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Cake day: June 9th, 2023

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  • ylai@lemmy.mltoAsklemmy@lemmy.mlHow long til Blu-rays get phased out
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    2 years ago

    Retention, or the lack thereof, when cold-stored.

    In term of SD or standard NAND, not even Nintendo does that. Nintendo builds Macronix XtraROM in their Game Card, which is some proprietary Flash memory with claimed 20 year cold storage retention. And they introduced the 64 GB version only after a lengthy delay, in 2020. So it seems that the (lack of) cold storage performance of standard NAND Flash is viewed by some in the industry as not ready for prime time. Macronix discussed it many years back in a DigiTimes article: https://www.digitimes.com/news/a20120713PR201.html.

    And Sony and Microsoft are both still building Blu-ray-based consoles.




  • There might be several misunderstandings:

    • Docker Desktop ≠ Docker Engine, and I think what you (and several in this thread) are thinking is actually Docker Engine. Docker Desktop ultimately includes a Docker Engine inside, but it does not appear you need that virtual machine (e.g. running non-Linux code). See: https://docs.docker.com/desktop/faqs/linuxfaqs/#what-is-the-difference-between-docker-desktop-for-linux-and-docker-engine
    • Docker Desktop is based on KVM, which already works with Flatpak. So this is not something new. For example, GNOME Boxes is available as Flatpak and provides a way to run KVM guests in SteamOS.
    • Starting with version 3.5 (the current stable) SteamOS already includes Podman with the default installation. And running the daemon-y Docker Engine “bare metal” is not going to be any easier with the immutable filesystem. While Docker Desktop solves this by using KVM, it adds another layer with performance loss, vs. just running Podman containers.

    So what you want is already available, and no Docker Desktop is actually needed.




  • My impression is that game AI (and I mean in FPS, not board games) were not considered as serious AI in the computer science sense. Most game AI even till this day are “cheating” in the sense that they are not end-to-end (i.e. cannot operate using screen capture, vs. engine information), and often also need additional advantages to hold ground. For example, virtually all these FPS game AI are quite useless once you actually want to interface it with some form of robotics and do open world exploration. So game AI is somewhat separate from the public’s obsession with the term AI, that suddenly turn nit-picky/moving-the-goalposty once AI became performant on end-to-end tasks.

    The Wikipedia article AI effect (not super-polished) has many good references where people discussed how this is related to anthropocentrism, and people can also be very pushy with that view in the context of animal cognition:

    Michael Kearns suggests that “people subconsciously are trying to preserve for themselves some special role in the universe”.[20] By discounting artificial intelligence people can continue to feel unique and special. Kearns argues that the change in perception known as the AI effect can be traced to the mystery being removed from the system. In being able to trace the cause of events implies that it’s a form of automation rather than intelligence.

    A related effect has been noted in the history of animal cognition and in consciousness studies, where every time a capacity formerly thought as uniquely human is discovered in animals, (e.g. the ability to make tools, or passing the mirror test), the overall importance of that capacity is deprecated.[citation needed]

    Note that there is also a similar effect, not explicitly discussed by that article, where people like to depict ancient societies dumber than they actually are (e.g. the today discounted notion of “Dark Ages”).


  • To clarify: The authors/Stanford used this exact stated/non-question title for their press release: https://hai.stanford.edu/news/ais-ostensible-emergent-abilities-are-mirage, which ended up also being the title of the previous post on !artificial_intel@lemmy.ml. As already noted by @huginn@feddit.it, this “AI’s Ostensible” title is therefore well in line with the paper’s actual conclusion, that is refuting current claims of emergence. And I picked the “AI’s Ostensible” title being from the authors/their employer, for clarity (especially when quoted inside a larger Lemmy post title), and continuity with the previous post.

    It is clear to anyone who used them and understand the task they were trained on, […]

    Yet where is the proof? This is the exact wishy-washy way of not substantiating a claim, which this paper investigated and have refuted.

    […] that LLMs do have emergent abilities.

    I think you should really not drop that sentence immediately in front of your quite selective quote — the authors put it in emphasis for good reasons:

    Ergo, emergent abilities may be creations of the researcher’s choices, not a fundamental property of the model family on the specific task.

    So regarding “emergent abilities,” it is quite clear the authors argue that from their analysis, if at all, cherry-picked metrics carry these “emergent abilities,” not LLMs.