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How much effort do you put into prompting it? Are you asking it one shot with a simple prompt? Are you giving it to multiple agents and giving them a workspace to collaborate in? You might give it to a trusted colleague who does not know the solution along with an agreement to jointly publish, ask them to go through the process of solving it with agentic support, and then compare your solutions.

Edit: to be clear, I completely believe your experience - just pointing out that it might be interesting for you to actually “try” to solve it thoroughly with the tools, though it is obviously hard to do that in a fair way when you know the solution.

Is there a path where compute gets poured into developing, and then eventually using, computational models that supersede the shortcoming of the existing computational approximations you mention, which thus makes computational analysis and developments possible at rapid scale?

In an area I am more familiar with though still not my domain: when the stiffness matrix and computational linear algebra methods collide, it unlocks a world of computational structural design and analysis by commoditizing the underlying mathematics. This is a simple example, but you get the idea.

Obviously with CFD, mechanics, etc there is always massive work being done to try to unlock new computational methods, faster/parallelizable computational methods, differentiable ones, etc etc, but the general feeling is that the core physics are well modeled (NS millennium problem not withstanding) and are not lacking in predictive power for useful applications. I would have assumed that the same would be generally true for computational biology etc, so just curious to hear you elaborate more. It seems plausible to me that turning the brute force of “the models” (as in, swarms of AI compute) to work on/develop/solve/address whatever representational problems there are in the computational approximations/numerical methods you mention, particularly if that is a bottleneck to performing more extensive methodological/experimental exploration in silico to enable better exploitation/use of limited resources in wet lab.

Again, I know nothing about computational biology, just stating my intuition and curious what your take is. Probably the limits of my knowledge can be demonstrated by the fact that the only modeling methods that come to mind as being vaguely relevant would be, like,… molecular dynamics, maybe discrete element method in a weird way but doubtful, and various pop science understandings of protein folding etc.

I think `uv lock -P <package-name>` to only update a particular package (and transitive deps of course).

Not sure why petrochemicals and trees ie hydrocarbons are any more or less absurd than the silicon, metals, etc quarried and mined from around the world needed to store information digitally in data centers (or mobile devices).

Storing data of any kind in plastic as opposed to silicon metal seems like a meaningless distinction that only comes about from imagining that there is some disembodied, ethereal and platonic notion of digital “data” which is decoupled from any physical substrate. everything is always materialized and mediated through some complex, and probably vaguely arcane, geologically extractive process in some way.

Yep, PassiveHouse standards which typically include an extremely tight envelope which forces installation of outdoor air supply famously can get away with just a few hundred watts of heating capacity because of heat exchange on the incoming and outgoing airstreams!

Sure I was playing a little fast and loose there, but (a) the large surface area of the home (and resulting conductive transfer through the walls + convection transfer via infiltration through gaps) is directly a result of the fact that you need a significantly larger volume for humans to move around in and live in than you do to store food and (b) even if we do look directly at the volume of air, the difference is significant since at the end of the day, since for any given constant deltaT, your energy spent is still linear with mass or volume. And we are talking about roughly 2-3 orders of magnitude difference in air volume between a house and a refrigerator.

Anyways, if you write out all of the heat balance equations, you get a few W/m2 of flux on the inside wall of the home and a few W/m2 of flux on the inside faces of the fridge, assuming a typical wood frame construction in summer time and steady states all around.

So yes, of course multiplying the flux through the home’s wall by the surface area of the home results in a massive heat gain value compared to the heat gain conducted through the surface of the refrigerator, but that’s arguably precisely because of the two different volume requirements.

FWIW, in a typical apartment or single-family home, refrigeration uses a fraction of the energy that space cooling (also via a refrigeration/vapor compression cycle) requires on a warm day (and probably year round too unless in very mild climates). The psychrometric chart path is different so there are of course differences in the amount of energy required for the sensible and latent components, but the real difference is just the volume of air that needs to be dealt with.

My point being that at least from an energy and carbon perspective, lowering the space cooling demand via more effective building envelopes or increasing the space cooling supply efficiency - eg via membrane or dessicant dehumidification, better heat pumps etc) is far more impactful on a macro scale than better refrigeration.

Granted refrigeration in a warehouse eg is really also space cooling, but I’m just making the distinction between the dT=0-25F context and the dT>25F context. If I could only choose one technology to arrive at scale to improve the efficiency, it would be for the former context.

> I'm particularly annoyed by using LLMs to evaluate the output of LLMs.

Even though I largely agree with parts of what you wrote, if you squint your eyes enough you can kind of see an argument along the lines of “difficult to solve but easy to verify.”

Hey out of curiosity were there any issues with my top level comment? Seemed pretty innocuous, curious what the problem was. Feel free to email me if it’s better suited for discussion outside of post context.

> That "problem" remains unsolved because it's actually a fundamental aspect of reality. There is no natural separation between code and data. They are the same thing.

Sorry to perhaps diverge into looser analogy from your excellent, focused technical unpacking of that statement, but I think another potentially interesting thread of it would be the proof of Godel’s Incompleteness Theorem, in as much as the Godel Sentence can be - kind of - thought of as an injection attack by blurring the boundaries between expressive instruction sets (code) and the medium which carries them (which can itself become data). In other words, an escape sequence attack leverages the fact that the malicious text is operated on by a program (and hijacks the program) which is itself also encoded in the same syntactic form as the attacking text, and similarly, the Godel sentence leverages the fact that the thing which it operates on and speaks about is itself also something which can operate and speak… so to speak. Or in other words, when the data becomes code, you have a problem (or if the code can be data, you have a problem), and in the Godel Sentence, that is exactly what happens.

Hopefully that made some sense… it’s been 10 years since undergrad model theory and logic proofs…

Oh, and I guess my point in raising this was just to illustrate that it really is a pretty fundamental, deep problem of formal systems more generally that you are highlighting.

Yeah, I think I’m with you if you ultimately mean to say something like this:

“the labels are meaningless… we just have collections of complex systems that demonstrate various behaviors and properties, some in common with other systems, some behaviors that are unique to that system, sometimes through common mechanistic explanations with other systems, sometimes through wildly different mechanistic explanations, but regardless they seem to demonstrate x/y/z, and it’s useful to ask, why, how, and what the implications are of it appearing to demonstrating those properties, with both an eye towards viewing it independently of its mechanism and in light of its mechanism.”

I don’t mean to amplify a false understanding at all. I probably did not articulate myself well enough, so I’ll try again.

I think it is inevitable that some - many - people will come to the conclusion that these systems have “ethics”, “morals,” etc, even if I or you personally do not think they do. Given that many people may come to that conclusion though, regardless of if the systems do or do not “actually” have such properties, I think it is useful and even necessary to ask questions like the following: “if someone engages with this system, and comes to the conclusion that it has ethics, what sort of ethics will they be likely to believe the system has? If they come to the conclusion that it has ‘world views,’ what ‘world views’ are they likely to conclude the system has, even if other people think it’s nonsensical to say it has world views?”

> The fact that a human image comes out of a mirror has no relation what so ever with the mirror's physical attributes and functional properties. It has to do just with the fact that a man is standing in front of it.

Surely this is not quite accurate - the material properties - surface roughness, reflectivity, geometry, etc - all influence the appearance of a perceptible image of a person. Look at yourself in a dirty mirror, a new mirror, a shattered mirror, a funhouse distortion mirror, a puddle of water, a window… all of these produce different images of a person with different attendant phenomenological experiences of the person seeing their reflection. To take that a step further - the entire practice of portrait photography is predicated on the idea that the collision of different technical systems with the real world can produce different semantic experiences, and it’s the photographer’s role to tune and guide the system to produce some sort of contingent affect on the person viewing the photograph at some point in the future. No, there is no “real” person in the photograph, and yet, that photograph can still convey something of person-ness, emotion, memory, etc etc. This contingent intersection of optics, chemical reactions, lighting, posture, etc all have the capacity to transmit something through time and space to another person. It’s not just a meaningless arrangement of chemical structures on paper.

> Stop feeding the LLM with data artifacts of human thought and will imediatelly stop reflecting back anything resembling a human.

But, we are feeding it with such data artifacts and will likely continue to do so for a while, and so it seems reasonable to ask what it is “reflecting” back…

So the author’s core view is ultimately a Searle-like view: a computational, functional, syntactic rules based system cannot reproduce a mind. Plenty of people will agree, plenty of people will disagree, and the answer is probably unknowable and just comes down to whatever axioms you subscribe to in re: consciousness.

The author largely takes the view that it is more productive for us to ignore any anthropomorphic representations and focus on the more concrete, material, technical systems - I’m with them there… but only to a point. The flip side of all this is of course the idea that there is still something emergent, unplanned, and mind-like. So even if it is a stochastic system following rules, clearly the rules are complex enough (to the tune of billions of operations, with signals propagating through some sort of resonant structure, if you take a more filter impulse response like view of a sequential matmuls) to result in emergent properties. Even if we (people interested in LLMs with at least some level of knowledge of ML mathematics and systems) “know better” than to believe these systems to possess morals, ethics, feelings, personalities, etc, the vast majority of people do not have any access to meaningful understanding of the mathematical, functional representation of an LLM and will not take that view, and for all intents and purposes the systems will at least seem to have those anthropomorphic properties, and so it seems like it is in fact useful to ask questions from that lens as well.

In other words, just as it’s useful to analyze and study these things as the purely technical systems they ultimately are, it is also, probably, useful to analyze them from the qualitative, ephemeral, experiential perspective that most people engage with them from, no?

On the other hand, IP addresses have crossed into the popular lexicon in exactly this manner… it’s common enough to hear people say “what’s my “ip?” or “are there any free ips?” or what are the IPs for x/y/z”.

I agree that it sounds stupid and incorrect, but that doesn’t necessarily mean using MCP as a metonym for MCP server.