nchagnet
> It’s important to note that there is a universal range of all mathematical functions: they can only output…. well, numbers.
That isn't even remotely true. Not even digging far, you have higher order functions which takes functions as arguments. You have functions on more abstract algebraic sets.
> You will never see a calculator give you the word “buttercup” or the symbol “” be the output of a function, nor will a sufficiently complex function arise that outputs not just a non-numerical character, but say, a living animal or a distinct smell. You could devise a machine that outputs non-mathematical things when a function takes a certain input, but that is something built outside of this formal system which is the pure realm and ontology of math. Math has a certain ontology which cannot create from itself something of a new or different ontology. This is obvious.
A smell is chemical reaction in your nose between two molecules which triggers a certain electrical impulse propagated to your neurons. You can _argue_ that what happens then is outside the ontology of the material world, but the fact that a smell is not a number has like zero connection to that, so you haven't proven squat.
> that unconscious and unspiritual cosmos of matter is precisely a massive material calculator, we should also realize that it as well cannot create a new distinct ontology out of itself alone—it cannot generate from itself something that is not a physical force of some type or complexity.
What do you mean by a calculator? How can the universe be a calculator if a calculator only deals with numbers (according to your reductive point) yet the universe is also comprised of things that's aren't numbers? You see how that doesn't work out? You can't take a reductive point of view when it suits you and contrast it with non-reductive statements just because.
Also what is "a physical force of some type or complexity" even about?
I'm going to stop here. This is worse than AI slop, it's nonsense.
Heck your descriptions of a model is also what we would call an effective theory (i.e. a description valid for a specific range of parameters/scale).
I don't think there's a commonly agreed difference between model and theory and I sure have heard many physicists use them interchangeably when it suits them (and I'm guilty of it myself). Perhaps theory feels 'wider', as in quantum theory encompasses models for many quantum systems, but that's as far as I'd go.
I don't have a problem with using llms for projects per se if it helps, so long as there is a vision, but why would anyone buy an introductory book to a popular language which the same llm could one-shot? What's the added value here?
Uv is fantastic, but its package management UX is a mess
You say, to the community, as it describes how it relates to the message.
You may not agree with it, but surely this thread among many should show you this view is not fringe or denial, but how a strong segment feels. I concede it's a divisive topic, some people feel optimistic, others less so. I myself don't fully know where I stand. I just don't agree with branding all of this as "unhinged nihilism".
When is the last time you opened an HN comment section and the main comment was that people enjoyed the writing quality? Maybe it says more about what we usually read as a crowd, but to me this was a breath of fresh air, it was engaging but also quite deep at times.
I think the mark of great writing is that it makes an impression on you, on others, in a way casual writing doesn't. At least that's my take on this.
In a sense I really get your complaint. It's the xkcd standard thing all over, we now have a new competing standard.
I think for me it's not so much the ggplot connection, or the fact that I won't need a dataframe library.
It's that this might be the first piece of a standard way of plotting: no matter which backend (matplotlib, vega, ggplot), no matter how you are getting your data (dataframes, database), where you're doing this (Jupyter or marimo notebook, python script, R, heck lokkerstudio?). You could have just one way of defining a plot. That's something I've genuinely dreamt about.
And what makes this different from yet another library api to me is that it's integrated within SQL. SQL has already won the query standardisation battle, so this is a very promising idea for the visualization standardisation.
In my experience, the only thing data fields share is SQL (analysts, scientists and engineers). As you said, you could do the same in R, but your project may not be written in R, or Python, but it likely uses an SQL database and some engine to access the data.
Also I've been using marimo notebooks a lot of analysis where it's so easy to write SQL cells using the background duckdb that plotting directly from SQL would be great.
And finally, I have found python APIs for plotting to be really difficult to remember/get used to. The amount of boilerplate for a simple scatterplot in matplotlib is ridiculous, even with a LLM. So a unified grammar within the unified query language would be pretty cool.
Regarding your points:
- I'm not sure I get your meaning here. My understanding is that for a random variable X, thr surprise is defined at the outcome level I(x) = - log p(x) while the entropy is essentially just the average value - sum_x p(x) log(p(x)). So to me it does look like entropy is expected surprise no? I do agree though that by being _expected_ surprise, entropy is itself a measure of surprise.
- I very much agree with that which is why I used _excess_ surprise (maybe relative is a better choice, but the intent is the same).
- That one I'm also confused about. It gets back to my first point: to me surprise (or information) is always defined at the outcome level first, so taking a moment is not tautological, it's meaningful, no?
Where .env files shine is that: - they act as a declaration of expected environment variables, - they are project-scoped, which is one big issue with using "/etc" for example
I personally like to set a .env.example for my collaborators to know what's expected, and I use a .envrc with direnv. And to make it more secure, I always have .envrc in my global gitignore so I can't just forget it.
The drawback is that for any non-interactive run (debugger) I have to manually add each variable each time.
I agree with another commenter that while flat, the Netherlands have their own hurdles (biking with a strong headwind on the banks of the IJ is not easy, even if flat), and I definitely agree that their city design is what makes this unique.
I lived in various parts of France growing up, and I can assure you there are flat cities there, yet biking in them felt very risky at best.
But with electric bikes becoming more affordable, hopefully the gap can eventually close.
And not just young active people, it's a habit found across all age groups, parents bike their children to school (or with them if old enough, etc.)
All that to say I wouldn't worry too much about the feasibility issue, it's really more of a mindset to adopt, and it's happening more and more in France.
Also, I don't know if it was supposed to be a covert ad for the cybertruck, but it reminded how ugly this car is.