Yes, on a linear basis it's not going to happen anytime soon.
But the trends in the space are developing around self-interacting discrete models to great effect (see OpenAI's Dall-E).
The better and broader that systems manage to self-interact, the faster we're going to see impressive results.
As with most compounding effects, it's slower growth today than the growth tomorrow. But a faster growth today than it was yesterday.
The human brain technically took 13.7 billion years to develop from purely chaotic driven processes, and even then it was pretty worthless up until we finally developed both language and writing so we could ourselves have lasting compounding effects from scaling up parallel self-interactions.
And from 200,000 years of marginal progress we suddenly went in less than 7,000 years from no writing and thinking the ground below our feet the largest thing in existence to measuring how long it takes the fastest thing in our universe (light) to cross the smallest stable object in our universe (a hydrogen atom).
Let's give the computers some breathing room before declaring the impossibility of their taking the torch from us, and in the process, let's not underestimate the effects of exponential self-interactions and the compounding effects thereof.
On the other hand those saying "it will sure happen" are missing the impact of diminishing returns.
Personally, i don't doubt that AGI is possible, even though it becoming a reality might take any number of centuries or millennia, if humanity even sticks around for that long and AGI is still a goal that they pursue.
The problem lies in everyone thinking on a more human timescale: "Will we see AGI during my lifetime?" The answer to that is almost certainly no, no matter how much the industry tries to sell state machines as AI or fledgling efforts as revolutionary advances.
Being overly optimistic in regards to time scales only hurts oneself, like expecting that we'd all have flying cars or even that we'll be able to get rid of ICE vehicles or make significant improvements to slowing the pace of climate change.
It’s so difficult to talk about AGI, sentience, consciousness in general because there are no clear definitions apart from “I’ll know it when I see it.”
It doesn't really matter what your guesses are, none of the results are good news.
I'm curious as to your answer. Because if one's building a purpose-built analog computer for the task, my estimate is a few hundred transistors, a few thousand passives, and ... an absolutely trivial amount of power on modern process.
But let's say we can. Let's say we need 320 transistors, which would be 20 transistors per pixel. That's pretending 99.7% of the seven thousand synapses each neuron has are useless for our purpose, but we'll do it. A chimp brain runs all the autonomous physical processes of a humanoid body while only having 22 billion neurons. We'll also pretend, wrongly, that chimps have no mind or emotions at all and that we only need the extra human neurons to make a sapient mind.
Humans have 86 billion neurons. Subtracting 22 gives us 64 billion, times 20 transistors per neuron gives us 1.28 trillion transistors.
1.28 trillion transistors, even with a bunch of handwaving to make it easier, and even pretending we exactly understood how sapience worked in the first place.
If you define the problem as importing 420,000 pixels, and target recognitions, and vector analysis, then you need a whole lot more computation than the organism uses. But presumably you're going to also get better results. We both know that's not exactly what's happening, I think.
That is, we know we can solve similar tracking problems with a whole lot less state.
> That's pretending 99.7% of the seven thousand synapses each neuron has are useless for our purpose
Not really... I think we can imagine a whole lot of passives / linear operations involved, along with the big nonlinear processes we need transistors for.
We're also assuming there's no net benefit to cognition that can happen using transistors, I'll note-- e.g. they have a ton of bandwidth compared to neurons, can be multiplexed more readily, etc....
> Humans have 86 billion neurons. Subtracting 22 gives us 64 billion, times 20 transistors per neuron gives us 1.28 trillion transistors.
So about half the number packed onto Cerebras WSE-2 today.
> even pretending we exactly understood how sapience worked in the first place.
This is the big problem.
So, basically, 45 x RTX 3080?
ENIAC also started big and slow. Now it fits in a microSD card.
The device running Spotify may also have an antenna, but I hope you get the analogy. My analogy is not meant to be taken faithfully, so that we need to start looking for antennas now instead of neurons. I am just saying that maybe the neuron-counting game is not the only thing. Maybe there is something else -- not magical, not divine, but physical and as-of-yet unknown. Humanity didn't always know everything, and maybe still doesn't.
Human optic nerve can't send more than ~10Mbit/s. Yet, somehow, 60fps at 640x480 screen isn't best possible movie watching setup for one-eyed people, even though it delivers uncompressed 9Mbit/s.
Lots of calculations (like aggregating data to lower-quality image; eg. input of human rod cells is aggregated through interneurons) happen around of body. 16 neurons that you are referring to are likely fed with carefully processed input, not raw input.
1960s - Herbert Simmons predicts "Machines will be capable, within 20 years, of doing any work a man can do."
1993 - Vernor Vinge predicts super-intelligent AIs 'within 30 years'.
2011 - Ray Kurzweil predicts the singularity (enabled by super-intelligent AIs) will occur by 2045, 34 years after the prediction was made.
So the distance into the future before we achieve strong AI and hence the singularity has been, according to it's most optimistic proponents, receding by more than 1 year per year.
Eventually I believe we will get a good enough understanding of the subject that we can map out a route to implementing AGI, and then our progress will accelerate towards a known and understood goal.
We won't build a duplicate of the human brain - unless we have AGI first to tell us how. But we really don't know what portions of the human brain are needed for useful AGI.
You can look at GPT-3. On the one hand, never being reliable puts a crimp on practical applications. One the other hand, it does a lot of amazing things that seem human. I'd say that since we don't know where we're going in a profound way, we don't know how far we have to go.
OTOH, we see specialized intelligences do all soft of superhuman feats, all the time, and more impressive abilities join these all the time. These, however, are not human-like intelligences. They aren't even bee-like. They are so alien we don't see "general intelligence" in them.
So, my guess is that we'll have some extremely complex and capable systems that are extremely alien in nature well before we can have a conversation with a human-like intelligent system. They'll be useful and treated like oracles - we won't be able to understand their reasoning, but they'll be right most of the time.
It is, however, a matter of time and desire. There is nothing inherently magical in our mammalian brains and our organic bodies that can't be simulated by a sufficiently capable machine and technology for that will, eventually, become possible, then available, then practical, and then ubiquitous.
And I'd like to believe that you're right about it only being a matter of time and desire, but I do also worry about the possibility that we're actually on a different kind of exponential curve and will instead reach a point where we see diminishing returns.
AI is a tool like many others, useful for some things and not for others.
The last and most difficult step in safe AGI is moral/value alignment. That is unfortunately probably last on the timeline of likely achievements because it requires general solutions to both planning and reasoning, and also an accurate world model and understand of physical actions and their consequences.
What we have is a fairly loose mix of categorisers and recognisers, biochemical motivators and goal systems, some abstraction, and a lot of externally persistent cultural and social programming. (The extent and importance of which is wildly underestimated.)
The result is that virtually all humans can handle emotional recognition and display with speech and body language including facial manipulation/recognition. But this doesn't get you very far, except as a baseline for mutual recognition.
After that you get two narrowing pyramids of talent and trained ability. One starts with basic physical manipulation of concrete objects and peaks in the extreme abstraction of physics and math research. The other starts from social and emotional game playing, with a side order of resource control and acquisition. And peaks in the extreme game playing of political and economic systems.
So what's called AI is a very partial and limited attempt to start climbing one of those peaks. The other is being explored in covert collective form on social media. And it's far more dangerous than a hypothetical paperclip monster, because it can affect what we think, feel, and believe, not just what we can do.
The point is that it's a default assumption that the point of AI is to create something that is somehow recognisable as a human individual, no matter how remotely.
But it's far more likely to be a kind of collective presence which doesn't just lack a face, it won't be perceived as a presence or influence at all.
Dubious
> and also driven by boring chemical/thermal/electrical interactions.
Implausible exotic matter, negative energy, etc, are usually prerequisites.
Just like the existence of flying birds were a hint that flying machines might be possible, the existence of thinking creatures is a hint that thinking machines might be possible.
Guess what is more likely to be implemented.
There are trillions of examples of insects on earth, but they do us no good when it comes to building one without using an evolved framework.
We've created a great number of things that had no natural analog. The internet, space travel, etc. I'd say our odds of doing something we haven't seen before are about even with artificially recreating a lot of things we see every day
Do we observe general intelligence in nature though, here on Earth implemented with the materials available in our environment? If so, it’s a bold claim to make that it will always be impossible to achieve it artificially.
The same is true of AGI. Of course it's possible. but right now no one has any clear idea how to do it without extreme brute force.
Personally, I think it's more likely that we'll have a working Alcubierre drive before anything approaching general intelligence
Impossible due to physics limits. Human lungs have 57 square meters for extracting oxygen from fluid with 21% volume oxygen. 30°C air-saturated water have 0.5% of oxygen, so working gills for human would need surface area of 2394 square meters.
You’re making the same mistake as those who critiqued the concept of heavier than air flying machines, starting from the assumption they must work by flapping their wings. As it happens now we have wing flapping drones anyway though.
“Ever” is a very, very, very long time.
This puts the timeline to about 2029-2035.
[0] https://www.scientificamerican.com/article/what-is-the-memor...
The trick of the human brain is that the "processing power" is enmeshed into the "memory", so the brain must have a colossal computational bandwidth, even with pretty slow neurons. I suppose that bandwidth is larger than that of most modern GPU / TPU clusters, which also don't feature anything comparable to 2.5Pb or RAM in their disposal.
The revolution should be mostly in the architecture, much like the deep learning evolution was enabled by GPUs.
Even with your numbers, that's a 6.4x decrease in price per TB (($100/1Tb) / ($250/16TB)), which is around 2.7 halvings over the course of 10 years, which is very close to my "2-3 years per halving" statement.
Even if it's slower than a halving in price per 2-3 years, 4-5 years say, this only delays my prediction by a decade or so.
Feasibility is great but economic access is the aspect that I'm focusing on.