I mean, I guess the answer there would be to build the usual kind of Haber-Brosch process plants that run continuously, and feed them with hydrogen derived from natural gas. But just build them in the US.
Sorry, that's not going to work out for myself, the 8.5+ million hectares of grain growing about my location, nor for the billion+ tonne per annum of mineral resource shifted in my state.
We're interested in producing fertilisers and fuel from non fossil sources.
The laws of physics don't like your politics. Also, last time you played around with this stuff, the outcome was very very bad and lots of people died. So before you start trying to mess around with industrial infrastructure, maybe learn physics and chemistry first. Because you keep trying to do things that simply don't work.
> they things they believe in are unlikely to happen.
Sorry, but most times I've talked to someone who says this (about AI completely replacing humanity), they don't have anything to say about why it's unlikely to happen other than:
- "well, it's just such an extreme outcome, it must be improbable"
- "humanity has survived near scrapes with extinction before"/"all the previous doomsday predictions have been wrong"
There is a cliche that all teenagers deep down believe that they are invincible. It seems to me that humanity is still a teenager in this respect: We don't take seriously the possibility of our own extinction. While one might think that the invention of nuclear weapons would serve as a wake-up call, if anything it has done the opposite.
I'm willing to hear arguments besides the two above, if you have them. (And to be clear, being replaced by AI doesn't necessarily mean being replaced by LLMs in particular. They are a relatively new development.)
Just a terminology note: Alignment does not mean the AI will help its owner kill people. (Indeed, an AI aligned to value human life would generally try to prevent murders.) The word for an AI that follows all instructions of its owner, as that owner intended them to be understood, is "corrigible" or "controllable".
If M is the total mass of the object, then we can substitute this into the sum in the last term. And we already saw that the sum in the middle term was 0. So:
T' = ½(∑ⱼ mⱼ v⃗ⱼ²) + Δv⃗⋅0⃗ + ½Δv⃗² M
T' = ½∑ⱼ mⱼ v⃗ⱼ² + ½MΔv⃗²
So in terms of the original kinetic energy T, which was purely thermal energy, we get:
T' = T + ½MΔv⃗²
In other words, because of the quadratic kinetic energy formula, we can see that the total kinetic energy T' of a hot object is just its thermal kinetic energy T plus the usual mechanical kinetic energy ½MΔv⃗².
If you use the right formula for calculating it (which approximates p=mv at low speeds), momentum is actually conserved in special relativity, and so is energy.
However: Energy and momentum are not invariant under changes of reference frame, though the magnitude of the energy-momentum 4-vector is invariant between frames.
Energy is conserved in Galilean relativity. The thing you're trying to say is that it's not invariant across reference frames.
The answer linked above actually takes advantage of the fact that energy is not the same in different reference frames in order to make the argument work.
I think you are overthinking the heat thing. If you have a train car full of hot water and you slow the train down (extracting kinetic energy from it) until it stops, the water in the train car does not change temperature at all, other than a bit of sloshing around and loss of heat to the surroundings.
Yes that is what I meant. It’s not the same across reference frames.
I don’t find the OP a convincing argument. What is temperature, why can you assume it didn’t change and the measurement also didn’t change commensurately? Why should kinetic energy be convertible with thermal energy? Chemical energy?
It’s very hand wavy and introduces many assumptions.
Kinetic energy is a book keeping trick. The real mystery is explaining how it relates to other forms of energy and how to tie it together.
thinking aloud here - so it seems like 2 things are taken as intuitive here:
a) energy is conserved in any frame of reference.
b) energy can vary in 2 frame of references.
but then what it feels like is that when you reference the energy as mE(v), the v is actually not the only variable, and it will be more like mE(v, v_moving_reference)?
so we also must take intuitive that c) E(v, v_moving_reference) == E(v - v_moving_reference)
This looks like good work. Unfortunately, this kind of thing always seems to attract midwits on social media who then exclaim "oh, the people worried about AI alignment have caused the very alignment issues they feared? How ironic!"
In reality, it is (as mentioned in TFA) very possible to filter the training data and remove documents that contain discussions of AI misalignment. If an AI lab isn't doing this, it's simply because they don't consider the problem important enough to be worth the expense and development effort.
If you have a limited budget of tokens as a defender, maybe the best thing to spend them on is not red teaming, but formalizing proofs of your code's security. Then the number of tokens required roughly scales with the amount and complexity of your code, instead of scaling with the number of tokens an attacker is willing to spend.
(It's true that formalization can still have bugs in the definition of "secure" and doesn't work for everything, which means defenders will still probably have to allocate some of their token budget to red teaming.)
> If you have a limited budget of tokens as a defender, maybe the best thing to spend them on is not red teaming, but formalizing proofs of your code's security.
You can only do this if you have a very clear sense of what your code should be doing. In most codebases I've ever worked with, frankly, no one has any idea.
Red teaming as an approach always has value, but one important characteristic it has is that you can apply red teaming without demanding any changes at all to your code standards, or engineering culture (and maybe even your development processes).
Most companies are working with a horrific sprawl of code, much of it legacy with little ownership. Red teaming, like buying tools and pushing for high coverage, is an attractive strategy to business leaders because it doesn't require them to tackle the hardest problems (development priorities, expertise, institutional knowledge, talent, retention) that factor into application security.
Formal verification is unfortunately hard in the ways that companies who want to think of security as a simple resource allocation problem most likely can't really manage.
I would love to work on projects/with teams that see formal verification as part of their overall correctness and security strategy. And maybe doing things right can be cheaper in the long run, including in terms of token burn. But I'm not sure this strategy will be applicable all that generally; some teams will never get there.
Radiators can shadow each other, so that puts some kind of limit on the size of the individual satellite (which limits the size of training run it can be used for, but I guess the goal for these is mostly inference anyway). More seriously, heat conduction is an issue: If the radiator is too long, heat won't get from its base to its tip fast enough. Using fluid is possible, but adds another system that can fail. If nothing else, increasing the size of the radiator means more mass that needs to be launched into space.
"Radiators can shadow each other," this is precisely why I chose a convex shape, that was not an accident, I chose a pyramid just because its obvious that the 4 triangular sides can be kept in the shade with respect to the sun, and their area can be made arbitrarily large by increasing the height of the pyramid for a constant base. A convex shape guarantees that no part of the surface can appear in the hemispherical view of any other part of the surface.
The only size limit is technological / economical.
In practice h = 3xL where L was the square base side length, suffices to keep the temperature below 300K.
If heat conduction can't be managed with thermosiphons / heat pipes / cooling loops on the satellite, why would it be possible on earth? Think of a small scale satellite with pyramidal sats roughly h = 3L, but L could be much smaller, do you actually see any issue with heat conduction? scaling up just means placing more of the small pyramidal sats.
Kudos for giving a concrete example, but the square-cube law means that scaling area A results in A^(3/2) scaling for the mass of material used and also launch costs. If you make the pyramid hollow to avoid this, you're back to having to worry about heat conduction. You assumed an infinite thermal conductivity for your pyramid material, a good approximation if it's solid aluminum, but that's going to be very expensive (mainly in launch costs).
In reality, probably radiator designs would rely on fluid cooling to move heat all the way along the radiator, rather than thermal conduction. This prevents the above problem. The issue there is that we now need to design this system with its pipes and pumps in such a way that it can run reliably for years with zero maintenance. Doable? Yes. Easy or cheap? No. The reason cooling on Earth is easier is that we can transfer heat to air / water instead of having to radiate it away ourselves. Doing this basically allows us to use the entire surface of the planet as our radiator. But this is not an option in space, where we need to supply the radiator ourselves.
In terms of scaling by instead making many very small sats, I agree that this will scale well from a cooling perspective as long as you keep them far enough apart from each other. This is not as great from the perspective of many things we actually want to use a compute cluster for, which require high-bandwidth communication between GPUs.
In any case, another very big problem is the fact that space has a lot of ionizing radiation in it, which means we also have to add a lot of radiation shielding too.
Keep in mind that the on-the-ground alternative that all this extra fooling around has to compete with is just using more solar panels and making some batteries.
At no point did I propose a massive block of solid aluminum. I describe the heated surface and I describe a radiating surface, so programmers understand the concept of the balance of energy flow and how to calculate rest temperature with Stefan Boltzmann law, if they want to explore the details they now have enough information to generalize, they can use RMAD and run actual calculations to optimize for different scenarios.
Radiation hardening:
While there is some state information on GPU, for ML applications the occasional bit flip isn't that critical, so Most of the GPU area can be used as efficiently as before and only the critical state information on GPU die or host CPU needs radiation hardening.
Scaling: the didactic unoptimized 30m x 30m x 90m pyramid would train a 405B model 17 days, it would have 23 TB RAM (so it can continue training larger and larger state of the art models at comparatively slower rates). Not sure what's ridiculous about it? At some point people piss on didactic examples because they want somebody to hold their hand and calculate everything for them?
