• 2 Posts
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Joined 3 years ago
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Cake day: July 5th, 2023

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  • I think it’s worth being clear about the scope of the rating. iFixit has always been about repairability defined by parts availability, and its ratings consider software restrictions only to the point where it interferes with the user experience when replacing parts to restore things to the original performance.

    Customizability (in software or otherwise) isn’t part of the score. Durability/longevity isn’t part of the score, either. Those are things that I want, too, but I can recognize those are outside the scope of what iFixit advocates for.

    I do have some concerns about the partnerships creating a conflict of interest, but sometimes that feedback loop is helpful for improving the product, where the maintainer of a standard also has a consulting business in helping others meet that standard. Ideally there’s a wall between the two sides (advisors versus raters), but the mere fact that one company might do both things isn’t that big of a deal in itself.




  • Using a simple flip phone with no app ecosystem would fix this, right?

    Probably not.

    The cell phone network will need to know where every subscribed phone is, in order to be able to route simple phone calls and text messages. In the old days, that might have meant very broad ideas of which areas were covered by which towers (often divided into 3 slices of 120° each from a single physical tower), and maybe some timing data to understand how much to offset the signal timing to make up for the speed of light.

    But each generation of cell phone technology has been about adding more capacity into each wireless frequency, and the towers have specialized tricks for transmitting and receiving on the same channel at the same time with different devices, by getting more precise about transmitting or listening in very specific directions and distances, with spatial signatures that distinguish between devices. It’s all very cool and mathematically beyond my understanding, but the result is that the towers have much more precise location data about the actual handsets.

    So the cell phone companies have your location data. The question becomes whether they sell them to location aggregators who resell the data on the open market, and whether some of the buyers of that data are law enforcement agencies without a warrant.





  • Yeah. AI is really good at generating footage and stills for these infrared night vision types of surveillance cameras, in large part because they don’t need to be high resolution and are in black and white.

    Because of the way they’re trained on cats and deer have eyes that reflect light back at the camera, these generated images also tend to give that effect even to animals (like humans) that wouldn’t have as pronounced of that effect.


  • Unintuitive locked down garbage that can’t do anything a PC can’t do for half the price.

    From the user perspective, enterprise managed Windows is locked down, too, and somehow less reliable.

    Most of the software engineers I know in FAANG and similar tier companies use Macbooks to program. Poke around a coffee shop in the bay area during a weekday and look around.

    And personally, I switched to Mac about 15 years ago mainly because dependency management and the shell made more sense to me coming from Linux. Windows has always been trash, and most other non-Apple OEMs make the actual physical laptop experience worse (hinges, behavior on closing the lid, trackpad behavior and size, power management, display quality in both brightness and pixel density, webcam/audio behavior).





  • Yes. There were plenty of people saying “but this business doesn’t have a path to making more money than it spends.” There was, at the time, serious doubt about internet advertising as a viable business.

    And the companies building out the telecommunications infrastructure. Between the 1996 reforms creating a lot of redundant competition for competing telecommunications networks, mania about the information superhighway, there was basically never going to be a way for these companies that spent billions deploying real resources in creating telecommunications lines to make enough money to even make their interest payments. So they mostly went bankrupt and their assets got sold to others at a fraction that it cost to build them.

    Warren Buffett sat the whole thing out and his portfolio significantly underperformed the market as a whole. His philosophy of only wanting to invest in companies that he saw as undervalued, with a low price for their earnings or dividends or general enterprise value, didn’t work really well for the prevailing investor sentiment at the time.



  • You can reason from a few principles:

    • At its core, the math functions being optimized by these AI tools and their specialized hardware is that they can perform inference and pattern recognition at huge scales across enormous data sets.
    • Inferring a rule set for pattern also allows generation of new data that fits that pattern.
    • Some portion of human cognitive work falls within the general framework of finding patterns or finding new data that fits an old pattern.

    So when people start making claims about things with clear, objective definitions (a win condition in chess, the fastest route to take through a maze, a highest lossless compression algorithm for real world text), it’s reasonable to believe that the current AI infrastructure can lead to breakthroughs on that front. So image recognition, voice recognition, and things like that were largely solved a decade ago. Text generation with clear and simple definitions of good or bad (simple summaries, basic code that accomplishes a clearly defined goal) is what LLMs have been doing well.

    On things that have much more fuzzy or even internally inconsistent definitions, the AI world gets much more controversial.

    But I happen to believe that finding and exploiting bugs or security vulnerabilities falls more into the well defined problem with well defined successes and failures. So I take it seriously when people claim that AI tools are helpful for developing certain exploits.


  • but isn’t the memory on the Neo on the same die as the processor?

    Not actually on the same die, but in the same package, stacked on top using TSMC’s Integrated Fan-Out Package on Package (InFO-PoP).

    So the memory still needs to be sourced from memory manufacturers, sent to TSMC, and then have TSMC package it all together in a single package. It’s unclear whether they had locked up this supply at pre-AI prices, though. The underlying A18 Pro chip/package was annoinced and launched about 18 months ago, so if they had the manufacturing pipeline set up for that they might have kept the contractual rights to continue buying memory at the old prices.




  • On the flip side, I’m a former sysadmin and I only stick around for 5 years because I had the educational credentials to move onto another field (and then another field). I’m glad I did the IT thing in my 20’s, and still like to tinker with homelab stuff 20 years later, but in the end it was a stepping stone towards something else (that does require formal schooling). The degree is a tool that can be used to control on a few more things in your life, in the hopes that you can go where you want to end up.