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Joined 1 year ago
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Cake day: August 4th, 2023

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  • You have to search using language that papers might actually use though. “Parachute effectiveness” means what the satirical paper is exploring, whether it prevents death or not. The only serious studies that might have used that language would be old WW2 studies that threw people out of planes with different parachutes to see how many survived.

    If you want to know how to design an effective parachute, you should be looking at reference books like Parachute Recovery Systems instead.


  • No, the “non-fungibility” simply means that anyone who creates an NFT with the same link will be distinct from your link to the image, even if the actual URL is the same. Both NFTs can also be traced back to when they were created/minted because they’re on a blockchain, a property called provenance. If the authentic tokens came from a well known minting, you can establish that your token is “authentic” and the copy token is a recreation, even if the actual link (or other content) is completely identical.

    Nothing about having the “authentic” token would give you actual legal rights though.


  • Billion dollar costs aren’t rounding errors even at YouTube/Google’s scale. They’re a measurable percentage of total revenue. I agree that it slightly improves the user experience, it’s hard to imagine a worse cost/benefit tradeoff from an engineering perspective even at more realistic costs. It’s especially hard to justify when there’s an easy alternative for users in the form of downloading videos.




  • No. Nvidia will be licensing the designs to mediatek, who will build out the ASIC/silicon in their scaler boards. That solves a few different issues. For one, no FPGAs involved = big cost savings. For another, mediatek can do much higher volume than Nvidia, which brings costs down. The licensing fee is also going to be significantly lower than the combined BOM cost + licensing fee they currently charge. I assume Nvidia will continue charging for certification, but that may lead to a situation where many displays are gsync compatible and simply don’t advertise it on the box except on high end SKUs.






  • TCP has been amended in backwards incompatible ways multiple times since 1993. See e.g. RFCs 5681, 2675, and 7323 as examples.

    Plus, speaking TCP/IP isn’t enough to let you to use the web, which is what most people think of when you say “Internet”. That 1993 device is going to have trouble speaking HTTP/1.1 (or 1.0 if you’re brave) to load even the most basic websites and no, writing the requests by hand doesn’t count.




  • I haven’t explained what the differences are because almost everything is different. It’s like comparing a Model T to a Bugatti. They’re simply not built the same way, even if they both use internal combustion engines and gearboxes.

    Let me give you an overview of how the research pipeline occurs though. First is the fundamental research, which outside of semiconductors is usually funded by public sources. This encompasses things like methods of crack formation in glasses, better solid state models, improved error correction algorithms and so on. The next layer up is applied research, where the fundamental research is applied to improve or optimize existing solutions / create new partial solutions to unsolved problems. Funding here is a mix of private and public depending on the specific area. Semiconductor companies do lots of their own original research here as well, as you can see from these Micron and TSMC memory research pages. It’s very common for researchers who are publicly funded here to take that research and use it to go start a private company, usually with funding from their institution. This is where many important semiconductor companies have their roots, including TSMC via ITRI. These companies in turn invest in product / highly applied research aimed at productizing the research for the mass market. Sometimes this is easy, sometimes it’s extremely difficult. Most of the challenges of EUV lithography occurred here, because going from low yield academic research to high yield commercial feasibility was extremely difficult. Direct investment here is almost always private, though there can be significant public investments through companies. If this is published (it often isn’t), it’s commonly done as patents. Every company you’ve heard of has thousands of these patents, and some of the larger ones have tens or hundreds of thousands. All of that is the result of internal research. Lastly, they’ll take all of that, build standards (e.g. DDR5, h.265, 5G), and develop commercial implementations that actually do those things. That’s what OEMs buy (or try to develop on their own in the case of Apple modems) to integrate into their products.


  • You have no idea how modern technology is produced. Any particular product is usually the result of dozens to thousands of iterations, some funded with public money and many not. Let’s take an example from your chart: DRAM. I actually don’t know when DARPA “developed” DRAM (since DARPA usually funds private companies to do development for them), but it must have been before 1970 when Intel designed the 1103 chip that got them started. Do you think that pre-1970s design is remotely similar to the DRAM operating on your device today? I’ll give you a hint: it’s not.

    And no, modern device development does not consist of gluing a bunch of APIs together. Apple maintains its own compilers, languages, toolchains, runtimes, hardware, operating systems, debugging tools, and so on. Some of that code had distant origins in open source (e.g. webkit), but that’s vastly different than publicly funded and those components are usually very different today.

    They’re failing to produce competitive modems because modern wireless is one of closest things humans have to straight up black magic. It’s extremely difficult to get right, especially as frequencies go up, SNR goes down, and we try to push things ever faster despite having effectively reached the Shannon limit ages ago.