And can be completely destroyed in a few minutes of complete inactivity…. Such as stop breathing or have a heart attack…. Rebuilding that same brain, that experienced the unscheduled down time, can take another decade or so…. It would be nice to have a method, or understanding, of rebuilding all of those lost connections in the brain…. I’m open to ideas… 😃

The downtime is on the user end, the brain is still working though

@@isshollandwrong. the body never has downtime, it just has concurrent repair time

​@@AC-jk8wqpsychedelics

There is no downtime, its constantly at work.

At that point I thought someone had failed a Turing Test.

When your professor is checking to see if you're paying attention.

Attention paid.

i thought i was having a brain aneurysm

I checked twice to see if I missed a point, or if Jon missed a point! 😃

Hard, but surprisingly elastic! The average human brain makes an excellent emergency trampoline if pancake smooshed (sorry for the technical language)

It depends on preparation id imagine

Exactly what I was gonna say lol

I think you’re being difficult 😉

Its not that difficult anyway, My mother made one like 28 years ago

Faggin lolol

Oooh so that's where the name comes from. Always wondered that.

they still do

Is it me or did Lots of interesting stuff happened in 1986 🙃

i think it was 2x for the amount of memory lane width in bits. Fortunately we have DDR manufacturers increasing the bandwidth.

That would be Biden’s law

@@Mfields4517get outa here…you think Trump and MAGA are more aligned with a science and engineering based society? Freaking quacks all of em. I’ll take the lesser of two evils…the same people in the GOP are not the ones moving technology forward in society today or in the past

just another hurdle in the way, with time and funding I'm sure this too will be solved. like you said it's "brain-like", but never will be a brain, only a machine

Yet we can still build airplanes, rockets and computers. Yes takes a lot of work and redundancies to make these possible with all these errors humans can make, but if it works it works

@@rizizum Yes, we use digital computers to airplanes, rockets and other computers because they are great tools for what the human brain doesn't do well.

​@@ethans4783 and what the fuck is a brain if not a very complex meat machine?

Ruler was fine just the way he was. Did he need a brain chip. I believe consciousness is outside of all the hoopla. Two different highways

Got it. Just edited it out for this one.

2 months out? Wow, that's quite the lead time.

@IAmPattycakes found the OG stan😅

To call the brain space efficient is like calling the ocean big. It's efficient to an extent that's not replicable by modern technology. The packaging of biomolecules and living tissues are and will be, for the foreseeable future, wonders of physics that everyone can only look up to.

🙄

Very impressive recovery story Ingrid! I have had the good fortune of working with many people recovering from TBIs. Their recovery continues strongly for more than a decade… I hope this note finds you continuing on your journey! No two TBIs are the same, but…. Chances are… you have great memories still awaiting to be discovered. The harder you work at memory recall…. The more memories get re-connected! An impressive non-linearly rate of recovery… TBI 2011 😃

you come across as hypochondriac and presenting with some kind of personality disorder, perhaps narcissism, that I'm not qualified to speculate about, more so than someone that actually has brain damage.

Thats cool

Liquid (Blood) cooling baby

to make matters worse, those links need to be tuned like an analog circuit

in-chip capillary cooling!

That explains why the brain is so darn power efficient, because otherwise it would just be a glowing orb.

heat is not such a problem when you run with ~10kHz, but I agree that network design is very critical for such systems.

would you agree that there might be research to do on something like a universal language of logic first? Let me explain. Right now, we have machine "language" at the center, the "ones and zeroes" everyone should know about, with several layers designed to make sense to humans - assembly first, low-level programming languages second, and finally high-level ones and scripts. What we do here is take computer logic and make it human-readable. I'd think it may come at a cost. I'd be inclined to say we may tackle the problem wrong right now. Don't get me wrong, the research is all valuable - there's lessons to be learned from all the attempts so far which will no doubt help down the road. But as so often in human nature, especially when I look at the tedium at office jobs, you get to ask: How do we even know what of all of this is truly neccessary? Is there something we overlook? What's the core problem, and did I communicate it correctly? Most times you can't even be sure, because our wirings are not even uniform. At work. Now try globally. Human cultures, male and female, go down to animals etc. One might do good in finding the Atom first, before we dive into how to do alchemy. "Intelligence" as it stands is fairly human-centric in its definition, or in plain terms we wouldn't know it if it bashed our face in right now because the term is quite old and refers to all kinds of clever outcomes. Stuff like "emotional intelligence" is a buzzword, but it's inference itself may lead us to the core of the problem here. Right now we all have a fuzzy interpretation of what kinds of machines we want to build with this. Maybe it's time to define the problem first?

@@ddlc_monika the problem that we are trying to solve is one intuitively known by everyone: we are trying to build a god. At its core, I think that the race for AI (including the need for better hardware for AI models) is about designing an entity that can solve all of our problems, an intelligent entity inspired by human intelligence but not bound by the limitations of the human condition (i.e being limited in ressources such as time, attention, biological needs, ...), a true embodiment of the philosophical notion of Logos.

There is a universal language of logic, it's called 'First Order Predicate Calculus' or FOPC. i think I understand what you are saying. If you are saying that we don't even have a good definition of intelligence - I agree with you. People use the words artificial intelligence to describe everything that doesn't have a straight linear relationship or has a unique response to a stimulus. The point I was trying to make about the conceptual complexity of intelligence is itself complex. People that haven't lived in the world of neural computation can't see it - they think it is just like neural nets. In truth neuromorphic is to neural networks like neural networks are to Von Neuman architecture. They may look similar but they are fundamentally different. @@ddlc_monika

Most people I've worked with have more modest asperations than becoming the spirt of the universe. Our goal was always discovery, of the mind and the brain and the mind/brain. I don't think anyone expects the intelligence clergy to come and bless their work. Few realize, as I discovered during my R&D work, that the test for intelligent systems isn't deterministic it is behavioral.@@Hollowed2wiz

1) llms can translate natural language into any code. Tranformers where made for translations. 2) Artificial intelligence nowdays is an emergent property of neural networks, it is not hard-coded symbolically.

Isn't that exactly how diffusion works in image AI?

@@user-up1id5rv2m yes, I think it does

Not randomness but chaos. If you think that idea is interesting, then you should definitely look into cybernetics.

That was a TCN the layers equate to temporal context....the 5-8 layers simply represent the time windown needed to recognise a spike train. so not indicative of complexity. There are better approches which are more faithful to postsynaptic neuronal response which are quite small and efficient compared to the TCNN approach

Im seeing this so often in videos now, whats going on?

@@RaverSnowLep An AI bug? :)

@@RaverSnowLep It's a common mistake, while editing the voice lines, you might hear the start of a sentence, and to not lose time, you skip to the end of the sentence, so you might incorrectly assume that that line is correct because the start is correct and the end is correct. You'll not notice it repeats itself because you haven't heard the middle. The only way to avoid this is to hear the whole thing, which almost no one does. I think I remember hearing an Oblivion NPC in like 2006 saying something like "let me do that one again" between two identical sentences, you can find it on KZfaq.

Would that elevate the status of North American hockey players? Or bass tournament anglers in The South? Asking for a friend.... 😉✌️

That what current AI are, just not of hardware but software shape

Sounds like we have a lot of the how's and I think we understand a lot of the why's. Trying to replicate it is helping to connect those dots. If anything it is deconstructing the longstanding theories that made it seem like magic.

In fact, everything is not as bad as it might seem. People understand a key concept of how the brain works - it is a huge set of nested conditions, which, due to their large nesting, can make an incredible number of matches (speaking as an AI student). The main thing that still remains a mystery is the details of the structure of the brain and the principles of its self-learning. This certainly does not indicate an almost complete lack of knowledge about the functioning of the brain; I would even say that the opposite statement is more accurate. We know more key concepts than we have left to learn.

@@lit1041indeed, the only real issue left is the memory/storage problem. Where woo tends to happen 😂

​@@lit1041 I'd say the main mystery is figuring out how subjectivity works, and we haven't made any real progress on that.

This is very evident when you read about medications for depression and bipolar …. They all state, “while how the drugs works is unknown it’s suspected that …”

yes!

Yes. There is no reason why silicon couldn't imitate or even surpass the performance of a biological neuron. A biological neuron calculates on the order of hundreds of impulses per second. A digital neuron, if built as an ASIC on cutting edge process node, could calculate on the order of _billions_ of impulses per second. The overwhelming majority of the complexity in a biological neuron is not necessary for the computing the neuron does, so you could really argue that there is a simulation aspect to our brain. Enormous quantities of molecules and proteins that have nothing to do with the logical operations, as opposed to a chip where only the substrate is not an active participant in calculation. At best they have immunological or other physical resilience purposes that an artificial brain wouldn't need to implement.

​@@cerebralmand yet, the brain needs over 3300 types of neurons.

Neural networks don't actually simulate how a brain works, since a human brain is not trying to approximate a mathematical function, which is all a neural network is doing. An analogy would be an aeroplane; the aeroplane manages to fly, but it is not using even remotely the same mechanisms for flight as a bird does. The end result is similar, yes, and its designers were probably originally inspired by birds, but the way it is actually achieved could not be more different.

“Simulate” has been the implicit problem with AI. Just because you can argue that your CNN or AlexNet, whatever, appears to be accounting for, say, 70% of what you attribute to be a brain’s network response(e.g. the initial retinal network of a mouse), this does not mean your AI network is actually doing anything like the brain network - in fact you’re making assumptions on both ends - what the mouse network actually is, and your AI approach. This difficulty was already in full swing with Newell and Simon’s General Problem Solver, 1972, where they assumed that because the program’s steps were, say, 70% similar to the steps humans claimed to take in solving something like a symbolic logic proof, that this meant their simulation approach had validity, that it was actually near emulating the human brain/thought process - when nothing such was necessarily the case.

You of course don't know, but there are people out there that knows much much much more than you.

@@azhuransmx126 And even what they know is a drop in the ocean. The issue is that our tech is fundamentally different from how our body functions. It's like comparing a fish to a whale. Both live in water, but they couldn't be any more different.

@@VanFire87 aircrafts and birds, they don't need to work the same, to do..... the same and better.

@@azhuransmx126 We are fine the way we're going forward right now, with a few feature inspired from our nervous system and the like. Advancement in processing power and efficiency is our way forward, and not making a human brain computer, unless you're willing to overturn and overhaul all of the advancement we have gone though and don't forget the massive numbers of human experiments required.

@VanFire87 The area of ​​the brain responsible for controlling offspring rearing in mammals is known as the limbic system, and within this system, the anterior cingulate cortex (ACC) plays an important role in regulating maternal behaviors. The ACC is located in the medial part of the frontal lobe and is connected to other areas of the limbic system, such as the hippocampus and amygdala. This brain area is involved in the regulation of emotions, decision making and evaluation of social stimuli, and its activity is believed to be essential for maternal motivation and care of offspring. In studies in mice, it has been shown that lesion or inactivation of the ACC can decrease maternal motivation and reduce the mother's response to signals from her offspring. The ablation of the ACC by electroscalpel makes the mother regress to a stage 200 million years more primitive or reptilian, seen in animals from the Carboniferous period 440 million years ago, mammals are from the (Permian Triassic) 230 million years ago. Scan that area, compile and digitize the algorithms that make it work, calibrate its neuronal weights, download the cortical model of the mother on an artificial substrate descended from current GPUs (probably photonic chips), reconnect its inputs and outputs and you will see how the mother returns to take care of her babies as if nothing had happened. Turn off the artificial neural network and the mother will revert to a reptilian state and her babies will starve to death. In the future General Artificial Intelligences will do a brain scan of animals in Biology starting from the most primitive beings (flatworms descended from Pycaia) to the most advanced (apes and humans). With these stored connectomes, a virtual twin of the biological being will be created that will be subjected to the same gradient, amplitude and frequency of inputs and if they react exactly the same (Intelligence) we will have created a digital twin. In the digital world copy and original lose all meaning, once something becomes Code and becomes Information it can be replicated millions of times and no one can say that they have the original download of a song. We have been digitizing everything, books, audio, paintings, etc., and the last thing we are going to be able to digitize is going to be the most important thing, our brain and not even we will achieve it, but the AIs will achieve it. Ray Kurzweil describes a similar procedure to realize the Mind Uploading in his book.

The brain isn't an analog device. It's a biological machine, something we have never even tried before. Describing it as analog or digital is fundamentally wrong. I don't know of a single machine that works on chemical signals, based completely upon water, is self replicating and self repairing, and have a hard age limit coded into them. Oddly enough, we went more and more electricity based with our technological innovation, while biological evolution did the complete opposite.

Most likely the brain is nothing more than a transceiver.

A company is using 100 lava lamps to introduce chaos for using in cryptography. Maybe we need to create a tiny chip with 100 micro lava lamps to create a particular personality, making it impossible to predict their actions. It always was a problem in computing science, how to generate random numbers from nothing.

video on analog computing would be dope

Business in the front, party in the back.

Probably, you are just going to use some different python libs for that :-D. Compiler developers will care about the rest.

would be dope as well

Or you meant to say low noise (total) as opposed to low noise ratio.

Training takes too long and is too expensive though

@@rizizum Costs almost nothing to train. Mimics by itself. In fact the most successful schooling systems are mainly powered by children interacting with each other, like the ACT system. Very automated and very scalable when done properly.

reproducing human brains cost almost nothing nowadays, but reverse engineer them is the toughest part