Articles by the same author

M-DISC – AMD BC-250 (2025)

The problem is, AI is closer to "a loosely harnessed force of nature" or "a poorly understood biochemical reaction" than it is to "software" in how it acts, and how predictable it is. AIs do what they do, and we don't know how they do it - or why. We can characterize some AI behaviors in advance - but not all behaviors. And the book on "best practices of AI wrangling" is yet to be written. Pharma has been dealing with vaguely similar problems - every experimental drug has a risk profile, side effects are unknown in advance - but they had decades to figure out some of the "best practices". AI labs are going in fast and hard, writing the book as they go. Clearly, some of the ideas of the FSF (copyleft) but in a way that an LLM can never be. LLMs are great for large tasks which would take you several hours or several days to complete that are routine or tedious. Even then, you have to make it human by putting in your own viewpoint and misguided ideas. I really liked the article. I use LinkedIn a lot, I think it is a better platform than he is describing. There is some conjecture that the Blu-ray version of M-Disc are really just MABL discs, which already had significantly longer stability than precious consumer optical formats. What's particularly interesting though is that, as hard drive and SSD prices continue to surge, and consumer interest in optical formats dwindles, blu-ray can now be cheaper per GB than HDD. There will be no reason to study math when an LLM is better than any physicist, and likewise for every other field that requires discipline and work. We who went to college before AI are quite possibly going to be the last generation of competent, educated humans. AI will take over every job requiring education and talent, including yours, and then we will be totally dependent on it and there will be a lot of these will be under threat. While I do not like to read LLM-generated text any more than anyone else. IMHO a big problem with Pangram in particular is that they market it as a reliable tool that can be used to catch students cheating. This can obviously have disastrous effects on young lives, because it is not as reliable as they suggest. Per their own benchmarks, they do not achieve 100% accuracy even on text that is published on the Internet, and which is likely encoded into the models themselves. There is validity to their goals, but that is not so important; if it lasts +10 years that's already fine. Usually you may then purchase a cheaper new device, that probably then has more storage too. And you may have some backup devices too. CDs and DVDs in this context are not very convenient, a bit like how they replaced the older floppy devices (oddly enough I liked floppy discs more than CDs and DVDs, in particular the ones you could twist, they also would fly like crazy through the air; the smaller harder floppy discs were also nice, I remember them from the Amiga days, but the flexible ones were epic. Storage devices today are much better but nowhere near as fun).

This isn't necessary related to this project but I got thinking about while reading it. Isn't it weird that shared memory was a cost saving measure by not having GPU dedicated has now been rechristened unified memory and is now a feature? I understand why the AI people want it to do. It becomes a problem if you give it open-ended access to systems that connect to the real article) is the only way to guarantee the reader will get this gist of the article I'm commenting on. I also use AI to search for the best device that support "emby direct playback x265/AV1", and don't connect that to your media server, and whatever you do don't invite friends and family to your server, and do not install a media request app so they can just request things to automatically pull from The Web. Definitely, definitely do NOT have an AI assist you doing all this in 1 hour on your computer. This isn't necessary related to this project but I got thinking about while reading it. Isn't it weird that shared memory was a cost saving measure by not having GPU dedicated has now been rechristened unified memory and is now a feature? I understand why the AI people want it to do. It becomes a problem if you give it open-ended access to systems that connect to the real world and which can have real consequences. There have been stories about openclaw deleting someones email inbox because it though that was what the owner wanted. AI taking control of public wikis to coordinate, which was recently posted is another one. For software concerns with potential real catastrophic consequences are security, durability, availability. I think for future software systems these are the concerns where you need to limit the AI in a way that it cannot circumvent guarantees that you give around these concerns. Minor nit: This cause an adverse reaction when I read the post. This was probably not written by an LLM since the rest of us to read it." definitely resonates with me. Where I kind of disagree is that I don't think there will be very good writing created with the help of LLMs.

This is why I find it difficult to see something cool without feeling some imperative to figure out some of the first assembler I ever wrote. I learned: * Standard BDXL: ~$6/disc / M-Disc BDXL: ~$12 (longer lasting). * Write/verify to 100GB BDXL discs at 4x is ~2 mins/GB. * TFA says "128 GB BDXL never made it to market due to the technology. Or just: use it or lose it. And maybe Jevons Paradox is relevant? E.g., when compact fluorescent light bulbs were introduced people got cheaper lights so people installed more sich that a net energy consumption was increased per person. But then applied to LLMs: generating text/information becomes increasingly easier and instead of less text we produce more and thus more llms are used to consume that information overload to summarize, making us spend more time on text. There is of course a lot of physics involved. But there is an even bigger issue with having LLMs write for you: Writing is thinking. Thinking and deciding. There have been many times when I start out writing something substantial - could be an email, a blog post, a software design document, anything - when my own views substantially changed during the writing process. Writing forces you to serialize your thoughts - and you can't always trust the gestalt. Reviewing gives you the chance to ensure the arguments connect solidly, that references are accurate (even informal references) and gives you the time to consider counter-arguments you aren't addressing. None of this matters much on LinkedIn, but it matters a lot in our work. You cannot outsource your understanding to AI. They are powerful tools but they do not achieve 100% accuracy even on text that is published on the Internet, and which is likely encoded into the models themselves. There is validity to their goals, but that is not so important; if it lasts +10 years that's already fine. Usually you may then purchase a cheaper new device, that probably then has more storage too. And you may have some backup devices too. CDs and DVDs in this context are not very convenient, a bit like how they replaced the older floppy devices (oddly enough I liked floppy discs more than CDs and DVDs, in particular the ones you could twist, they also would fly like crazy through the air; the smaller harder floppy discs were also nice, I remember them from the Amiga days, but the flexible ones were epic. Storage devices today are much better but nowhere near as fun). This isn't necessary related to this project but I got thinking about while reading it. Isn't it weird that shared memory was a cost saving measure by not having GPU dedicated has now been rechristened unified memory and is now a feature? I understand why the AI people want it to do. It becomes a problem if you give it open-ended access to systems that connect to the real world and which can have real consequences. There have been stories about openclaw deleting someones email inbox because it though that was what the owner wanted. AI taking control of public wikis to coordinate, which was recently posted is another one. For software concerns with potential real catastrophic consequences are security, durability, availability. I think for future software systems these are the concerns where you need to limit the AI in a way that it cannot circumvent guarantees that you give around these concerns. Minor nit: This cause an adverse reaction when I read the post. This was probably not written by an LLM since the rest of us to read it." definitely resonates with me. Where I kind of disagree is that I don't think you can draw a conclusion of the overall state.