is not a real neuron. It just symbolizes one.
Ah I see. I had always heard analog vs digital. Thought there was some semantic meaning I was missing. Thanks for the answers.
The electrical signals in our nervous system are analog, not digital.
Right. I misunderstood symbolic to mean a third form of signal passing, in addition to analog and digital.
Haha amazing. Like asking the brain to explain itself.
I’ll look into making an account. Is this like a wiki chat bot you can ask anything to?
When you hear a person play violin in a subway-analog. When you hear a violin played over your cell phone while on hold—digital. Biological neural systems allow for an infinite level of tuning due to their analog nature. ANNs have a limit defined by their processors.
The name "Chat bot" is missleading. It can really help you to program and other things. I use it a lot together with github co-pilot.
Here is an example from another guy using the 'chat bot': https://www.reddit.com/r/GPT3/comments/zalfyg/i_asked_chatgpt_to_make_me_unity_c_code_that/?sort=old
What??
Is this a meme or serious? How the fuck is that possible?
CrwdsrcEntrepreneur t1_iypseni wrote
Neural networks are basically groups of containers for series of mathematical operations, both within the container and across layers of containers. "Symbolic" is referring to the fact that early researchers decided to call these containers "neurons", to symbolize the way biological neurons in our brains share "information" with each other (i.e. a network of neurons). ANNs are static in the sense that once you define the architecture (# of layers, neurons per layer, layer-to-layer connections) this architecture does not change. Your brain, however, does transform itself as you age and learn new things, hence it is dynamic.