siddboots

I’d say this is firmly about knowing how colour mixing works, and not about memorising.

I think both approaches are useful. AI2027 presents a specific timeline in which a) the trajectory of tech is at least somewhat empirically grounded, and b) each step of the plot arc is plausible. There's a chance of it being convincing to a skeptic who had otherwise thought of the whole "rogue AI" scenario as a kind of magical thinking.

Maybe lack of empathy, although I don't think it's because managers are especially unempathetic people. We have a deeply encultured expectation that deference, gratitude, and loyalty are owed much more in the upward direction, than the downward direction. We expect employees to act as though they are subjugated, rather than merely subordinate.

I like to tell my colleagues that the Heaviside function is so named because it is heavier on one side than the other.

A Gaussian process fits a single high dimensional Gaussian, for example, by treating n observations along a single dimension as a n dimensional space.

Gaussian mixture models fit a large number of low dimensional Gaussians for example you might imagine 2D data generated by several 2D Gaussian superimposed.

This approach is just an example of the latter. It uses higher dimensional Gaussians to capture extra information from a scene, but not in the emulation of an infinite dimensional space in the way that defines Gaussian processes.

It's just a contract - if both parties are happy to deal with the energy in bulk, then there's no problem.

However, if either the buyer or seller thinks there is a risk some of the generation won't be produced, there's still lots of ways to manage that risk in a relatively simple way. Probably the simplest is a variation on "take-or-pay" where the buyer holds some of the risk when the generator is curtailed, i.e., not dispatched by the system controller. Essentially that means that the buyer is committing to have load available to generate against.

I've also seen renewable PPAs with time of use specified either in volume for purchase, or in the price structure.

It resembles a pie chart, but if you think of it instead as like a stop watch, then it makes perfect sense.

Just a data point: I've got access to plugins as of the last hour, but no access to web browsing yet.

I love that reddit now wants you to log in to view 18+ subreddits, and that the work-around is to replace "www" with "old" in the URL, asserting that you are indeed old enough.

It’s honestly something of a marvel to see a big ol’ framework like SQLAlchemy successfully manage these big structural api changes. The changes that have lead up to v1.4 and v2.0 have been very significant improvements to the user interface, and have kept the library up to date with the language in a way that is rare to see for a code base of such complexity. Also the new unified bulk insert interface is a big win for my ETL workflows.

Hats of to everyone be involved!

When I was quite a bit younger I went through a Wendy Carlos obsession, and spent a lot of time with Switched On Bach, Clockwork Orange, and some of Wendy’s other synth works.

Much later on, after my interests had wandered a long way from analog synth stuff, I went through a Bossa Nova phase, and at some point discovered Joao Gilberto’s 1973 self titled album which shortly became one of my favourite albums of all time. It’s an absolutely hypnotic, beautifully stripped back yet harmonically complex distillation of the bossa sound.

Only after having listened to it surely hundreds of times I read up on the recording and discovered that Carlos was the sound engineer!

That's where my mind went as well - in fact, it reminded me of Guy Debord:

> In societies where modern conditions of production prevail, all of life presents itself as an immense accumulation of spectacles. Everything that was directly lived has moved away into a representation.

I agree. The explosion of hype, the layers of scams, the idiocy of NFTs - all of it has put a bad taste in a lot of mouths, which is understandable, but unfortunate.

It's unfortunate because distributed ledgers are so much fun to play with. Conceptually simple enough that you can build one from scratch in an afternoon; deep enough that, notwithstanding the hype, there remains a huge amount of room for ideas barely explored.

Imagine if Hacker News could be a place that celebrated ideas like this for the love of hacking.

We've all made that mistake before.

I enjoy to agree with this article but in my belly I know it is just a story we incurable collectors tell to comfort ourselves.

Simply put, there are many people who are neither "beginners" nor "advanced". There is a section of the book titled Audience which reads

> Bayes Rules! brings the power of Bayes to advanced undergraduate students and comparably trained practitioners. Accordingly, the book is neither written at the graduate level nor is it meant to be a first introduction to the field of statistics.

Some more vocabulary for thinking about this is “analysis” and “synthesis”. Analysis is about breaking up a problem into isolated parts. Synthesis is reassembling the solved parts.

One fun thing to do is to take these death probabilities and throw them into a Leslie matrix [1], along with assumptions for the age-specific birth rates. From there you can simulate the projected population growth (ignoring migration) with no more than a couple of lines of Python/R/whathaveyou.

It's also a great study case for understanding some basic principles of linear algebra: The dominant eigenvalue is the stable population growth rate, and the corresponding eigenvector is the stable age distribution.

[1] https://en.wikipedia.org/wiki/Leslie_matrix

I largely agree with this. Occasionally it suggests a few lines that are more or less what I want, but rarely more than that.

One use case that I reach for relatively often is writing a comment to describe the one line of code I want when I can’t remember the specifics of the API I’m working with. E.g. # reset numpy random seed, and copilot pretty reliably gives me what I want.

They're called "Lambda Diagrams". See the inventor's homepage [1], and some animations [2]. There's actually a long and obscure history of visualizations for lambda calculus. One of the originals is "To Dissect a Mockingbird" [3], which if I recall correctly, was the main thing on the internet in 1996.

[1] https://tromp.github.io/ [2] https://www.youtube.com/playlist?list=PLi8_XqluS5xc7GL-bgVrx...

[3] https://dkeenan.com/Lambda/

I love remote work, but the timing of this particular pandemic has just sucked. Two small kids at home, with my wife and I trying to share parenting and part time work - throw WFH into the mix and everything kind of falls apart.

All of Statistics by Larry Wasserman is a great introductory book from the frequentist tradition that includes some sections on Bayesian methods. It's definitely not frequentist propaganda - more like a sober look at the pros and cons of the Bayesian point of view.

While we are airing our pet dumb theories, is there any way that a universe with a cyclic geometry, like the geometry of a sphere, could explain the accelerating universe with just gravitation? Could the attraction of the matter in our universe from “the other side of the world” be made to explain the observed acceleration?

I have big love for PE. I've learnt so much in the process of trying to solve some of these problems. In particular, number theory and data structures are two fields that I have come to love almost entirely because of this website. I did a random selection of the first 200 problems on my own about a decade ago but ran out of steam as the problems got harder.

Recently, however, I introduced it at work as a way of encouraging the team I manage to work collaboratively. We have a fortnightly catch up where we talk through solutions, pick new problems (we have a script that randomly picks an easy, medium and hard problem, which has become an exciting ritual), and then we have an initial discussion about each of the new problems.

It's a good way to foster group work. It's also a great way to introduce people to using version control and pull-requests in a non-scary way!

This is broadly how I was thinking about it, but I don't have an intuition for why there would be a recurrence relation involving the factors of Q(m, n). What made you think of attacking it that way?

You’re implying that the only possible goal is to “get ahead”, which is not true. There are clearly other goals one can have in writing and in life.

A more “back of the envelope“ approach to handling uncertainty for this sort of thing is the “three point estimate” approach, where you give a best, worst, and most likely estimate for each sub task. These points are implicitly used to parametrise a distribution, and then you analytically find the overall uncertainty, rather than through simulation.

Maybe where you’re from that’s the accepted convention, but in some domains (e.g., scientific computing, statistical programming) it is common to mix in Greek letters . If the symbol is widely understood, it absolutely makes sense to use it.

Life-cycle emissions accounting is useful if we're considering technology options or feasibility assessment for a specific project. But the linked article isn't talking about any specific project. It's talking about whether geothermal is a good tech in general.

In that context the lifecycle emissions stats are less useful because the calculation assumes a rate of indirect emissions (due to construction, mining, refinement, containment, etc.) based on the incumbent power generation tech.

In other words, if geothermal power was more ubiquitous, then the indirect emissions for a new geothermal project would be lower.

Yet another example of temporal ambiguity is the notion of “bringing forward” or “pushing back” a deadline. The sense employed is the opposite of the ordinary use i.e., moving “back” into the past or “forward” into the future.