Maybe this is just my backend/network focus with Golang though. Scaling beyond 10-15k lines of code always was quite intimidating as it is usually where I lose the ability to just keep a model of the codebase fully in my head.
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Maybe this is just my backend/network focus with Golang though. Scaling beyond 10-15k lines of code always was quite intimidating as it is usually where I lose the ability to just keep a model of the codebase fully in my head.
However when I setup Windows it wiped my TPM keys for LUKS so maybe there is a potential conflict there.
But the CEO in the intro just seems like an odd choice. PFAS were known to cause issues for a long time, if you continued to use them for years then it is in your back too.
Being "surprised" this might eventually affect your own product line just seems naive. You might have trusted 3M but just blindly trusting a supplier is not an excuse at some point.
In my setups it just was easier to use fixed paths (or relative to project dir) from a permissions management perspective. Backup tools did not always have to/should run as root which is helpful on machines providing multiple distinct services.
Putting borg or a similar tool in a container that is part of the compose manifest file can also help. I haven't seen this used in practice though yet.
Docker volumes (and bind mounts) however have the minor problem of being hard to get a consistent copy to without stopping the service. You can work around this by, e. G., having ZFS or btrfs as the underlying FS and making a snapshot there. Otherwise, your software (like PostgreSQL) might also have other online backup tooling.
That means they are sometimes economically incentivized to choose an option with lower initial cost but a higher running cost. Governments can/do bend these incentives via taxes but it can be hard/expensive to renovate old complexes (and that part cannot directly be offloaded by the landlord).
One could blame the user for not "just" holding it right. Or alternatively reconsider if the handle should have a grippy coating instead.
(and as a side-note, the in-kernel driver also has some problems. Ime, it sometimes dropped one of my nics for no apparent reason until the next reboot. It is better than the out of tree one though)
There are better learning resources and a better ecosystem available around Nvidia cards & software (cuda).
Long answer, it depends. It will add more challenges and require significantly more effort (even outside the GPU programming itself, debugging toolchain etc. is a somewhat separate skill). The smaller/less mature ecosystem also means you will have less examples to look at for references.
I don't like Anti-Cheat solutions with elevated privileges but they have (at least for some time) reduced the number of Cheaters in games like Valorant or BF, for most users this is at least a somewhat understandable tradeoff. Denuvo on the other hand is DRM and a pure tradeoff in favor of the publisher at the cost of the consumed.
You can read more about it here: https://isabelle.in.tum.de/dist/doc/sledgehammer.pdf
The language is different (not necessarily better) in comparison to Lean, but I do agree with some of the points on dependent types. It seems both languages mostly just made different tradeoffs, which imo, were fair and have shaped them into quite efficient tools for their domains. The domain of "proofs" is large and different paradigms just have different strengths/weaknesses, Lean just specialized for a different part of this space.
Sledgehammer is nice but probably just a question of time until an equivalent can be ported/created for Lean. It might also be nice to use for explorative phases but is a resource hog, it also makes proofs concise but I would usually rather see the full chain of steps directly for a proof in the published code instead of a semi-magic "by sledgehammer".
Working on Isabelle itself however is painful (especially communicating with developers) in comparison to Lean. Things like "we don't have bugs just unexpected behaviour" on the mailing list just seems childish/unprofessional. The callout to RAM consumption of Lean and related systems is also a bit of joke when looking at Isabelle's gluttony for RAM.
Finding a successor is also not easy nor cheap (in regards to time).
This can done with carve outs/ gaps for public service buses, a somewhat cheap implementation are Pop-Up bikelanes but concrete barriers of 10-15 cm also do the job well.
Because (relatively) small teams can act faster. It is also a lot easier to have a small, motivated core group with shared objectives and aligned vision of a project. A non-profit/public benefit entity is also a reasonable host for such an effort. Such projects can also tap into public money (under particular circumstances) via the various EU and national grant schemes.
> Just have it be an official EU government backed identity.
The amount of baggage this would entail is quite large. Besides just bureaucracy you almost certainly would then also invite politics even more, because, even for small projects, the next question will be: In what countries is the service hosted and by which agency/developers?
That is besides the almost inevitable inefficiencies for resource usage and other obligations from being associated with public funds (which can require a LOT of internal politics work to acquire and especially retain).
The commenter above argued that the problem was slightly different, it's not too many meetings for communication but too many that are not achieving effective communication. A meeting in itself does not create communication (of information and exchange of opinions etc.) and the commenter wanted to increase the number of meaningful meetings instead of/in addition to just cutting down meetings by numbers. The criticism of not enough time spent on communication is in the same vein, both agree on the issue of "too many unnecessary meetings".
A smaller builder might reconsider (re)acquiring relevant skills and applying them. We don't suddenly lose the ability to program (or hire someone to do it) just because an inference provider is available.
Their role is to stop the train in an emergency and adjust to speed etc. to track/driving conditions.
Automating their job probably wouldn't even need the complex ML used for self-driving because the context is significantly simpler and relatively well defined. Maybe a team in city might need such a model but it would still be a significantly simpler task than driving a car.