Posts by Paul Kinsler 1128 publicly visible posts • joined 9 Aug 2007
It's likely to vary. For some, it will indeed be analysing a giant chunk of just-harvested data, or running very specific simulations, and so might well be occasional and compute intensive. But at the other extreme, there is continuous processing of incoming data in real-time (or near real time) ... as those in space weather, e.g. doing CME modelling/ forecasting, based on satellite or radio-telescope outputs.
Indeed. But perhaps since these models are touted as "AI", it is of some interest exactly to treat them as if they were, and see what an analysis reveals.
And possibly, with an anthro/psych framing like this, results might be more easily taken on board by those who either believe the "AI" claim, or at least who are inclined to treat their interactions with them in that way -- because that is how things *seem* to them.
This is (or at least was) a thing that used to be done sometimes on linear tv - the ad for a thing would change week-to-week or whatever, advancing some small narrative, and it indeed seemed to engage some viewers. But it probably relied mostly on the inertia of those stuck - or prepared to wait - in front of the tv whilst waiting for the ad break to finish (I mean, how many cups of tea might you actually need in an hour?), and what with all the time shifting, catchup, bingeing, and skipping capabilities now I'm not sure it could manage anything like the same traction.
However, note that GPS-style GNSS satellites (GPG, Glonass, Galilleo, Baidou) - with the exception of a couple of Baidou ones - are not geostationary; so individual satellites do not cover just some specific part of the world; although there are a few regional services.
I would have thought that it would be better to say that microkernels move most (or a lot of) the attack surface into userland; which might indeed solve or reduce the many problems introduced by that attack surface, but not -- I presume -- all of them.
OK, but if you want a deliverable lunar reactor for when you need it to appear, some design and testing will have to have been done in advance ... such as in this project. And if you expect to need a reactor to power your moonbase, you might even want to have it in place and running reliably for a while *before* it becomes a critical part of your infrastructure.
And in the meantime, some physicists will -- most likely -- be along shortly with innumerable projects for a wide variety of sensors, telescopes, and the like, all of which might benefit from a convenient power source. Might be tricky to get your robot to plug in the necessary powerboard/extension cable though. :-)
Alternatively: K.W. Jeter
https://en.wikipedia.org/wiki/Morlock_Night
Quote: "Morlock Night is a science fiction novel by American writer K. W. Jeter. It was published in 1979. In a letter to Locus Magazine in April 1987, Jeter coined the word "steampunk" to describe it and other novels by James Blaylock and Tim Powers. "
As a general point, and irrespective of whether-or-not the subject is LLMs, many apparently "unsolvable" problems can be solved, if only you work out how - may be this is a moment of genius, or maybe some better mathematics or technology that overcomes the roadblock, and sometimes - like in some research - a sheer bloody-minded but systematic iteration through a vast array of combinations. And, as a case in point, computerised/robotic labs have made such brute-force efforts much more tractable.
It might be that LLM's are a true dead end, or it might be that they are not a true dead-end, but have some rare but valuable use-cases. But if finding out how to engineer those use-cases is hard or unlikely (as you suggested with your "dead end" remark), then IMO trying a wide and diverse mixture of strategies is probably more likely to be successful at finding that unexpected valuable use, than is focusing in on just a few decided at the top level.
But which does not necessarily mean that OpenAI are using their money wisely, or have their balance right; just that they might not be entirely wrong in their approach.
Although see e.g.
Electromagnetic Energy Extraction from Kerr Black Holes: Ab-Initio Calculations
Meringolo et al
The possibility of extracting energy from a rotating black hole via the Blandford-Znajek mechanism represents a cornerstone of relativistic astrophysics. We present general-relativistic collisionless kinetic simulations of Kerr black-hole magnetospheres covering a wide range in the black-hole spin. Considering a classical split-monopole magnetic field, we can reproduce with these ab-initio calculations the force-free electrodynamics of rotating black holes and measure the power of the jet launched as a function of the spin. The Blandford-Znajek luminosity we find is in very good agreement with analytic calculations and compatible with general-relativistic magnetohydrodynamics simulations via a simple rescaling. These results provide strong evidence of the robustness of the Blandford-Znajek mechanism and accurate estimates of the electromagnetic luminosity to be expected in those scenarios involving rotating black holes across the mass scale.
https://arxiv.org/abs/2507.08942
I am not sure that overclaiming with "what people needed" really helps your argument. It should be pretty clear by now that many of the people who post here are perfectly happy with what X11 has delivered and still delivers (me included). Thus at best your statement has to become:
"X11 has a long history of not being able to deliver what some people needed".
Perhaps that "some" should be "many"; although where you might find reliable stats one way or another is an interesting question.
Broadly, however, just like with systemd, the choice of wayland vs X11 is not being actively made by anything like a majority of linux users; who most likely just make do more-or-less happily with whatever their distro-of-choice devs happen to prefer, and in all likelihood really haven't given the issue much thought (unlike us variously partisan commentards here).
At a tangent, but since I was reading a couple of interrelated discussions on ways of thinking about AI/LLMs yesterday, I thought others here might be interested in them:
http://bactra.org/weblog/feral-library-card-catalogs.html
https://crookedtimber.org/2023/07/03/shoggoths-amongst-us/
https://www.science.org/doi/10.1126/science.adt9819
You might find it educational to read up on the subject: coupling light into an optical fibre is not necessarily trivial, and optical fibre will not usefully transmit any frequency of light you might wish to send (notably due to absorption, inconvenient dispersive properties, or indeed various other things).
I think it would best to *start* the project off with a small, visible, but nonetheless tasteful and polite request for donations (or even just noting that they might eventually be requested). That way everyone will just automatically have to get used to it by default, and so regular users will not be shocked and/or annoyed by one suddenly appearing a few years down the track. :-)
I also have my thesis on some old tape format, but it doesn't matter that I can't read it -- I have had the file in my work archive copied from machine to machine to machine as I moved around.
The problem is, in fact, not how its been stored, but that it was created by the then version of MS Word. Fortunately I still have the nicely bound hardcopy version ... not that I need to read it very often.
On the BBC page there is a link to a pdf. In it both OLED and LCD displays are mentioned, and the difference between OLED and LCD noted.
However, their single test device is in fact a Macbook Pro with an LCD display.
As a final remark, this seems to be a report which is really more about addressing user-expectations, rather than about technology differences. As in e.g. a user might have heard "dark mode saves power", but not twigged to the fact that it isn't true for their LCD display, especially once they perhaps have also put the brightness up a bit.
They are presumably not infallible, but many scientific journals now automatically check the citations in submitted papers, and raise a query if they cannot find an authoritative match.
Thus you might imagine a scheme where any "citation" detected and tokenised, could also be tagged as validated, or as unvalidated; and if used, reported as such.
Unlikely to be infallible, and only workable in specific cases, sure -- but still an improvement. But you probably wouldn't want an LLM to do the validating :-)
It seems to me the training process, at the very least, needs to treat each citation it finds as a single unique token, rather than just another miscellaneous collection of characters or words. Then it would at least only generate actual citations, rather than merely some text that resembles a citation. And it might even manage to put them - sometimes - in a correct context, but I don't think you could rely on it - the reasoning behind why authors cite a thing is not always clear - it can range from some-generic-backgound, all the way down to a-specific-result-on-page-something.
Hmm. Recently Google used raw GNSS data to run a study on android phones without explicit permission:
https://www.nature.com/articles/s41586-024-08072-x
If they can yank raw code phases and pseudodistances, what makes you think a position spoofing app is a bulletproof solution?
For these kinds of order-of-magnitude estimates it doesn't matter very much whether you count a neutron as one particle or its three constituent quarks (or, for the old school types, a proton plus an electron). The number is to get an idea of the scale, not to get a value which is supposed to "correct".
Since the article says "Avcoat was developed in the 1960s and used on the Apollo missions to protect spacecraft as they re-entered Earth atmosphere", I'd probably guess they have had enough (other) experience of it to be able to have reasonable confidence in their judgement..?
Ah, so we should use the double hyphen, i.e. ....
rm -- *
... but then why create a "-rf" file in the first place?
[edit: I suppose you might do it by accident, with one of those misplaced/mangled pastes that create a load of files named after the commands you wanted to run. Or is that just me?]
I tend to put a trailing / on all my directories which can mitigate this sort of thing (unless already in /), thus (in bash) there would be the possibly missing
QATOOLS="/opt/qatools/"
and then
rm -rf ${QATOOLS}bin
Also, it just occurred to me that (again in bash) you could even try to remember to type (or script)
rm -rf ${QATOOLS:-QQQQ}bin
so that the rm shouldn't get anything ever, unless you really like directory names with Q in them:-)
But if the number of Mersenne primes is unbounded, then presumably for any fixed choice of "large", there will be more "large" Mersenne primes than small ones, and, further, infinitely more large than non-large. Which might make it at least more-or-less reasonable to say that Mersenne primes "are large". :-)
But perhaps what was meant that if considering all discovered "large" primes, you will notice that more of them are Mersenne than of any other type? (or some similar statement).
But shouldn't a law against the creation and/or enabling of bioweapons (whether by AI, by chemical precursors, or whatever) be the control in such a case; not us merely hoping that it will happen as a side-effect of generic AI controls?
It seems implausible to me that Generic AI law will ever cover all dangerous use-cases; so what they should attempt to control is AI-specific dangers, not those from any possible application.
But I suppose if you had to cope with user input, then an LLM might be handy for creating a large number of plausibly-human like responses (ie which might also be slightly mangled or confused), as a sort of weak fuzzing...
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