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Joined 2 years ago
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Cake day: August 11th, 2023

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  • I’ve tried making this argument before and people never seem to agree. I think Google claims their Kubernetes is actually more secure than traditional VMs, but how true that really is I have no idea. Unfortunately though there are already things we depend upon for security that are probably less secure than most container platforms, like ordinary unix permissions or technologies like AppArmour and SELinux.


  • Crypto is actually really useful for buying drugs and other illegal products and services. People have legitimately made a lot of money as well if they weren’t falling for the stupid scams. You should see the price of BitCoin or Ethereum these days.

    Not saying it’s ethical to run a lot of these given their limited usefulness and very high costs. But saying they didn’t make people money, were all scams, or didn’t have a use is objectively wrong.









  • There is a lot that can be discussed in a philosophical debate. However, any 8 years old would be able to count how many letters are in a word. LLMs can’t reliably do that by virtue of how they work. This suggests me that it’s not just a model/training difference. Also evolution over million of years improved the “hardware” and the genetic material. Neither of this is compares to computing power or amount of data which is used to train LLMs.

    Actually humans have more computing power than is required to run an LLM. You have this backwards. LLMs are comparably a lot more efficient given how little computing power they need to run by comparison. Human brains as a piece of hardware are insanely high performance and energy efficient. I mean they include their own internal combustion engines and maintenance and security crew for fuck’s sake. Give me a human built computer that has that.

    Anyway, time will tell. Personally I think it’s possible to reach a general AI eventually, I simply don’t think the LLMs approach is the one leading there.

    I agree here. I do think though that LLMs are closer than you think. They do in fact have both attention and working memory, which is a large step forward. The fact they can only process one medium (only text) is a serious limitation though. Presumably a general purpose AI would ideally have the ability to process visual input, auditory input, text, and some other stuff like various sensor types. There are other model types though, some of which take in multi-modal input to make decisions like a self-driving car.

    I think a lot of people romanticize what humans are capable of while dismissing what machines can do. Especially with the processing power and efficiency limitations that come with the simple silicon based processors that current machines are made from.







  • MIMO improves throughput if you have an Internet link it can saturate; realistically even a midrange 2x2 802.11AC router will provide more wifi bandwidth than your internet does.

    And that’s where the fat controller says you are wrong. I have 1000 Mbps down. I’ve yet to actually hit that speed with WiFi 6.

    Also newer WiFi standards significantly improve latency. That’s nothing to do with having more antennas though you would be correct there.

    The meme is correct. A $6 ethernet cable beats any and all wifi routers and client adapters, and always will.

    With current technology you would be correct. But as for the always part: Ethernet is an electrical signal, so it’s actually slower than microwave signals used by WiFi, and the WiFi signals can also take a more direct path. So in the future WiFi or LiFi could in fact be faster. It’s the processing delay, and scheduling that makes WiFi have higher latency. Not the physical medium.

    Before you say this is all academic because of the small distances involved I would remind you that propagation delay is actually a large issue in current microelectronics and computers. Sometimes parts of the same chip are far enough apart to create problems for the engineers due to the high clockspeeds of modern devices.