Why would I want AI to write diary entries for me? Maybe the other stuff is valuable, but this seems like an inversion. I would prefer it help me write an entry by giving me a useful view and context with extremely low friction entry. Maybe I'd want nudges and reminders or reframings based on my entries, pending privacy concerns, but I definitely don't want a diary not written by me. The writing itself is the value, the act of thinking, preserving your feelings and thoughts honestly.
Almost but not quite I think. You can throw money at parts of problems. I think it's helpful to think it kind of like supercomputer MD/MC or electronic structure calculations. A tool that can get you valuable answers but not necessarily aid understanding. Simulations can be used to aid understanding also, and are integral to theory development. In the same way the approach to this result is.
I think a lot of people don't understand, with respect to a mathematical theory, the relation between a carefully stated conjecture requiring formal proof vs. using the objects in the theory effectively. Could better understanding of NS lead to better practical tools? Almost certainly, even if only to give us bounds on performance. Has its unresolved status stopped us from using NS? No. Almost no one using it cares. Resolving it is valuable, especially if it comes with mathematical and/or physical insight leading to greater understanding. But it is not this is grand result that like instantly unlocks 100+ day weather forecasts.
It would be like saying proving ergodicity more generally for physical systems would unlock condensed matter physics, ignoring how well stat mech has served us regardless.
I am not anti-AI and I don't think we should stop throwing them at conjectures. I'm against this fundamentally misleading type framing that's become prominent. Millennium prize problems are important. Treating this specific aspect of NS as the one missing piece is just harmful. If we just throw compute at formal conjectures voila cancer and fusion.
I think the better example of "AI" usefulness toward solving problems is AlphaFold, and immensely powerful tool. But also suffering from a false framing/marketing problem as "solving protein folding". It feels like the right use of compute. Considering many factors that we can't hold in our head at once. "Solving" something that was already "solved" via computation (simulation) but now much more efficiently. The output is a valuable tool itself, it was not about "solving the protein folding problem", which it didn't do. It is a tool to solve problems requiring a sequence->ground state calculation. Which is a very broad set.
Formal verification of a conjecture we set up as a benchmark we set to test human understanding is not valuable in the same way.
I'm failing to make multiple points and gotta run, but i think that final point is important. The millennium prizes are not about technological/practical value, at least not intentionally. They're about shit that seems fundamental to us, things that feel[1] to us based on our understanding are important AND feel like they should be solvable in a human-comprehensible way. So formally resolving them with pure compute is not really the point. It seems closer to that story about one of those prime conjectures where some guy just ran brute force enumerations to find a counterexample. Valuable for sure, time-saving. And knowing the answer makes it a lot easier to solve a problem.
TL:DR science and math are more than formally resolving conjectures, they're about building up understanding and tooling that you can then build more on. AI should be an increasingly big part of it, but declaring "AI will solve fusion because it's smart" is like the rest of the fucking owl meme. I have no doubt it will help, most likely via simulations/quicker testing/calculations and verification. Maybe partly via reactor designs. Maybe partly being fed conjectures about bounds/limits that would be useful as inputs for the next iteration. And maybe even in the form of resolving some formally stated conjectures (I don't know enough plasma physics to name any).
[1] obviously to the mathematicians it's more than a feeling..
Places that used to be 32C in summer are consistently hitting 36C+. It absolutely sucks to be outside in those temps. You are running from aircon to aircon. Doom scenarios of unbearable heat is definitely true.
Germany had two sizable heatwaves this summer, of which one was so intense that for the first time in about "ever" ACs tripled/quadrupled in price (note this includes those on online stores where the shipping times would allow for trucking them in from all across central Europe)... I'm not referring to installation labor/technicians even. But like window units and similar ones that don't rely on HVAC technicians to take out the box and turn on.
I was responding to the claim that many models had predicted catastrophe. An Inconvenient Truth is a movie made by a politician. It, of course, chose to depict the more extreme ends of probabilities. And despite that, I think it stands up pretty well, all things considered.
That doesn't relieve people of the responsibility of having enough scientific literacy to understand that 30 years is only an instant on geological time scales. And the fact that we see meaningful change at all on this time scale is very concerning.
Ah yes, I believe one of those models was called the Strawman Model, generated by Elliot F. Strawman during his tenure at MIT. He was forced into retirement due to his deep embarrassment over his model’s inaccuracies.
Anyway, Illinois is about to break the all time record for tornadoes by a single state, previously held by Texas, during the strongest El Niño ever measured. I’ll be proud tucking my kids in and telling them as long as they pray hard enough to the Gods of technological progress, we’ll be guaranteed to stumble upon a carbon sequestration technology akin to the Haber process and they won’t have to be forced into a Sophie’s choice when there’s only enough clean water for 2 of their 3 children.
Worth noting Texas is having one of its quietest tornado years in the ~20 years of comparable data, at the same time. Which is the problem: the reliable detection era is about 30 years, and the preliminary dataset behind these headlines starts in 2004. The IPCC has low confidence in observed trends in severe convective storms for exactly this reason. And your El Niño point argues against you, since El Niño is associated with suppressed spring tornado activity in the southern Plains, which is what we're seeing in Texas.
From what I read Texas will have larger and more intense heat domes. On the plus side, this high pressure shifts tornado alley towards the east away from Texas. On minus side, Texas will be the new Arizona.
Can’t say that I follow. What does a king have to do with forming a more perfect Union, establishing Justice, insuring domestic Tranquility, providing for the common defense, promoting the general Welfare, and securing the Blessings of Liberty to ourselves and our posterity?
If you allow justifying government power according to some ambiguous notion of general welfare, then all you need to say is that something promotes general welfare. There is more to the structure of the US system than the preamble to the constitution.
You're conflating purpose with power. "Promote the general Welfare" doesn't create unlimited power. The power comes from the Constitution. The point is that once you are interpreting those powers, the Constitution's stated purposes are relevant to what they mean and how broadly they should be understood.
Nor was "general Welfare" some contentless phrase at the Founding. Protection, safety, prosperity, happiness, and the well being of the political community were all part of the contemporary vocabulary surrounding the public good. As Madison wrote in Federalist 45, “the public good, the real welfare of the great body of the people is the supreme object to be pursued”.
All government powers carry some risk of abuse. But, as Joseph Story put it, “Neither rulers, nor any other functionaries, much less any private persons, have a right to cripple it, because it is according to their own views inconvenient, or dangerous, unwise or impolitic, of narrow limits, or of wide influence.”
Maybe I'm misinterpreting what you meant in your original comment? "This seems to fall under the whole “promote the general welfare” part of the Preamble of the Constitution, though perhaps the court is unaware of it."
The OP is about a federal ruling saying clean water is not a constitutional right, no? And if you're disagreeing you're saying it should be a positive federal right in interpretation if not declaration, implying power of enforcement.
Yes? Why would there be? This is a nation built on negative rights. If you pay taxes/fees to some institution for a service and the the institution fails to provide it, that's already covered by some contract law, no?
I know this will be read as me saying they shouldn't have clean water. What I'm saying is that declaring a positive right is not an effective approach to satisfying that right in this country, or anywhere that I'm aware. But especially this country. If I was in that jurisdiction I would be kind of insulted if this was presented as a reasonable approach to secure clean water.
I have a positive right to legal counsel, and trial by jury. We have, over the years, extended that to access to education and a wide variety of other items.
The Ninth Amendment exists in the Bill of Rights specifically to combat this misconception that the Constitution is an exhaustive list of the rights you possess.
"The enumeration in the Constitution, of certain rights, shall not be construed to deny or disparage others retained by the people."
Still sounds like negative framing to me. And when those implicit non-declared rights are judged legally, they are still judged in a negative rights lens, no?
The right to legal counsel and jury are protections are still defensive in framing, though I concede your point. Access to education I would also concede is partially positive though you see it is about not denying. I would also say the more recent positive-sounding rights declarations/rulings are not always on super solid grounds, but this is admittedly circular.
Warning: ramble ahead. I am not a statistician. This is based on my experience as a physicist-by-training exploring the more theoretical side of ML/AI.
Statistics is big. It's hard to answer without knowing what you plan on covering. I agree that most books (I've seen) suck. Wasserman all of statistics is the best I know, for my purposes. The problem I've found with most statistics books is trying to be too cute and clever by catering to a certain crowd thereby justifying holes that make it harder to truly understand and making the subject seem an incoherent patchwork.
The other problem that's even harder to solve is that the majority of people picking up a statistics book don't really think they need to learn statistics, just certain pieces. Which makes statistics seem less coherent and thus furthering the perception that statistics is in fact incoherent, leading to special background books that say "here's all you really need to know about statistics."
The final problem is statistics IS kind of incoherent as most often presented, especially when it tries to be what I'd roughly call "backward compatible". Why is so much time spent on p-values, for example? Is that really what a consistent modern perspective of statistics entails[1]? But backward compatibility forces it's inclusion, because that's what people still use and have used because they never got taught of "philosophy" of statistics, but rather rules. If you don't teach those rules everyone else uses, you're making them spend even more time on statistics than the small amount they're already unhappy spending. So the lowest common denominator is taught, which is incoherent. It's a vicious cycle that is not the fault of statisticians.
To an outsider there's not unifying dominant through lines because the field is justified largely through its application. There's no obvious "philosophy" or vibe of how to think about statistics. What I mean is that one approaching the field doesn't really grow more comfortable with it and doesn't really feel like they're advancing to a more coherent view, so they're less motivated to try to grok it, because it simply doesn't look like there is something to grok. With all of previous factors contributing to this.
So I guess the point of my ramble is that I think what's missing the promise of a reward for learning statistics "properly", really understanding it. In my biased view this is largely because it's not often presented to the non-professional statistics student as if there is a clear thing to understand, more just a collection of tools. And I think this is partly because the author already knows the reader doesn't want to spend time on it. So my advice would be, come up with a clear story of what statistics is. Promise and fulfill the promise that it is worth spending the time in a more abstract world for a little bit because the end is worth it. That it will save time and frustration in the long run because it won't just be a collection of basically faith-based tools with mystical rituals they will feel uncomfortable with for the rest of their careers. Tell that coherent story and then you can demand more commitment from your audience[2]. Maybe that cuts down your audience size but I think the net effect will be more people understanding statistics and what it actually is.
What would be the main threads and themes in your book? How would you justify spending time on it? What would require as necessary background? I don't understand the subject enough to offer any opinion. The most coherent things to me are convergence types and bounds. And then do you include computational approaches? For example in practice I'd say 90%+ of people would be better off using bootstrapping analysis for errors in most real-world cases compared to the standard "approved" approaches, but that's not very satisfying and the theory of it is certainly hard to integrate cleanly. TL;DR I don't envy anyone writing a statistics textbook.
[1] This is just a single aspect, but it gets to a broader problem. This is a really hard problem to overcome. So much of academia is taught p-values and to so much of academia that is basically the hardest math they know, and they work very hard to follow the rules they were taught, which to them is statistics. I don't know how you tell them to re-learn something especially when the answer is more math. That makes them even more hesitant and less likely to fully embrace a deeper understanding of the field.
[2] maybe that's the larger point. The analogy is maybe teaching calc vs. algebra based physics. Algebra based physics is harder to teach and learn, and it is less coherent and complete. There is not much meat in it, mostly rote tools. IMO conservation laws like energy and momentum and solving shit from there would leave a better taste for what physics is, but instead they are often used in one lecture to derive kinematic equations which are then elevated because students can memorize them. I guess it's better than nothing but it leaves people with the wrong impression of what physics is, just like I think most statistics leave a bad impression of what statistics is. Make the statistical equivalents of something like conservation laws the central objects. Something that makes it a coherent story that builds and rewards.
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