daviddever23box

You may want to read up on industry best practices for theatrical sound mixing and digital cinema delivery.

It's not; there is a nominal series of standards for this.

If you haven't used a more current programming language in terms of tooling, you may be in for a shock: package management, concurrency, formatting and linting are all sorted, with decent support in Visual Studio Code. I'd honestly look at these things first so that you can right-size individual modules, etc.

There is a reason for "obsoleting" these Intel-based Macs - they're simply too slow for the average user with Apple and other services enabled. Disable iCloud, Spotlight, MS Office auto-update and other cloud storage services and one has a chance at a (mostly) useful machine, up to a point.

With some hardware skills, one can upgrade / replace the internal storage, though this only goes so far.

Problem is, there are newer, cheaper and better devices with faster storage and higher memory bandwidth, so the market on more recent (non-obsolete or non-vintage) Intel Macs holds steady (for legacy compatibility purposes), while anything that lacks Thunderbolt 3 / USB-C ports becomes a liability.

The last time I saw this was during the transition to Intel chips: PPC G5-based devices fell off the face of the earth within a couple of years, with older G4s holding up the rear for legacy (Mac OS 8.x/9) compatibility. It's a plateau.

Always be three steps ahead when it comes to constraints of time / money / available space / intellect. If you ration your resources correctly, you will be far ahead of anyone else.

The on-premise compute (server) market doesn't offer anything unique for Apple to contribute; they are themselves, purportedly, continuing to use quite a bit of white-box and third-party branded compute, with Linux as one of the OSes. (Disclaimer: I have not stepped into an Apple-owned data center anytime within the last six years, so any of this may be subject to change, which itself might be very interesting!)

As for the on-premise workstation market, this is long rumored to be shrinking, leaving the Dell-HP-Lenovo (DHL) triad to the spoils for Linux or Windows on commercial PCs. That dominance yields when remote / BYOD enters the fray (as Microsoft 365 and Google Docs run nearly anywhere).

Yes - and it is certainly possible to export the "final", up-to-date set of drivers via DISM, then build an orthogonal set that you can recursively install via a single one-click pnputil batch file in Audit Mode (Ctrl-Shift-F3 at the top of OOBE).

This is the easiest way to validate benchmarks across neutral, bloatware-free OS versions (at least the ones supported by that SoC, anyway).

Check your DNS server settings!

Could it simply be that much of the "creator" technical content, as with Medium, is simply state-the-obvious level drivel?

Listen to the data that you're migrating from one system to another, so to speak. Test v1-to-v2 and v2-to-v1 migrations until you're blue in the face. Feature-flag migrations for individual clients. Ensure that any SLAs are met with v1-only, v1-in-flight-to-v2, v2 only, and/or some mix of static partial migration. Make sure that you have an absolutely homeomorphic mapping of data from one representation to another.

DISCLAIMER: this list is x64-centric, and your results may vary under arm64 environments.

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PACKAGE AUTOMATION

- Windows Package Manager "winget" command-line tool (winget.exe): https://github.com/microsoft/winget-cli

On both Windows 10 and 11, every application and system package on my devices gets batch-installed, as winget import --import-file {{JSON-file}}, when possible. One can also export a list of installed packages for automation purposes.

Winget is shipped as a component of the App Installer package, which is supplied by default under Windows 11 but is an optional installation for Windows 10.

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DRIVER AUTOMATION

- Deployment Image Servicing and Management (DISM.exe): https://learn.microsoft.com/en-us/windows-hardware/manufactu...

I use this a lot, as dism /online /export-driver /destination:{{output-directory}}, mainly to manage exported driver packages post-Windows Update that are subsequently cherry-picked (latest active, installed version only), stored on a USB-C thumb drive, and pre-installed into a neutral OS (in Windows Audit Mode, using Ctrl-Shift-F3), via PnPUtil, for clean-machine testing.

- PnPUtil (PnPUtil.exe): https://learn.microsoft.com/en-us/windows-hardware/drivers/d...

As an example, I leverage the exported driver packages from above to one-click install them via a one-line batch command (in Windows Audit Mode, using Ctrl-Shift-F3 on first launch) for neutral-installation, clean-machine testing.

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Automation is key to getting things done, and reproducible environments are a necessity, especially when performing regression testing across various Windows OS build versions.

The combination of DISM and PnPUtil is now fast enough that I actually no longer bother using WinPE to capture and flash system images, or setting up DISM to inject the drivers into an existing image. Time is money and personal sanity.

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SCREEN CALIBRATION

- DisplayCAL: https://github.com/eoyilmaz/displaycal-py3

Every display panel I own (whether portable, laptop, all-in-one desktop, 4K monitor or other) gets a clean-room measurement under daylight (5000K) lamps with an X-Rite i1D3HL OEM colorimeter (e.g., CALIBRITE ColorChecker Display, et al), generating an ICC profile that can then be loaded into Windows Color Management at any later date.

Color calibration makes a huge optical quality-of-life improvement, with the occasional use of an adaptive grey-scale filter (to minimize color distraction, as well as to verify grey-scale compatibility and contrast) a close second.

This repo accommodates the changes required to run with Python 3 support.

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DIAGNOSTICS

- REALIX HWiNFO: https://www.hwinfo.com/

HWiNFO provides "more info about your computer than you'll ever need", which is nonetheless incredibly useful. I've been using this for years.

Oddly enough, the fact that you want to work for a FAANG company might make you less attractive as a candidate, though don't let that dissuade you from applying.

Secondly, front-end development from a pure programming perspective is less stable (with the rise of AI-assisted development) than the ability to communicate with stakeholders; you may have a superpower that you are in fact under-selling.

Open-source projects are probably your best opportunity to demonstrate your skillset, with NDA-free client projects your second-best opportunity.

Seriously, I think this is way off-base; the job of a software engineer (not a "programmer") is to distill problems that are both technical (bits) AND psychological (Bobs and Barbaras) into a reasonable, reproducible solution that can be subsequently improved upon and maintained. Most days, it's the latter that's the real work.

ChatGPT is, on one level, a fancy form of Google search: you still need to know how to leverage the prompts in order to make decent progress, and it's based on knowledge (correct OR incorrect) that was originally generated by a human, one of whom must still evaluate as to whether or not the outputs are relevant to the task at hand.

There's a whole branch of philosophy dedicated to this, by the way, that deals with the knowledge lifecycle: how concepts come to be, how they are reinforced socially, and then discarded when no longer relevant. The same lifecycle applies to the data pools used for training "old" models.

News agency-style journalism is an easy target, as its primary role is to aggregate and convey information from multiple sources to the reader in a nominally unbiased, dispassionate fashion. Learned language models are ideal for this; it's a style manual wrought large.

As for developers–we've had automated code generation for decades. And machine learning has been a part of investment data analysis for a long time.

Why the fear, uncertainty, and doubt? Are you creeping closer to death?

Coming from both environments, I'd be wary of making some of these assertions, especially when you consider that any ecosystem that optimizes software and hardware together (from embedded devices all the way to general-purpose computing machines) is generally going to perform well, given the appropriate engineering focus. This applies regardless of (RT)OS / hardware choice, i.e., it's simply common sense.

The signing of binaries is a part of adult developer life, and is certainly required for the platforms you mention as well.

Unquestionably, battery life on 4090-based laptops sucks on a good day, and if you're working long hours, the last thing you want to have to do is park yourself next to your 350W adapter just to get basic work done.

It is, provided that the hardware vendor has reasonably decent support for power management, and you're willing to haul around an AC adapter if not. In general, I really like AMD hardware with built-in graphics for this, or alternately, Intel Tiger Lake-U based hardware.

Asahi Linux is shockingly great on Apple Silicon hardware, though.

It seems that you're trying to "educate" me on how containers and virtualization work, when in fact I've been doing this for a while, on macOS, Linux and Windows (itself having its own Hyper-V pitfalls).

I know you mean well, though.

There is no Docker on macOS without a hypervisor layer - period - and a VM, though there are multiple possible container runtimes not named Docker that are suitable for devops-y local development deployments (which will always, of course, be constrained in comparison to the scale of lab / staging / production environments). Some of these can better leverage the Rosetta 2 translation layer that Apple provides, than others.

Remember, though, that the binaries deployed in production environments are not being built locally on individual developer machines, but rather in the cloud, as reproducible builds securely deployed from the cloud to the cloud.

Modern language tooling (Go, Rust et al) allows one to build and test on any architecture, and the native macOS virtualization (https://developer.apple.com/documentation/virtualization) provides remarkably better performance compared to Docker (which is a better explanation for its fading from daily use).

Your "trend" may, in fact, not actually reflect the reality of how cloud development works at scale.

And I don't know a single macOS developer that "lean(s) on the team member who is on Linux" to leverage tools that are already present on their local machine. My own development environments are IDENTICAL across all three major platforms.

That ASUS laptop seems like a decent budget device, provided that shortened battery life is not an issue.

No window-dressing for legacy package formats!

You need to know how the donuts are made before you can speak about optimizing the size of the hole.

Try pivoting to MLOps, where you can get a taste of systems programming plus a bit of high-level machine learning.

Books? https://source.android.com/docs/security/features/selinux

Might be an excellent opportunity to re-think how we handle timekeeping in general, especially as Local Solar Time will vary wildly by dint of the moon's orbital patterns.

Work remotely in a city for which the cost of living is low.

Wouldn't dealing with an outside consultancy firm be considered a low-value, mundane task?

Folks feel the same way about Markdown versus LaTeX: why use something significantly more complicated where a looser, human-readable grammar works better?

For any other situations, I use https://pandoc.org/, or, generate a Word doc scriptomatically.

Don't bother - it's not worth it.

It's all fun and games until someone modulates their AC mains feed with a deterministic pattern.

You could have said "influencer" or "fashionista" and conveyed the same degree of usefulness.