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This is a great setup. I’m approaching the age where I just want things that work and for no one to move my cheese

Any form of hacking products to be more useful is a win in my books! I can see the multi room play being a nice thing on the odd occasion. Perhaps if I had kids and had to move around the house a bunch more or maybe if it operated as a home system that could also do those additional things I may have had a more positive experience with it. But I maintain my original point that hardware tethered to some software service is basically a random financial-enshitification-quarter away from being bricked and that’s a shame for otherwise excellent hardware

I feel certain products just dont need apps or 'tech'. Speakers should not be 'smart' anymore than a powertool needs an app. It just turns products that should otherwise be long-lasting become disposable waste once software support evaporates for any reason.

I dont think it was a good product even back when it did 'work'. We received a pair as a house-warming gift and I remember not understanding how or why I should use them. I already had a soundbar that I could stream music to. I now, out of politeness, had to use these new "wireless" speakers that demanded a constant wifi connection but still required their own Very Visible power cables along with its own dedicated app which was nothing but a wrapper for music services that logged me out after every software update. I couldn't even use it as a dumb speaker and operate it as part of my main sound system so now I have a soundbar that is nicely mounted to the wall and additionally these speakers that clutter my living room. Lovely.

"Heavier vehicles are safer for their occupants.."

Only if the other vehicle is smaller/lighter. SUVs were relatively uncommon when this perception of safety was established. Its now just something people like to tell themselves as justification for buying an even bigger car.

What a crap business model these companies have if they rely on haggling over legal loopholes to operate. The business case, at best, is the status quo remains with material threats to their operations if these laws change. This is a lose-lose for everyone. Ignore the morality arguments, why risk your money on something with almost zero upside and all this downside? Suing the government is not a sign of strength

The BT46B being banned after a single race is a bit of an urban legend. It was not banned and was perfectly legal to run for the remainder of the year.

The background to why Gordon Murray (designer) decided to go with the fan design was the flat-12 engine used by Brabham didn't allow venturi tunnels along the side of the car (flat-12s being too wide) so he had to find another way to respond to the then-new ground-effect others were exploiting.

A neat legal trick was discovered: a fan could be installed on the car as long as its primary purpose was to cool the motor. Primary purpose in this case meant, and GM got a lawyer's opinion on this, at least 51% of the volume of air went to cool the engine. Brabham was very clear this fan sucked the car to the ground but also proved to the governing body that most of the air went to cooling, so it was deemed legal for the rest of the year but the loophole was to be closed for the following year. Stories by Andretti about the BT46 throwing stones and being dangerous to other drivers was complete rubbish made up by Colin Chapman to get the car banned as he saw Brabham would walk away with the championship. In effect the tips of the fans never moved particularly fast (ballpark 50mph along the edges) so it was never dangerous to other drivers.

The actual story as to why it was withdrawn is Bernie Ecclestone, then owner of the Brabham team was also the head of the Formula One Constructors Association and the other manufacturers threatened to leave the association if he didn't withdraw the car. Seeing the bigger picture of securing TV and advertising rights to F1, Bernie withdrew the car after a single race.

These sorts of articles dont reflect how the US gov funds itself:

1. Gov spends $100 and taxes $90

2. Commercial banks then have $10 (100-90) in reserves at the Fed

3. Treasury is required to sell $10 of bonds to keep its account at the Fed at zero balance. (This collective tally of 'debt' is what everyone loses their minds over)

4. Commercial banks buy these bonds up immediately as long as the interest earned on the bond is greater than the interest earned on the reserves at the Fed.

Important things to remember:

- The $10 'borrowing' done by the government is funded by the deficit it created.

- The treasury doesn't have to issue bonds to fund itself it can simply deficit spend as its done in every major war or during Covid.

- When the treasury does choose to issue bonds the coupons dont need to match market interest rates (this is what the Bank of Japan is doing this very minute). The bonds will always be purchased so long as there is a positive interest rate differential between the bond and the Fed's reserve interest rate.

- Bonds have secondary uses but funding the government is not one of them.

- Government debt = private sector savings. Collectively it represents the excess of money paid into the pvt sector vs whats been taken out via taxation.

- US gov bonds are extremely useful financial instruments used in all sorts of repo operations providing liquidity in the banking sector. They are better than gold!

- Dont stress about government debt. It has never, and will never, be repaid and thats a good thing because it effectively translates to a massive destruction of pvt sector savings.

Thats really impressive students are doing this. These tools are non-trivial to use and it shows great initiative from them. I could see these tools being used proactively as part of a creative writing class or helping people improve their language skills. Top stuff!

Have you used the Polars (https://www.pola.rs/) package? It does what Pandas does with a fraction of the RAM and twice the speed

I am certain I'm in the wrong here but I'm struggling to understand Arrow's USP. I (originally) assumed it meant python/R users would be able to get around memory limitations when model-fitting but all the examples I've come across are just data manipulation and none of the main modeling packages support it. Those who are using it, what am I missing?

You will own nothing and love it

>> Have a handful of executives who can't wait to get back into their comfort zone - the office - and that office spending budget will find a way to get spent

you could have just said this. everything else you wrote is superfluous justification

Totally agree there. It is not a replacement and it is trying to solve a different problem. I dont believe Julia contributers are lying awake at night upset that other languages exist and feel they need to put a stop to that. My point (put across clumsily I see) is that IF that was their goal then they are going about it the wrong way as most R/Python users have different priorities. But it is a moot point as that would be an absurd motivation to create a whole new language

'highfalutin ivory tower' is a great name for a band :D

Naturally you are correct and I am wrong to dismiss it as unimportant. What I'm saying is that the majority of R/Python users today are not looking for ultimate speed or sophisticated programming paradigms. Most users are doing the unsexy bread and butter of 'Take some tabular data' -> analyse -> report on it and I want to dismiss the argument of 'users will migrate to Julia because of these nifty features' because it ignores the very reasons the existing users use these tools in the first place. It would be as absurd as proclaiming Excel users will switch to Python because the accounts deparment suddenly cares about NLP.

If we removed dplyr, then R scripts would absolutely scream so I find the speed argument for 'why switch to X' unconvincing. If users cared so deeply about speed, almost no one would be using tidyverse instead we'd all be using base-R or data.table.

Multiple dispatch? Hmm is this really a problem that I'm going to come across in the real-world when 90% of our time is spent ingesting a poorly-formatted csv, doing some quick plots and perhaps building a model to test something out. If the goal of Julia is to replace R/Python then their priorities feel way off the mark

Based on this reply I assumed the topic was all about context-switching in a kitchen-environment. What a weird way to strawman

My guitar teacher has switched to using Rock Out Loud (https://rockoutloud.live/) and its made an enormous difference. Music is no longer distorted and the lag is negligible so we're now able to jam together realtime rather than having to take turns playing sections.

Fascinating! I hadn’t heard of this before. The closest I’ve found in the same vein is a 1994 article by Edward Luttwak who predicted another wave of fascism in the western world driven by economic decline of the middle class:

“It is only mildly amusing that nowadays the standard Republican/Tory after-dinner speech is a two-part affair, in which part one celebrates the virtues of unimpeded competition and dynamic structural change, while part two mourns the decline of the family and community ‘values’ that were eroded precisely by the forces commended in part one. Thus at the present time the core of Republican/Tory beliefs is a perfect non-sequitur. And what does the moderate Left have to offer? Only more redistribution, more public assistance, and particularist concern for particular groups that can claim victim status, from the sublime peak of elderly, handicapped, black lesbians down to the merely poor.”

Link to article here. https://www.lrb.co.uk/the-paper/v16/n07/edward-luttwak/why-f...

Credit growth expands the money supply and stimulates economic growth so long as that expansion is ever increasing (park what that means practically). This mechanism of credit growth linked to some asset has been the largest driver of economic growth in the western world for decades. For the UK, where I live, the growth in household debt / gdp has been steadily increasing since the late 80s and I'd be surprised if its much different for other developed nations https://www.theglobaleconomy.com/United-Kingdom/household_de...

Countries that have come to rely upon their property markets for economic/political ends are likely going to come up with ever more elaborate schemes to maintain the above mechanism (UK, Australia, Canada and Denmark spring to mind). Indeed the unhealthy focus on the property market in the UK is a sign of the disconnect between real economic activity and asset inflation. Rationally this is an absurd mechanism for economic growth as it causes large divisions within society but its difficult to see these countries reverse course and what is more likely to happen is growth in private debt levels will level off and overall economic growth will stagnate similar to what Japan has experienced now for 3 (going on 4) decades.

Plug away! Thanks for the weekend reading!

Your solution is similar to mine, but I've gone a step further and put in times in my calendar when I'm available for questions/updates/requests etc. It doubles up as the admin-part of my day where I update my GTD-style inbox of tasks that may have come up and then allocate times in my calendar when I'll deal with various tasks in future.

There is a larger problem you're touching on that in most knowledge-workcompanies there is little to no attention paid to the production line process of how that work is 'produced' with the inevitable miasma of low-value busywork ('quick question, where are we with X','thoughts on X??' etc)

> I would bet on EV planes replacing regional jets

Energy density of batteries are around 1/40th of that of kerosene (0.9 mj/kg vs 44mj/kg) so we are talking 44x the energy density we need to make up for to get perfect parity. From what I can find I’ve seen 35% thermal efficiency for modern airliners and I believe 95% for electric motors. Ok so this means we can reduce the density gap required for parity to just under ~ 44/2.5 so ~18/19 mj/kg? (I’m doing this in my head so it’s rough). Rough calls show we need batteries with 20x the capacity to replace what we have right now with electric alternatives. While the gains in battery densities have been impressive we need to keep these gains in mind that we need to be making much bigger gains for this to become a reality. Personally I don’t see it being feasible for a very long time given the progress and I believe we’re better off taking fewer unnecessary flights than hoping on some miracle battery breakthrough

(Edited for clarity)

Many cities (in the USA) are mandated to have balanced budgets, limiting the size and scope of providing UBI-style benefits so something like this is difficult to role out without federal support. I’m pro a limited UBI but I don’t think it does people any good to not have a job to do so I’d want to see UBI as being a first tier program with a universal jobs guarantee as a second tier with each municipality having the choice over what they want those jobs to be.

> All improvements are good, but I'd like to know if this is more than a distraction to make people feel better about continuing to demand products they know are damaging the environment (e.g. Amazon deforestation).

I think you're on the money. This is the equivalent of us wanting to keep driving around in 2.5ton SUVs by justifying to ourselves that it’s a hybrid

The performance of DuckDB's predecessor, MonetDBLite, was/is stellar. DuckDB, when I tried in 6 months ago, was a bit behind in terms of csv parsing or aggregation by groups and didn't seem much faster than regular sqlite so I didn't really jump at it. Does anyone here know if the performance improved since then and how it compares to MonetDBLite?

Boy oh boy as a car enthusiast this stuff makes me nervous for Aston's future. There's absolutely nothing wrong with brands having these separate businesses by attaching their names to things(ahem Ferrari aftershave), but Aston has gone off the deep end in the past few years involving itself power-boats, luxury high-rise buildings and all sorts of marketing schemes while its core products have stagnated. These side-shows are an effortless way for companies to fool themselves into thinking they are doing real work but, to me at least, it looks like they have ignored their core products. The new DBX is promising, but the Vantage is comically overpriced for its segment I don’t think their DB11s are exactly walking out the showrooms

>> If you don't and just storm in talking about something something neural nets, they'll see it as a waste of time, won't bother explaining nuances

>> Another major point is specifying the metrics. The real world metrics, not AUC or F1 scores. You need collaboration to get there, too.

>> you need their help getting data, and their expertise to understand it.

All this x100. And it's made worse as this humility isn't taught in schools and rarely asked in data science interviews

Yes, it’s a given you need to understand what the different techniques are doing and when to apply them, but rarely to the level of depth expected in these white-board interviews that are often just thinly-disguised ways to grill and belittle nervous candidates.

If I could redo my twenties, I would tell myself to choose some topic I cared about, find publicly available data on that topic, and just start exploring the dataset with basic pivot tables and graphs. Ideally write up what you found and publish it somewhere. As you find interesting things in your data you'll naturally start asking more questions and you'll learn modeling techniques as a function of those questions and writing about will help you become a clear communicator (this matters far more than technical knowledge)

I’ve worked in the field for 7 years now so not that long but long enough to build some heuristics. The best data scientists are just people who try to understand the ins and outs of business processes and look at problems with healthy suspicion and curiosity. The ability to explain the nuances of manifolds in SVMs is not something that comes into it outside these contrived interviews. I prefer to ask candidates how they would approach solving a problem I’m facing at that moment rather than these cookie cutter tests which are easy to game and tell me nothing

> Python offers more intuitive memory management than R (which is really more a statement on how bad R is at memory efficiency).

I haven't found that to be the case. Loading a 2gb CSV file when you have 8gb of ram is touch and go with pandas but with data.table it’s a breeze not to mention operations once loaded up are a fair-bit faster. The pythong version has recently been released and already provides a serious speed bump over pandas not to mention out the box memory-mapping for huge files. I recommend checking it out if you haven't heard of it https://h2oai.github.io/db-benchmark/