How does this analogy work at all? LoRA is chosen by the modifier to be low ranked to accommodate some desktop/workstation memory constraint, not because the other weights are “very hard” to modify if you happens to have the necessary compute and I/O. The development in LoRA is also largely directed by storage reduction (hence not too many layers modified) and preservation of the generalizability (since training generalizable models is hard). The Kronecker product versions, in particular, has been first developed in the context of federated learning, and not for desktop/workstation fine-tuning (also LoRA is fully capable of modifying all weights, it is rather a technique to do it in a correlated fashion to reduce the size of the gradient update). And much development of LoRA happened in the context of otherwise fully open datasets (e.g. LAION), that are just not manageable in desktop/workstation settings.
This narrow perspective of “source” is taking away the actual usefulness of compute/training here. Datasets from e.g. LAION to Common Crawl have been available for some time, along with training code (sometimes independently reproduced) for the Imagen diffusion model or GPT. It is only when e.g. GPT-J came along that somebody invested into the compute (including how to scale it to their specific cluster) that the result became useful.
This is a very shallow analogy. Fine-tuning is rather the standard technical approach to reduce compute, even if you have access to the code and all training data. Hence there has always been a rich and established ecosystem for fine-tuning, regardless of “source.” Patching closed-source binaries is not the standard approach, since compilation is far less computational intensive than today’s large scale training.
Java byte codes are a far fetched example. JVM does assume a specific architecture that is particular to the CPU-dominant world when it was developed, and Java byte codes cannot be trivially executed (efficiently) on a GPU or FPGA, for instance.
And by the way, the issue of weight portability is far more relevant than the forced comparison to (simple) code can accomplish. Usually today’s large scale training code is very unique to a particular cluster (or TPU, WSE), as opposed to the resulting weight. Even if you got hold of somebody’s training code, you often have to reinvent the wheel to scale it to your own particular compute hardware, interconnect, I/O pipeline, etc… This is not commodity open source on your home PC or workstation.
The situation is somewhat different and nuanced. With weights there are tools for fine-tuning, LoRA/LoHa, PEFT, etc., which presents a different situation as with binaries for programs. You can see that despite e.g. LLaMA being “compiled”, others can significantly use it to make models that surpass the previous iteration (see e.g. recently WizardLM 2 in relation to LLaMA 2). Weights are also to a much larger degree architecturally independent than binaries (you can usually cross train/inference on GPU, Google TPU, Cerebras WSE, etc. with the same weights).
There is even a sentence in README.md
that makes it explicit:
The source files in this repo are for historical reference and will be kept static, so please don’t send Pull Requests suggesting any modifications to the source files […]
There has been:
He was criticized also because the girls were not in danger of becoming infected. See e.g. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6724388/ :
The Chinese episode has also generated other issues. Several notes demonstrate that this was an experiment and not a therapeutic intervention (even He Jiankui called it a ‘clinical trial’). The babies were not at risk of being born with HIV, given that sperm washing had been used so that only non-infected genetic material was used. Further, even though one of the parents (or both) was infected, it did not mean the children were more prone to becoming infected. The risk of becoming infected by the parents’ virus was very low (Cowgill et al., 2008). In sum, there was no curative purpose, nor even the intention to prevent a pressing risk. Finally, the interventions were different for each twin. In one case, the two copies of CCR5 were modified, whereas in the other only one copy was modified. This meant that one twin could still become infected, although the evolution of the disease would probably be slower. The purpose of the scientific team was apparently to monitor the evolution of both babies and the differences in how they reacted to their different genetic modifications. This note also raised the issue of parents’ informed consent regarding human experimentation, which follows a much stricter regimen than consent for therapeutic procedures.
Other critical articles (e.g. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8524470/) have also cited in particular https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4779710/, which states in the result section:
No HIV transmission occurred in 11,585 cycles of assisted reproduction using washed semen among 3,994 women (95% confidence interval [CI] = 0–0.0001). Among the subset of HIV-infected men without plasma viral suppression at the time of semen washing, no HIV seroconversions occurred among 1,023 women following 2,863 cycles of assisted reproduction using washed semen (95%CI= 0–0.0006). Studies that measured HIV transmission to infants reported no cases of vertical transmission (0/1,026, 95% CI= 0–0.0029). Overall, 56.3% (2,357/4,184, 95%CI=54.8%–57.8%) of couples achieved a clinical pregnancy using washed semen.
GIMP is a special case. GIMP is being getting outdeveloped by Krita these days. E.g.:
https://gitlab.gnome.org/GNOME/gimp/-/issues/9284
Or compare with:
https://www.phoronix.com/news/Krita-2024-GPUs-AI
GIMP had its share of self inflicted wounds starting with a toxic mailing list that drove away people from professional VFX and surrounding FilmGimp/CinePaint. When the GIMP people subsequently took over the GEGL development from Rhythm & Hues, it took literally 15 years until it barely worked.
Now we are past the era of simple GPU processing into diffusion models/“generative AI” and GIMP is barely keeping up with simple GPU processing (like resizing, see above).
Have people actually checked the versions there before making the suggestion?
F-Droid: Version 3.5.4 (13050408) suggested Added on Feb 23, 2023
Google Play: Updated on Aug 27, 2023
https://f-droid.org/en/packages/org.videolan.vlc/
https://play.google.com/store/apps/details?id=org.videolan.vlc
The problem seems to be squarely with VLC themselves.
From my own statistics how many I feel worthy posting/linking on Lemmy, the most direct alternative to Kotaku is Eurogamer. PCGamer, PCGamesN and Rock Paper Shotgun are occasionally OK, but you have to cut through a lot of spam and clickbait (i.e. exactly this “50 guides per week” type of corporate guidance). Not sure if this is also the state that Kotaku will end up in. The Verge sometimes also have good articles, but the flood of gadget consumerism articles there is obnoxious.
The PS Vita side of Sony customer has gotten a deep taste of Sony’s issues of catering everything to a singular console. And same with PSVR2: Of course it must be PS5 exclusive, because everything are adornments towards their shiny console — and went on to not sell a lot of PS5.
There is pre-existing context and criticism. And it is not about, or just being the perception of “this journalist”:
https://www.theverge.com/23992402/geoff-keighley-the-game-awards-layoffs
https://videogames.si.com/features/games-industry-deserves-better-than-geoff-keighley
https://www.inverse.com/gaming/the-game-awards-2023-needs-to-acknowledge-industrys-lay-offs-problem
https://dotesports.com/the-game-awards/news/the-game-awards-layoffs-developers-no-respect
The problems also goes beyond just the layoffs, but his overt coziness and preferential treatment of large studios, over even the ones that actually won the award he is presiding over, and are supposed to be celebrated:
https://insider-gaming.com/geoff-keighley-shows-cowardice-at-the-game-awards/
https://www.eurogamer.net/the-game-awards-speeches-were-too-short-geoff-keighley-admits
My understanding is that it allows you to play planar video from a website, but not (yet?) side-loaded videos that are spherical/hemispherical. And the latter is what these people really wanted for this application.
There are now summaries from non pay-walled (and English) press: https://www.eurogamer.net/new-the-day-before-report-alleges-employees-fined-for-making-mistakes
My motivation was the “dead wrong expecting someone to step up like adults in the room” part.
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 are plenty of EDID blockers and emulators already on the market. Unfortunately, no, “find[ing] […] the monitor’s model number” is not as trivial as you may think, if somebody really wants to evade. It is quite trivial nowadays to spoof the EDID in hardware, without the software able to do anything.
Three side remarks about China, which can be a peculiar example to compare to for Russia, maybe even any other country: