B.Eng (Mechatronics)
I suggest an additional axis of "how hard is world takeover". Do we live in a vulnerable world? That's an additional implicit crux (IE:people who disagree here think we need nanotech/biotech/whatever for AI takeover). This ties in heavily with the "AGI/ASI can just do something else" point and not in the direction of more magic.
As much fun as it is to debate the feasibility of nanotech/biotech/whatever, digital-dictatorships require no new technology. A significant portion of the world is already under the control of human level intelligences (dictatorships). Depending on how stable the competitive equilibrium between agents ends up, required intelligence level before an agent can rapidly grow not in intelligence but in resources and parallelism is likely quite low.
One minor problem, AI's might be asked to solve problems with no known solutions (EG:write code that solves these test cases) and might be pitted against one another (EG:find test cases for which these two functions are not equivalent)
I'd agree that this is plausible but in the scenarios where the AI can read the literal answer key, they can probably read out the OS code and hack the entire training environment.
RL training will be parallelized. Multiple instances of the AI might be interacting with individual sandboxed environments on a single machine. In this case communication between instances will definitely be possible unless all timing cues can be removed from the sandbox environement which won't be done.
As a human engineer who has done applied classical (IE:non-AI, you write the algorithms yourself) computer vision. That's not a good lower bound.
Image processing was a thing before computers were fast. Here's a 1985 paper talking about tomato sorting. Anything involving a kernel applied over the entire image is way too slow. All the algorithms are pixel level.
Note that this is a fairly easy problem if only because once you know what you're looking for, it's pretty easy to find it thanks to the court being not too noisy.
An O(N) algorithm is iffy at these speeds. Applying a 3x3 kernel to the image won't work.
So let's cut down on the amount of work to do. Look at only 1 out of every 16 pixels to start with. Here's an (80*60) pixel image formed by sampling one pixel in every 4x4 square of the original.
The closer player is easy to identify. Remember that we still have all the original image pixels. If there's a potentially interesting feature (like the player further away), we can look at some of the pixels we're ignoring to double check.
Since we have 3 images, and if we can't do some type of clever reduction after the first image, then we'll have to spend 1.1 seconds on each of them as well.
Cropping is very simple, once you find the player that's serving, focus on that rectangle in later images. I've done exactly this to get CV code that was 8FPS@100%CPU down to 30FPS@5%. Once you know where a thing is, tracking it from frame to frame is much easier.
Concretely, the computer needs to:
Only step 1 requires looking at the whole image. And there, only to get an idea of what's around you. Once the player is identified, crop to them and maintain focus. If the camera/robot is mobile, also glance at fixed landmarks (court lines, net posts/net/fences) to do position tracking.
If we assume the 286 is interfacing with a modern high resolution image sensor which can do downscaling (IE:you can ask it to average 2*2 4*4 8*8 etc. blocks of pixels) and windowing (You can ask for a rectangular chunk of the image to be read out. This gets you closer to what the brain is working with (small high resolution patch in the center of visual field + low res peripheral vision on moveable eyeball)
Conditional computation is still common in low end computer vision systems. Face detection is a good example. OpenCV Face Detection: Visualized. You can imagine that once you know where the face is in one frame tracking it to the next frame will be much easier.
Well human vision is pretty terrible. Resolution of the fovea is good but that's about a 1 degree circle in your field of vision. move past 5° and that's peripheral vision, which is crap. Humans don't really see their full environment.
Current practical applications of this is to cut down on graphics quality in VR headsets using eye tracking. More accurate and faster tracking allows more aggressive cuts to total pixels rendered.
This is why where's waldo is hard for humans.
Yeah, transistor based designs also look promising. Insulation on the order of 2-3 nm suffices to prevent tunneling leakage and speeds are faster. Promises of quasi-reversibility, low power and the absurdly low element size made rod logic appealing if feasible. I'll settle for clock speeds a factor of 100 higher even if you can't fit a microcontroller in a microbe.
My instinct is to look for low hanging design optimizations to salvage performance (EG: drive system changes to make forces on rods at end of travel and blocked rods equal reducing speed of errors and removing most of that 10x penalty.) Maybe enough of those can cut the required scale-up to the point where it's competitive in some areas with transistors.
But we won't know any of this for sure unless it's built. If thermal noise is 3OOM worse than Drexler's figures it's all pointless anyways.
I remain skeptical the system will move significant fractions of a bond length if a rod is held by a potential well formed by inter-atomic repulsion on one of the "alignment knobs" and mostly constant drive spring force. Stiffness and max force should be perhaps half that of a C-C bond and energy required to move the rod out of position would be 2-3x that to break a C-C bond since the spring can keep applying force over the error threshold distance. Alternatively the system *is* that aggressively built such that thermal noise is enough to break things in normal operation which is a big point against.
This requires that "takeoff" in this space be smooth and gradual. Capability spikes (EG:someone figures out how to make a much better agent wrapper), Investment spikes(EG:major org pours lots of $$$ into an attempt), and super-linear returns for some growth strategies make things unstable.
An AGI could build tools to do a thing more efficiently for example. This could turn a negative EV action positive after some large investment in FLOPs to think/design/experiment. Experimental window could be limited by law enforcement response requiring more resources upfront for parallelizing development.
Consider what organizations might be in the best position to try and whether that makes the landscape more spiky.
Sorry for the previous comment. I misunderstood your original point.
My original understanding was, that the fluctuation-dissipation relation connects lossy dynamic things (EG, electrical resistance, viscous drag) to related thermal noise (Johnson–Nyquist noise, Brownian force). So Drexler has some figure for viscous damping (essentially) of a rod inside a guide channel and this predicts some thermal W/Hz/(meter of rod) spectral noise power density. That was what I thought initially and led to my first comment. If the rods are moving around then just hold them in position, right?
This is true but incomplete.
But the drive mechanism is also vibrating. That's why I mentioned the fluctuation-dissipation theorem—very informally, it doesn't matter what the drive mechanism looks like. You can calculate the noise forces based on the dissipation associated with the positional degree of freedom.
You pointed out that a similar phenomenon exists in *whatever* controls linear position. Springs have associated damping coefficients so the damping coefficient in the spring extension DOF has associated thermal noise. In theory this can be zero but some practical minimum exists represented by EG:"defect-free bulk diamond" which gives some minimum practical noise power per unit force.
Concretely, take a block of diamond and apply the max allowable compressive force. This is the lowest dissipation spring that can provide that much force. Real structures will be much worse.
Going back to the rod logic system, if I "drive" the rod by covalently bonding one end to the structure, will it actually move 0.7 nm? (C-C bond length is ~0.15 nm. linear spring model says bond should break at +0.17nm extension (350kJ/mol, 40n/m stiffness)). That *is* a way to control position ... so if you're right, the rod should break the covalent bond. My intuition is thermal energy doesn't usually do that.
What are the the numbers you're using?(bandwidth, stiffness, etc.)?
Does your math suggest that in the static case rods will vibrate out of position? Maybe I'm misunderstanding things.
During its motion, the rod is supposed to be confined to its trajectory by the drive mechanism, which, in response to deviations from the desired trajectory, rapidly applies forces much stronger than the net force accelerating the rod.
(Nanosystems PP344 (fig 12.2)
Having the text in front of me now, the rods supposedly have "alignment knobs" which limit range of motion. The drive springs don't have to define rod position to within the error threshold during motion.
The knob<-->channel contact could be much more rigid than the spring, depending on interatomic repulsion. That's a lot closer to the "covalently bond the rod to the structure" hypothetical suggested above. If the dissipation-fluctuation based argument holds, the opposing force and stiffness will be on the order of bond stiffness/strength.
There's a second fundamental problem in positional uncertainty due to backaction from the drive mechanism. Very informally, if you want your confining potential to put your rod inside a range with some response speed (bandwidth), then the fluctuations in the force obey , from standard uncertainty principle arguments. But those fluctuations themselves impart positional noise. Getting the imprecision safely below the error threshold in the presence of thermal noise puts backaction in the range of thermal forces.
When I plug the hypothetical numbers into that equation (10Ghz, 0.7nm) I get force deviations in the fN range (1.5e-15 N) that's six orders of magnitude from the nanonewton range forces proposed for actuation. This should Accommodate using the pessimistic "characteristic frequency of rod vibration"(10Thz) along with some narrowing of positional uncertainty.
That aside, these are atoms. De Broglie wavelength for a single carbon atom at room temp is 0.04 nm and we're dealing with many carbon atoms bonded together. Quantum mechanical effects are still significant?
If you're right, and if the numbers are conservative with real damping coefficients 3 OOM higher, forces would be 1.5 OOM higher meaning covalent bonds hold things together much less well. This seems wrong. Benzyl groups would seem then to regularly fall off of rigid molecules for example. Perhaps the rods are especially rigid leading to better coupling of thermal noise into the anchoring bond at lower atom counts?
Certainly if drexler's design is impossible by 3 orders of magnitude rod logic would perform much less well.
The adversary here is assumed to be nature/evolution. I'm not referring to scenarios where intelligent agents are designing pathogens.
Humans can design vaccines faster than viruses can mutate. A population of well coordinated humans will not be significantly preyed upon by viruses despite viruses being the fastest evolving threat.
Nature is the threat in this scenario as implied by that last bit.
edit: This was uncharitable. Sorry about that.
This comment suggested not leaving rods to flop around if they were vibrating.
The real concern was that positive control of the rods to the needed precision was impossible as described below.
well coordinated
Yes, assume no intelligent adversary.
There is a tradeoff to be made between level of bio monitoring, speed of air travel, mitigation tech and risk of a pathogen slipping past. Pathogens that operate on 2+day infection-->contagious times should be detectable quickly and might kill 10000 worst case. That's for a pretty aggressive point in the tradeoff space.
Earth is not well coordinated. Success of some places in keeping out COVID shows what actual competence could accomplish. A coordinated earth won't see much impact from the worst of natural pathogens much less COVID-19.
Even assuming a 100% lethal long incubation time highly infective pathogen for which no vaccine can be made. Biomonitoring can detect it prior to symptoms, then quarantine happens and 99+% of the planet remains uninfected. Pathogens travel because we let them.
I claim almost entirely orthogonal. Examples of concrete disagreements here are easy to find once you go looking:
I claim these don't reduce cleanly to the form "It is possible to do [x]" because at a high level, this mostly reduces to "the world is not on fire because:"
vs.
There is some projection onto the axis of "how feasible are things" where we don't have very good existence proofs.
These are all much much weaker than anything involving nanotechnology or other "indistinguishable from magic" scenarios.
And of course Meta makes everything worse. There was a presentation at Blackhat or Defcon by one of their security guys about how it's easier to go after attackers than close security holes. In this way they contribute to making the world more vulnerable. I'm having trouble finding it though.