After I picked up the project again a year later (around 2019ish), I stumbled across OSQP again. OSQP blew both cvxopt and MOSEK out of the water in terms of speed (up to 10 times faster) and quality of the solutions (not as sensitive to bad conditioning). Plus the C interface was quite easy to use and super easy (as far as numerics C code goes) to integrate into my larger project. I particularly liked that the C code has no external dependencies (more precisely: all external dependencies are vendored).
First of all, there is no single accepted definition of "neuromorphic" [1]. Still, as a point in favour of the "neuromorphic systems are analogue" crowd: the seminal paper by Carver Mead that (to my knowledge) coined the term "neuromorphics" specifically talks about analogue neuromorphic systems [2].
Right now, there are some research "analogue" (or, more precisely "mixed signal") neuromorphic systems being developed [3, 4]. It is correct however that there are no commercially available analogue systems that I am aware of. Unfortunately, the same can be said for digital neuromorphics as well (Intel Loihi is perhaps the closest to a commercial product, and yes, this is an asynchronous digital neuromorphic system).
[1] https://iopscience.iop.org/article/10.1088/1741-2560/13/5/05...
[2] https://authors.library.caltech.edu/53090/1/00058356.pdf
[3] https://brainscales.kip.uni-heidelberg.de/
[4] https://web.stanford.edu/group/brainsinsilicon/documents/ANe...
Apple has supported "ALAC" for longer, which unlike FLAC uses only integer math and is therefore less power hungry on mobile devices. You can transcode losslessly between FLAC and ALAC.
[1] https://github.com/astoeckel/libfoxenflac/blob/master/foxen/...
So, given that FOSS---which a large portion of the HN crowd depends on---cannot work without copyright (at least not in its current form), the recent discussions may be less of a surprise.
Of course, for now, cheats like the one featured in the article should be fairly easy to detect (at least from what I've seen in the linked video). The motion of the bot is extremely jerky; a simple rule-based system, or, if you want to be fancy, a neural network based anomaly detection system should be able to detect this.
On the side of the cheat authors, this could be easily circumvented if they include a "calibration phase", where user input trains a simple neural network to stochastically emulate the dynamics of the user's sensor-action loop. The cheat could then act slightly faster than the user, giving them an edge while still using their unique dynamics profile.
I wonder where this will lead eventually, and I genuinely feel sorry for all the people who pour their heart and soul into competitive gaming; I don't think that this kind of cheating is something that can and should (see above) be prevented in the long-run. The best possible outcome I can imagine is that online gaming becomes more cooperative or once more converges back to small groups of people who know and trust each other.
[1] https://en.wikipedia.org/wiki/Analog_hole
Edit: Spelling, grammar, and clarity
I used to have such a bridge (OpenWrt on Netgear WNDR3800 hardware) Velcro'd to the underside of a TV cart, so that an appliance on the cart that only had Ethernet and 2.4 GHz WiFi built-in could do a more reliable 5 GHz across the room.
Edit: From what I can tell, support for WDS depends on the WiFi chipset. "iw list" must explicitly include "WDS" as a "supported interface mode". At least the Broadcom chipset on the Raspberry Pi Zero does not support this, but, for example, the Atheros chipsets used in a variety of routers do.
Wikipedia solves a but isn't great for b or c.
Unfortunately, the project has never really taken off, and only few new articles have been added over the past few years. And of course, just as I am writing this comment, I realize that [2] now redirects to some domain squatter and is blacklisted by my DNS server...
[1] https://sr.ht/~lattis/muon/