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zaptrem

1,951 karmajoined há 6 anos

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Wikipedia: Sandbox

en.wikipedia.org
93 points·by zaptrem·há 5 meses·37 comments

comments

zaptrem
·há 6 dias·discuss
Why haven’t we seen any queues or the like over the past week then? If it’s truly a capacity limitation why not just boot subscription users to a lower priority queue or limit usage to outside peak hours?
zaptrem
·há 17 dias·discuss
Should we require the destruction of the brains of those that watch pirated movies?
zaptrem
·mês passado·discuss
Needs more WebGL spinning rubik's cube
zaptrem
·mês passado·discuss
Can you include GPT 5.5 non-pro (extra high thinking I guess) in your comparison? GPT Pro is the "I am willing to torch cash for a sooometimes slighty better result" option, not the one people are actually expected to use daily. That's probably part of the reason it's not in Codex
zaptrem
·mês passado·discuss
OOM on CUDA GPUs is relatively graceful (the process crashes). However, on macOS if torch MPS tries to allocate too much memory, the whole kernel will simply lock up and the only option is to reboot the computer. I have no idea why Apple doesn’t reserve memory for stuff like the OOM/kernel watchdog, but it seems they either don’t or there is a bug.
zaptrem
·há 2 meses·discuss
Love me some JSD. Here is a problem most people don't consider with generative modeling (e.g., AI text, image, music, video models): basically all standard pre-training algorithms for generative models (i.e., cross entropy, basically all diffusion/flow formulations) are closer to a Forward KL divergence. In other words, given limited capacity the model will try to stretch itself to cover every mode. This gives you a jack of all trades (lots of knowledge and diversity), but a master of none (you get blurry images and text filled with nonsense).

The real magic in generative modeling comes from the post training process that comes after, which usually (e.g., RLHF) approximates Reverse KL (given limited capacity, try to perfectly cover what you can, but it's fine to drop the rest entirely). This gives amazing results, but is also the cause of AI oddities like the "AI Image Pixar Look", many of the verbal tics of LLMs, and all AI music using the same small set of voices. Jensen-Shannon Divergence sits right in the middle of Forward and Reverse KL and is what many GANs are claimed to approximate. Ideally, it is a better trade-off between diversity and fidelity.
zaptrem
·há 2 meses·discuss
V4-Pro is about 2.4× total params and 1.3× active params of V3.2.
zaptrem
·há 2 meses·discuss
Seems pretty clear, Claude and Codex were getting a lot of free publicity by instructing their models to do the same and MS wanted similar results. However, a bug caused this to be applied to all commits instead of all Copilot-influenced commits.
zaptrem
·há 3 meses·discuss
I bumped from $20 -> $100 today but the Codex CLI lacking code rewind and "you can change files but ask me every time" mode from Claude Code is quite annoying. Sometimes I want to code, not vibe code lol.
zaptrem
·há 3 meses·discuss
Agreed, that’s why I specified end to end (I.e., text to waveform)
zaptrem
·há 3 meses·discuss
My point is you should consider creating truly undetectable audio end to end with AI to be effectively impossible for the foreseeable future (i.e., I would bet money it is still trivially detectable five years from now). It won't be detectable to humans, though, only models.
zaptrem
·há 3 meses·discuss
I train music generation models. They are very trivial to detect. In fact, detecting them then training them to evade detection by the detection model is a big part of training them! But the detectors win instantly without some hardcore regularization. Simply turn that off and you've instantly got a perfect classifier.

This isn't like text classification, the signal many orders of magnitude higher bitrate and so many more corners need to be cut. It's likely going to be nearly impossible or at least not remotely worth it to generate an audio signal that is truly undetectable in the foreseeable future.
zaptrem
·há 3 meses·discuss
What's your reasoning effort set to? Max now uses way more tokens and isn't suggested for most usecases. Even the new default (xhigh) uses more than the old default (medium).
zaptrem
·há 3 meses·discuss
YouTube et al's automated copyright systems put way too much trust in the hands of those making the claims.
zaptrem
·há 4 meses·discuss
Many of the games that actual kids spend time on are the purest expression of gaming slop (half-broken microtransaction gambling hell with schizophrenic flashing colors). Roblox and Fortnite's Islands system are both guilty of this. The problem is kids don't know any better and don't yet understand the value of money. The obvious response is "parents should handle this" and while I agree, there is no system to let them say "here are Robux/V-Bucks you can spend on quality content (e.g., Fortnite's Battle Pass is very well designed, quality content), but gambling slop is disabled".
zaptrem
·há 4 meses·discuss
In my experience, the Epic Games Store downloads faster, installs more efficiently, and launches games faster than Steam. The social features I actually use (i.e., add a friend, join them in a game) work fine. I'm not aware of any features Steam has that EGS lacks that I actually use frequently (Valve's VR, streaming tech, and Proton are great, but I don't use those frequently). It's not just me, many indie game developers are also big fans of EGS (most recent example that comes to mind are Jeff Kaplan's remarks during his 10 hour stream a week or two ago). Gamers' vehement defense of what is effectively a monopoly continues to confuse me.
zaptrem
·há 4 meses·discuss
I have Max 20x and they're still separate on 2.1.75.
zaptrem
·há 5 meses·discuss
Data centers don't do anything other than sit there and turn electricity into heat. They only emit nothing but heat (which could be useful to others in the building).
zaptrem
·há 5 meses·discuss
What did Epic do?
zaptrem
·há 6 meses·discuss
"Previous data from the trial reported that 107 participants received the mRNA vaccine and Keytruda treatment, while the remaining 50 only received Keytruda. At the two-year follow-up, 24 of the 107 (22 percent) who got the experimental vaccine and Keytruda had recurrence or death, while 20 of 50 (40 percent) treated with just Keytruda had recurrence or death, indicating a 44 percent risk reduction"

Statistically, if those in the control group had gotten the treatment, then in expectation 9 of those people wouldn't have had their cancer return or died. It must be exciting to run these sorts of trials with super promising drugs, but also a little bittersweet/dark.