With respect to tire pollution, buses are far less bad than cars. Providing a bus is not nearly empty, while the per-vehicle pollution is worse than a car, it's per-passenger pollution is much less.
If only it did. AI is designed to do what you tell it to, and that mostly works. But in the general case, AI does what it does, with no real guarantee of anything.
LLMs seem to have been fine-tuned to use metaphors, presumably because they read like vivid creative writing. The over-use of metaphor in LLM-produced text is exhausting.
Should chips like the Jetson Orin module be regarded as dual-use technologies? Or have similarly powerful embedded processors now become widely enough available that it isn't worth making the distinction any more?
He's right, of course, for those people who already have a mathematical gift, but the problem with that is that Tao has never experienced not being a mathematical genius, and is no more capable of understanding what it's like to not be a genius as an ordinary person is capable of understanding what it's like to be one.
I found the use of <SYMBOLS LIKE THIS> throughout the text without explanation somewhat off-putting. Clearly some sort of technical usage is being suggested, but it doesn't seem to add anything to the text.
This is a romantic and very appealing idea that flies in the face of reality. The market for skilled trade workers like plumbers, electricians, landscapers and so on is more or less in equilibrium, and the demand side of it is relatively inelastic. Dumping hundreds of millions of new workers into these trades will not increase demand sufficiently to let anyone earn a viable living from them.
There is nothing that can absorb millions of new workers. If AI destroys jobs to that degree pitchfork manufacturers will be the only ones left in business.
Where I live at least right now it is quite hard to find contractors for anything and many are close to retirement age and have a hard time finding replacements.
There's also the thing where trade work is in the process of pricing itself out of what normal folks are willing to afford. Combined with Youtube tutorials and AI help that is getting better, it wouldn't surprise me if more and more people would just decide to do all this stuff themselves at a fraction of the cost.
Yeah, I feel DIY is definitely on an upswing. There's surprisingly decent info, tools and parts for cheap to be found. And materials are getting simpler to work with.
There are still things that will remain difficult (or illegal) in domestic settings for DIY, of course, but that's no model for full employment.
I haven't got any experience with them but there's even vendors for house assembly kits that cost a fraction of a finished one. Imagine you idiot-proof house planning and building: just do exactly what the app says.
I wonder just how far we have to push this until we finally get the 10h work week.
250 MB is exactly the sort of bloat you'd expect from this sort of daft web-browser-wrapper application, and Apple get it there. 1.2 GB, on the other hand, is 5x as much, and completely insane even when you start off with daft as your starting point.
Apple weather is fully native from what I understand. I suspect the 250MB comes from the video backgrounds they play. Arguably that would be a reasonable thing to sacrifice on low memory systems, you'd barely notice.
- ~34-40 MB of memory as general heap memory that was otherwise unaccounted for (this seems to mostly be stack memory and threading-related stuff, and the actual application logic)
Nice find and summary. Of I'm not surprised to see the ~75MB for the high graphical fidelity of the app.
I am however surprised that 10MB is Swift language runtime - with ABI compat this is supposed to be shared, and that the weather daemon is >6MB (surely this is just a simple API client?!).
Oh yea, something worth mentioning is that my analysis did not consider what memory was shared or not. That might influence the actual numbers. I believe the amount of memory used by the weatherd daemon also includes code and not just the heap memory, so the libraries that weatherd loads would be included in that.
I think this depends on perspective. Compared to an Electron app, it's significantly better. Compared to a hand-optimised app implemented in a low level language it's not great.
I've not done a lot of Swift/iOS/macOS, but I have a passing familiarity. These numbers are basically what I'd expect for a normal app. In other words I think the relative optimisation comes from the fundamentally better technology choice rather than from being particularly careful about performance.
Yea this is what I meant. I guess a more accurate phrasing would be "feels reasonably optimized." Qualitatively in terms of (lack of) graphical stutters and whatnot the macOS one feels very smooth.
I wonder if the same is also true of other high-spatial-complexity activities like rock climbing and professional dancing? (Exercise level would of course be a counfounding varable to be eliminated in these cases.)
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