Stuff just gets done, I guess? Projects move faster, people onboard faster with less intervention, etc. The speedup seems noticeable enough that it doesn’t need precise measuring.
If the speed up is noticeable enough then coming up with a metric should be easy?
I haven’t noticed a speed up in my own org though the feeling of engineers rushing to implementation has become more pronounced. Team members no longer understand what others are doing and siloing has become intense even within my team.
As a disclaimer I haven't read the article, nor do I know much about simulating instruments in particular, but I just wanted to point out that accurately simulating the physics of a musical instrument is most likely still a very difficult problem.
I have no doubt there's been analytical/semi-analytical models around for decades. I mean a program that can take an arbitrary geometry or class thereof with specific materials and simulate the high frequency vibrations and model interactions with the body with high fidelity (not through ad-hoc models) is probably still out of scope of real time simulation.
My point is really that there's often families of models that deal with one thing, from semi-analytical first coded in Fortran in the 80s that can run in milliseconds but is only valid in certain configurations with a low degree of accuracy, to "first principles" simulations that may well require a supercomputer to produce results to a useful degree of accuracy (and not in real time). So, just because you see someone claim they can "simulate X", and then another makes the same claim 40 years later, that doesn't mean they're doing the same thing.
For instance, aeronautics has XFOIL. It's a semi-analytical model first devised in the 80s that computes aeronautics coefficients for a certain class of airfoils (NACA). My understanding is it's a very clever, and industrially significant, piece of code, but ultimately it works in a narrow regime with some heavy simplifications. You can now get results from this in real time on a webpage. A proper CFD calculation to a NACA wing will take in the order of minutes to hours on a workstation (depending on requested precision and settings, e.g. speed of air), and while closer to first principles, it's still using physical simplifications (RANS). So yeah, although nominally people have been "simulating airfoils" for 40 years, the techniques have refined considerably, and will continue to do so (practical LES and, someday, DNS). It might be another century that people are still "simulating airfoils" in ever more accurate (nailing down within the constraints), high fidelity (lifting constraints) and generic ways.
Back to instruments, this is a difficult coupled problem, in fairly high frequencies (high frequencies = more expensive), with possible fluid-structure interactions, not to mention the geometries are fairly complex (to even get a workable mesh to begin with). My uneducated guess is we're still at either semi-analytical, or at the "considerably simplified first principles" stage for this type of problems. Just like DNS, I'm sure you could "just resolve the scales and run it through a simulation with a really tiny time step", and this is liable to be similarly expensive as DNS (million dollar single simulation). Additionally, they have to deal with the human ear, which is perhaps more unforgiving than an error plot on drag or lift. So I wouldn't dismiss news of instrument simulation as stale just because someone made something that produced similar artifacts in the past, as the methods will continue to evolve considerably.
I didn't know (but should have assumed) AI-generated podcasts existed. That's depressing.
I imagined if mankind had the ideal machine, that could automate anything, we would get rid of dull office work and back breaking physical labor, but not the things that are actually enjoyable: sharing with each other, entertaining each other, making art. I imagined a lively world of live performance and creation, since all subsistence work had been taken care of. Instead we might end up in the world of fifteen million merits.
It seems people don't mind letting their minds be hacked by machines that can create the form of what they find enjoyable, if not the substance. But I guess there's always been slop and the public for it. To imagine actual people wasting their limited time on Earth listening to these GPT logorrhea podcasts is truly depressing. The unchemical soma.
What are we even supposed to spend our days doing in this bright future of the AI champions'? Stop automating away the things that give people purpose, tackle real problems instead.
The incentives are at odds. In this capitalist landscape, you create podcasts and blogs (or have them created) to attract an audience which then attracts those fat advertising dollars.
It's superficially true, currently. We've had generative AI for a few years and people are using it to make a quick buck. But even if the world had been taken over by communism, or if the Western Highlands of Papua New Guinea had got imperial ambitions and now we all lived in a gift economy, people would still be using generative AI to gain attention and status. This will work until it wears thin. Thinner.
To take this further, don't LLMs justify lowering the "barrier to attention"; i.e., if it only takes Claude's and not the hacker's eyeballs on the software, won't people find vulnerabilities in custom software for one too?
Besides that, one could easily imagine software created for similar purposes ("make me a file editor") by the same tool or handful thereof (claude and a very small "etc" for completeness) might share similar vulnerabilities, so this kind of broad net might be even cheaper to cast than one might imagine at first.
Yes, GPUs run machine code like CPUs. The toolchain compiles code to machine code that gets executed on GPUs. In the stacks referenced above it's not exactly Python, which is why I used the term Python-ish instead of Python.
Literally the same in Italian, la notte porta consiglio. It's in the Bible, in nocte consilium from the Book of Proverbs, but it's likely to pre-date even that by centuries.
Not an attorney so I don’t know the details but it is definitely possible to leave the US several months in a row on a J1. When I did it (also as postdoc), it was an involved process that escalated to the (vice?)president’s office to get permission so there are clearly questions the university needed to address...
I didn’t have any visibility into it all but what I was told about regarded taxes mainly (since getting paid abroad).
So technically possible but also a tall ask (I didn’t know at the time of asking and my PI went with it).
I then came back and carried on without any immigration issues.
If your country is Italy that might be the case, but groceries are at most 30% more expensive than France, and some are nearly the same price (vegetables). Meat and fish do cost an arm and a leg (100% tax on border crossing).
Meanwhile, median net salary in CH is 5'000-5'500 per month, double to triple its neighbors. So food is actually very affordable.
The food that costs more is the one someone cooked for you, which is logical considering the cook is likely paid more than your engineer (assuming that's your case) salary. But then again, minimum wage Italians are not eating out at the restaurant with any frequency. If you were an engineer in Switzerland instead, you could afford eating out there. The restaurants and terraces are never empty, anyways.
Now, if you want to enjoy a beer in the sun, you can get a 2CHF can at the supermarket and go fire up a barbecue at the lake of Zurich, I see people doing that all the time.
But 1% is on the total held, not on the capital gains, right?
If that's the case, it affects earnings quite a bit. Say your investments beat inflation by 3 percentage points, you're effectively down to 2 percentage points after tax, so a 33% reduction in income.
Yea it was better in the years of extremely low rates. 2020-2022 it was 0.375% of total. Now it's up to 0.888% last year. There's some cases where it might be benefitial to use the "normal" account but for average Joe, not having to track every transaction has generally been very benefitial. And as a result 80-90% of adults own some type of stock either directly or through funds/retirement accounts vs the free market utopia us of 62%.
You'd have to break this down into "archetypes" because like 90% of what you pay for is specific:
- retirement
- healthcare: negligible expense for most young people (for instance, about 80% goes to the 65+ in France)
- unemployment (a little more universal, with some large variations still)
Then there's everything to do with children (from direct subsidies to public schools or kindergarten slots), education (not everyone goes to university, for instance), and other subsidies that are income-dependent (two common ones in France are rent subsidy and a salary top-up for low-but-not-too-low incomes).
Plus, ultimately, 100% of what comes in goes out (modulo administrative costs) at the global scale, so you can't just average this or everywhere looks the same.
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