[a-dub]

neuromorphic hardware is just hardware that has biologically inspired designs.

spiking neural networks are artificial neural networks that actually simulate the dynamics of spiking neurons. rather than sums, ramps and squashing, they simulate actual spike trains and the integration of energy that occurs in the dendrites.

neuromorphic hardware can range from specialized asics for doing these simulations efficiently to more experimental hybrid analog-digital systems that use analog elements to do more of the computation.

it's all very cool stuff, but i tend to think of snns as similar to the wings on the avion 3 where simplified unit functions look more like a modern jet wing.

but who knows, maybe the neuromorphic route will open the door to far more efficient computations. personally, i'm very excited about potential wins that could come from novel computational substrates!

[ImHereToVote]

I wonder how far we will move the goalposts once we have a multimodal transformer type model running on neuromorphic hardware.

[welferkj]

Lots of people involved in explaining away AI are labouring under the axiom that intelligence is mysterious. Therefore, if I can understand how a system works, it logically follows that it can't be intelligent.

[lucubratory]

I predict that many of those people will continue to believe that up until human cognition is mechanistically understood, at which point there will be some other reason that humans are "real" thinkers and machines are not. The problem is that theoretical opposition to the existence of AIs is incompatible with materialism and thus just doesn't fit with our world, which is very much built using the scientific truths that materialism enables us to discover.

[welferkj]

It is insane to me that views of consciousness and cognition other than physicalism still exist in mainstream scientific and philosophical discourse. As far as I can tell, no matter how much discourse you dress it up in, any alternative boils down to "it's magic, I ain't gotta explain shit".

[dartos]

We… can’t really understand how neural networks work, but we can definitely tell they’re not intelligent beyond making good sounding word soup (as demonstrated in their minimal practical reasoning abilities)

I wouldn’t call pagerank intelligent, even though I can give it a text prompt and get relevant information back.

In my view, the only difference between that and an llm is the natural language interface.

I’m no expert on intelligence, but I’d expect being able to introspect and continually learn to be part of it.

[welferkj]

You're engaging in explaining away intelligence.

One way to help you notice this is to try and estimate how many billions of people you've defined out of "being intelligent" with your latest goalpost movement.

Be honest, how many people do you think "introspect and continually learn" on a daily basis?

[cootsnuck]

> Be honest, how many people do you think "introspect and continually learn" on a daily basis?

That's wild if you think that isn't quite literally one of the defining features of human consciousness (and many would say other animals as well).

If you think people thinking differently than you means they don't still indeed...think...then I don't know what tell you.

[welferkj]

Unfortunately for the intelligence denial crowd, introspection and learning capability is something we can measure, as opposed to the vibes-based discourse you prefer to engage in. If that's what you've picked for your threshold of "intelligence", you've reduced the majority of the bell curve's left side to soulless automatons. Again, your definition, not mine.

[dartos]

It’s crazy to me that people would rather believe that we can create intelligence by feeding the text of the internet into a statistics machine, than believe that the people making that text are intelligent.

[dartos]

> how many people do you think "introspect and continually learn" on a daily basis?

At the very least, every single person who plays sports, video games, tries finding a way around traffic, a faster route home, a way to do less work, take a longer break, or a way to save some extra money getting food.

Literally any optimization task at all requires an observation, analysis (read: introspection,) and adjustment. That’s why we model training loops as optimization problems.

We spoof that with REACT prompts in LLMs, but it becomes clear after a few iterations that there’s no real optimization going on, just guessing at tokens (a gross oversimplification, as this guessing has real uses). It’s doing what it was trained to do, completes text. Not to mention that those steps all disappear when the prompt is changed.

[exe34]

> One way to help you notice this is to try and estimate how many billions of people you've defined out of "being intelligent" with your latest goalpost movement.

love this, I will use this in future rants.

[dartos]

That argument only works if your audience already thinks of humans as mostly automotons…

[joloooo]

I think there is a difference from people upset around over hyped LLMs and arguing about intelligence in "A.I.". Most of the "intelligence" arguments I've seen are fighting against putting too much stock in chatgpt and Sam's fever dreams.

[a-dub]

the goalposts for what?

[ImHereToVote]

Literal goalpost in a game of football of course. Or soccer if you are an American.

[a-dub]

thanks. you seem to think that a spiking multimodal variant of transformers on neuromorphic hardware would demarcate a goal of some sort, which one?

for as far as i can see, the achievement would just be a spiking multimodel variant of transformers on neuromorphic hardware.

[ImHereToVote]

I bet you are great at playing blackjack, but suck at Texas hold 'em.