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Cake day: June 15th, 2023

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  • Once users have given up on comfortable single-handed use, the only limiting factor is pocket size.

    For me, that means once it passes about 65mm in width, I might as well jump to ~80mm in width, which is huge even by today’s standards. 70mm wide phones are just the worst of both worlds to me.

    I want a small phone, but there hasn’t been a serious option in over 10 years. The Xperia Z3 Compact was the last good “small” Android phone that was actually small enough to justify its existence. That was 2014.

    Edit: Also, I suspect with bezels being so small now, the frame would need to be even smaller to avoid accidental edge presses with one-handed operation.



  • If you’re willing to pay money for it, you can get your own domain for $2-$15 per year, then use it with pretty much any commercial email service. That way you can change email providers without changing your address.

    This is my plan going forward. I’m going to suffer the inconvenience of changing my address, but only one more time, not every time I want to change providers.





  • If you think this isn’t related to human rights, then you’ve missed the point.

    People have the right to use technology, and indeed we effectively need technology to exercise our right to free speech. You cannot have one without the other. Not anymore.

    The right way to think about this that they are arbitrarily banning a topic of discussion simply because it is not dead-center average. This isn’t even a legal issue, and the justification is utter nonsense (Facebook itself runs on Linux, like >90% of the internet). No government has officially asked them to do this, though the timing suggests that it is unofficially from the Trump administration.

    This is about exerting control, establishing precedent, and applying a chilling effect to anything not directly aligned with their interests. This obviously extends to human rights issues. This is a test run.



  • Yeah. If you want to be on the cutting edge of storage, look for a mobo that has PCIe gen5 m.2 slots. But really, PCIe gen4 m.2 drives are still pretty darned fast. You can get some with >7GB/sec transfer rates. Do you need >12GB/sec transfer from disk? Probably not. Is it cooooool? Sure. :)

    This is a popular SSD these days, very good for the price: https://us-store.msi.com/PC-Components/Storage-Devices/Solid-State-Drive/M482-NVMe-M2-2TB-Bulk . If you want something high-end, look for an SSD with DRAM cache. Useful if you’re writing massive amounts of data regularly, like video mastering or something like that, generally overkill otherwise.

    I’ve been on the Ryzen x700 line for a long time now, first the 1700 and now on the 7700. No complaints, they rock. So I’d start by looking at the 9700. 9900 has more cores (and uses significantly more power), 9600 has fewer cores. Single-core performance is basically the same across the board, so it just depends on whether your workload can use a lot of cores or not. The “X3D” chips have additional CPU cache that supposedly improves performance in some workloads (notably in gaming). So if that’s important to you, the 9800X3D is the natural choice.


  • Fortunately, my worn is not LLM related but just simple neural networks, but I don’t know how that might affect best practices for hardware.

    Okay. If this is something you already do on existing machines, you’ll be in good position to know how much memory you actually need, and then maybe give yourself a little room to grow. My guess would be that you’re not working on massive models so you’ll probably be fine with a mid-range card.

    At the same time, a lot of AI/ML stuff is becoming mainstream and requires a ton of VRAM to get good performance. If you do any work with graphics, audio, or video, you might find yourself running large models without really thinking about it. There are lots of use cases for speech recognition models, for example, which are quite large. Photoshop already has some medium-sized models for some tasks. Noise reduction for audio can also be quite demanding (if you want to do a really good job).

    As for system RAM…the world of DDR5 is indeed complicated. I don’t think there’s a huge need to go over 6000MHz RAM, and faster RAM brings some compatibility issues with some mobos/CPUs. It’s also usually faster to use two sticks than four. So 2x32GB would be better than 4x16 in general.

    For GPUs in particular, new gens with more VRAM are on the way, so buying the high-end now might leave you with something that feels obsolete by the time you grow into it. If you spend $750 now and $750 again in 2-3 years, you might end up better off than if you spent $1500 today and waited twice as long to upgrade. Particularly if you are able/willing to sell your old equipment to offset upgrade costs.


  • VRAM is king for AI workloads. If you’re at all interested in running LLMs, you want to maximize VRAM. RTX 3090 or 4090 are your options if you want 24GB and CUDA. If you get a 4090, be sure you get a power supply that supports the 12V HPWR connector. Don’t skimp on power. I’m a little out of the loop but I think you’ll want a PCIe 5.0 PSU. https://www.pcguide.com/gpu/pcie-5-0-psus-explained/

    If you’re not interested in LLMs and you’re sure your machine learning tasks don’t/won’t need that much VRAM, then yes, the 4070 Ti is the sweet spot.

    logicalincrements.com is aimed at gaming, but it’s still a great starting point for any workload. You’ll probably want to go higher on memory and skew more toward multi-core performance compared to gaming builds, IMO. Don’t even think about less than 32GB. A lot of build guides online skimp on RAM because they’re only thinking about gaming.


  • But any 50 watt chip will get absolutely destroyed by a 500 watt gpu

    If you are memory-bound (and since OP’s talking about 192GB, it’s pretty safe to assume they are), then it’s hard to make a direct comparison here.

    You’d need 8 high-end consumer GPUs to get 192GB. Not only is that insanely expensive to buy and run, but you won’t even be able to support it on a standard residential electrical circuit, or any consumer-level motherboard. Even 4 GPUs (which would be great for 70B models) would cost more than a Mac.

    The speed advantage you get from discrete GPUs rapidly disappears as your memory requirements exceed VRAM capacity. Partial offloading to GPU is better than nothing, but if we’re talking about standard PC hardware, it’s not going to be as fast as Apple Silicon for anything that requires a lot of memory.

    This might change in the near future as AMD and Intel catch up to Apple Silicon in terms of memory bandwidth and integrated NPU performance. Then you can sidestep the Apple tax, and perhaps you will be able to pair a discrete GPU and get a meaningful performance boost even with larger models.


  • This will be highly platform-dependent, and also dependent on your threat model.

    On PC laptops, you should probably enable Secure Boot (if it’s not enabled by default), and password-protect your BIOS. On Macs you can disable booting from external media (I think that’s even the default now, but not totally sure). You should definitely enable full-disk encryption – that’s FileVault on Mac and Bitlocker on Windows.

    On Apple devices, you can enable USB Restricted Mode, which will protect against some attacks with USB cables or devices.

    Apple devices also have lockdown mode, which restricts or disables a whole bunch of functionality in an effort to reduce your attack surface against a variety of sophisticated attacks.

    If you’re worried about hardware hacks, then on a laptop you’d want to apply some tamper-evident stickers or something similar, so if an evil maid opens it up and tampers with the hardware, at least you’ll know something fishy happened, so you can go drop your laptop in an active volcano or something.

    If you use any external devices, like a keyboard, mouse, hard drive, whatever…well…how paranoid are you? I’m going to be honest: there is a near 0% chance I would even notice if someone replaced my charging cables or peripheral cables with malicious ones. I wouldn’t even notice if someone plugged in a USB keylogger between my desktop PC and my keyboard, because I only look at the back of my PC once in a blue moon. Digital security begins with physical security.

    On the software side, make sure you’re the only one with admin rights, and ideally you shouldn’t even log into admin accounts on a day-to-day basis.





  • Typically, I use a slow-charger overnight (a plain ol’ USB type-A charger, which I think means 5W max), then top-up as needed during the day with USB-PD fast chargers. I generally do not top up to 100% during the day. I have adaptive charging enabled in settings.

    That said, I’m a heavy phone user, and I’ve never had a phone that reliably lasts me a full day. According to aBattery, my current phone is at 750 charge cycles, which is just about 1 per day since I bought it. I’m not up to date on all the latest developments in battery tech, but I think it’s normal for a battery to drop to 80% of its original max charge after 500 cycles. I don’t think I have a dud on my hands, just an ordinary battery that is aging as expected. Like I said, it’s still “fine”. It hasn’t started unexpectedly shutting off or anything like that.

    I still have my old Pixel 2 (now 7 years old) that I occasionally use as a wi-fi device. I used that phone heavily for 2 years and very lightly for the remaining 5. I’m lucky if the battery lasts half an hour at this point; it’s basically a desktop device now.



  • vd (VisiData) is a wonderful TUI spreadsheet program. It can read lots of formats, like csv, sqlite, and even nested formats like json. It supports Python expressions and replayable commands.

    I find it most useful for large CSV files from various sources. Logs and reports from a lot of the tools I use can easily be tens of thousands of rows, and it can take many minutes just to open them in GUI apps like Excel or LibreOffice.

    I frequently need to re-export fresh data, so I find myself needing to re-process and re-arrange it every time, which visidata makes easy (well, easier) with its replayable command files. So e.g. I can write a script to open a raw csv, add a formula column, resize all columns to fit their content, set the column types as appropriate, and sort it the way I need it. So I can do direct from exporting the data to reading it with no preprocessing in between.