Neuromorphic chips represent the future because they mimic the brain's neural architecture, leading to significantly higher energy efficiency and parallel processing capabilities. These chips excel in pattern recognition and adaptive learning, making them ideal for complex AI tasks. Their potential to drastically reduce power consumption while enhancing computational performance makes them a pivotal advancement in hardware technology.
Why your brain is 3 milion more times efficient than GPT-4
161–170 of 213 posts
Re: Why your brain is 3 milion more times efficient than GPT-4
#162Earlier quoted context omitted.
No, only a brain can "think" and be original. A computer is limited to what we input to it. An "AI" simply recapitulates what it was trained on.
that's incredible! how did you put the confetti back in the canon?
I wonder which american guy went to italy, found out that there are almond candies called confetti and thought: "I'll do the same in my country, but made out of paper instead!"
Re: Why your brain is 3 milion more times efficient than GPT-4
#163Earlier quoted context omitted.
I’m not saying we don’t have limitations, we clearly do. There are limits to our intellectual capacity and creativity. ChatGPT can exceed humans in its knowledge store. It is excellent at doing research. But it’s not thinking it is merely selecting the most likely nest words based on some algorithm.
I wouldn't even give as much appreciation to chatgpt as you do. But I don't see it doing anything different than human brains do. It's just still not very good at it. If it were up to me I'd try to give it another representation than just words. I think those models should be trained to represent text as relationship graphs of objects. There's not much natural data lole that, but it should be fairly rasy to create va…
You might find Drexler's "Quasilinguistic Neural Representations" stimulating.
Re: Why your brain is 3 milion more times efficient than GPT-4
#164The comparison doesn't really hold. He is comparing energy spend during inference in humans with energy spend during training in LLM's. Humans spend their lifetimes training their brain so one would have to sum up the total training time if you are going to compare it to the training time of LLM's. At age 30 the total energy use of the brain sums up to about 5000 Wh, which is 1440 times more efficient. But at age 30…
If we’re going to exclude the cortical areas associated with vision, you also need to exclude areas involved in motor control and planning. Those also account for a huge percent of the total brain volume.
We probably need to exclude the cerebellum as well (which is 50% of the neurons in the brain) as it’s used for error correction in movement.
Realistically you probably just need a few parts of the lambic system. Hippocampus, amygdala, and a few of the deep brain dopamine centers.
Re: Why your brain is 3 milion more times efficient than GPT-4
#165There is an immensely strong dogma that, to my best knowledge, is not founded in any science or philosophy: First we must lay down certain axioms (smart word for the common sense/ground rules we all agree upon and accept as true). One of such would be the fact that currently computers do not really understand words. ... The author is at least honest about his assumptions. Which I can appreciate. Most other people jus…
Amusingly, the author does not appear to fully understand the meaning of "axiom". While practice, axioms are often statements that we all agree on and accept as true, that isn't necessarily true and isn't the core of it's meaning. Axioms are something we postulate as true, without providing an argument for its truth, for the purposes of making an argument. In this case, the assertion isn't really used as part of a ar…
> Axioms are something we postulate as true, without providing an argument for its truth, for the purposes of making an argument.
Uhm… no?
They are literally things that can't be proven but allow us to prove a lot of other things.
Re: Why your brain is 3 milion more times efficient than GPT-4
#166Earlier quoted context omitted.
Amusingly, the author does not appear to fully understand the meaning of "axiom". While practice, axioms are often statements that we all agree on and accept as true, that isn't necessarily true and isn't the core of it's meaning. Axioms are something we postulate as true, without providing an argument for its truth, for the purposes of making an argument. In this case, the assertion isn't really used as part of a ar…
> Axioms are something we postulate as true, without providing an argument for its truth, for the purposes of making an argument. Uhm… no? They are literally things that can't be proven but allow us to prove a lot of other things.
It seems like you fully agree with the parent.
I also agree, that the author probably not meant to establish an axiom: The axiom being established, while not having any support right now, does seem like something we can reduce in the future. The author also uses the word "currently" in their axiom, which contradicts axioms (or is temporal axioms a thing?).
I think the author merely meant to establish the scene for the article. Something I truly appreciate.
Re: Why your brain is 3 milion more times efficient than GPT-4
#167They are not comparable. There's a prevalent metaphor which imagines the brain as a digital computer. However, this is a metaphor and not actual facts. While we have some good ideas on how the brain works on higher levels (recommended reading Incognito: The Secret Lives of the Brain by David Eagleman) we do not really have any ideas on the lower levels. As the essay I link below mentions, for example, when attending a concert, our brain changes so that later it can remember it but two brains attending the same concert will not change the same way. This make modelling the brain really damn tricky.
This complete lack of understanding is also why it's completely laughable to think we can do AGI any time soon. Or perhaps ever? The reason for the AI winter cycle is the framing of it, this insane chase of AGI when it's not even defined properly. Instead, we should set out tasks to solve -- we didn't make a better horse when we made cars and locomotives. No one complains these do not provide us with milk to ferment into kumis. The goal was to move faster, not a better horse...
https://aeon.co/essays/your-brain-does-not-process-informati...
Re: Why your brain is 3 milion more times efficient than GPT-4
#168The comparison doesn't really hold. He is comparing energy spend during inference in humans with energy spend during training in LLM's. Humans spend their lifetimes training their brain so one would have to sum up the total training time if you are going to compare it to the training time of LLM's. At age 30 the total energy use of the brain sums up to about 5000 Wh, which is 1440 times more efficient. But at age 30…
If we’re going to exclude the cortical areas associated with vision, you also need to exclude areas involved in motor control and planning. Those also account for a huge percent of the total brain volume. We probably need to exclude the cerebellum as well (which is 50% of the neurons in the brain) as it’s used for error correction in movement. Realistically you probably just need a few parts of the lambic system. Hip…
A lot of our cognition is mapped to areas that are used for something else, so excluding areas simply because they are used for something else is not valid. They can still be used for higher-level cognition. For example, we use the same area of the brain to process the taste of disgusting food as we do for moral disgust.
Re: Why your brain is 3 milion more times efficient than GPT-4
#169Earlier quoted context omitted.
That explanation never made any sense to me. Plenty of much easier ways for the machines to generate vastly more energy with far less hassle than using humans as “batteries”. There must be more to it than that!
The original idea wasn't batteries, so they probably started out with humans as cpus but then went with batteries to make it easier to understand for people.
In dollhouse they put people through nightmare scenarios repeatedly, to make their brain evaluate scenarios.
Re: Why your brain is 3 milion more times efficient than GPT-4
#170[deleted]