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claiir

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claiir
·قبل 14 يومًا·discuss
The writing of the paper was so heavily ai, I was unsure if it was satire given the subject matter.
claiir
·الشهر الماضي·discuss
> currently (as of Q3 2025) the fastest-growing of the top four languages in the world… +90% users in the past 3.5 years.

Because of AI, right?
claiir
·قبل 5 أشهر·discuss
Oh this makes sense.
claiir
·قبل 5 أشهر·discuss
And Gemini 3 can’t..? Isn’t this just a thinking vs nonthinking model thing?
claiir
·قبل 5 أشهر·discuss
This part is interesting:

> [verify to] Speak in a stage channel.

My understanding is non-stage voice channels are E2E encrypted, and Discord retains no recordings, whereas stage channels are not. Is this a liability thing—Discord not wanting to have voice recordings of non-adults?
claiir
·قبل 8 أشهر·discuss
Javascript doesn’t generally execute on your GPU.
claiir
·قبل 11 شهرًا·discuss
> Asked by CNN's Kaitlan Collins why previous editions of the National Climate Assessment were no longer available online, former fracking company CEO Wright responded [..]

lol
claiir
·السنة الماضية·discuss
Maybe just have commands auto-execute if you click on links in the existing text? That would allow someone to experience the entire interface on a touch device! :>

E.g. there is **__contact__** in the page, bold and underlined, but you cannot click on it to do anything.
claiir
·السنة الماضية·discuss
Sounds like the LLM you used when writing this slop comment struggled with the problem too. :>
claiir
·السنة الماضية·discuss
Same experience with my personal benchmarks. Generally unimpressed with Qwen3.
claiir
·السنة الماضية·discuss
o1-preview had this same issue too! You’d give it a long conversation to summarize, and if the conversation ended with a question, o1-preview would answer that, completely ignoring your instructions.

Generally unimpressed with Qwen3 from my own personal set of problems.
claiir
·السنة الماضية·discuss
Likely not the case, given (1) the body was peri-mortem decapitated (by a human) and (2) apparent structural damage was limited to a single bite mark (on the ilium), with no signs of "taphonomic" damage (indicating limited soft tissue trauma)? [1]

(1) > 6DT19 had been decapitated with a single cut between the second and third cervical vertebrae , delivered from behind.

(2) > Additional [to the decapitation] peri-mortem trauma was present in the form of a series of small depressions on both sides of the pelvis [..]

> Taphonomic damage alone is also unlikely due to the appearance and margins of the lesions, which are the same colour as the surrounding bone (this differs if the break is post-mortem; [56]), and the adherence of bony fragments at the injury site (which occurs when soft tissue is present) .

[1]: https://journals.plos.org/plosone/article?id=10.1371/journal...
claiir
·السنة الماضية·discuss
Actual paper: https://journals.plos.org/plosone/article?id=10.1371/journal...
claiir
·السنة الماضية·discuss
> GoDaddy is actively experimenting to integrate image generation so customers can easily create logos that are editable [..]

I remember meeting someone on Discord 1-2 years ago (?) working on a GoDaddy effort to have customer-generated icons using bespoke foundation image gen models? Suppose that kind of bespoke model at that scale is ripe for replacement by gpt-image-1, given the instruction-following ability / steerability?
claiir
·السنة الماضية·discuss
Okay, but why did `LeaveCriticalSection` change? Compiler changes, new features, refactoring, etc? That’s the most interesting part (and absent)!
claiir
·السنة الماضية·discuss
It’s not just you. The speedup is an artefact of the CFG (Classifier-Free Guidance) the model uses. The other problem is the speedup isn’t constant—it actually accelerates as the generation progresses. The Parakeet paper [1] (which OP lifted their model architecture almost directly from [2]) gives a fairly robust treatment to the matter:

> When we apply CFG to Parakeet sampling, quality is significantly improved. However, on inspecting generations, there tends to be a dramatic speed-up over the duration of the sample (i.e. the rate of speaking increases significantly over time). Our intuition for this problem is as follows: Say that is our model is (at some level) predicting phonemes and the ground truth distribution for the next phoneme occuring is 25% at a given timestep. Our conditional model may predict 20%, but because our uncondtional model cannot see the text transcription, its prediction for the correct next phoneme will be much lower, say 5%. With a reasonable level of CFG, because [the logit delta] will be large for the correct next phoneme, we’ll obtain a much higher final probability, say 50%, which biases our generation towards faster speech. [emphasis mine]

Parakeet details a solution to this, though this was not adopted (yet?) by Dia:

> To address this, we introduce CFG-filter, a modification to CFG that mitigates the speed drift. The idea is to first apply the CFG calculation to obtain a new set of logits as before, but rather than use these logits to sample, we use these logits to obtain a top-k mask to apply to our original conditional logits. Intuitively, this serves to constrict the space of possible “phonemes” to text-aligned phonemes without heavily biasing the relative probabilities of these phonemes (or for example, start next word vs pause more). [emphasis mine]

The paper contains audio samples with ablations you can listen to.

[1]: https://jordandarefsky.com/blog/2024/parakeet/#classifier-fr...

[2]: https://news.ycombinator.com/item?id=43758686
claiir
·السنة الماضية·discuss
Yea they mention a “perplexity drop” relative to naive quantization, but that’s meaningless to me. > We reduce the perplexity drop by 54% (using llama.cpp perplexity evaluation) when quantizing down to Q4_0.

Wish they showed benchmarks / added quantized versions to the arena! :>
claiir
·السنة الماضية·discuss
In this case it's a little bit worse; the "nate" app had a literally "0% automation rate," despite representations to investors of an "AI" automation rate of "93-97%" powered by "LSTMs, NLP, and RL." No ML model ever existed! [1]

See:

> As SANIGER knew, at the time nate was claiming to use AI to automate online purchases, the app’s actual automation rate was effectively 0%. SANIGER concealed that reality from investors and most nate employees: he told employees to keep nate’s automation rate secret; he restricted access to nate’s “automation rate dashboard,” which displayed automation metrics; and he provided false explanations for his secrecy, such as the automation data was a “trade secret.”

> SANIGER claimed that nate's "deep learning models" were "custom built" and use a "mix of long short-term memory, natural language processing, and reinforcement learning."

> When, on the eve of making an investment, an employee of Investment Firm-1 asked SANIGER about nate's automation rate, that is, the percentage of transactions successfully completed with nate's AI technology, SANIGER claimed that internal testing showed that "success ranges from 93% to 97%."

(from [1])

[1]: https://www.justice.gov/usao-sdny/media/1396131/dl?inline
claiir
·السنة الماضية·discuss
Actual indictment: https://www.justice.gov/usao-sdny/media/1396131/dl?inline
claiir
·السنة الماضية·discuss
* Please respond to the strongest plausible interpretation of what someone says, not a weaker one that's easier to criticize. Assume good faith.

Be charitable. I provided encyclopedic reference out of a mutual discovery interest. Magazine articles[/opeds] may—in your words—present “opinions of some,” whereas reference-grade material provides a broad and citable foundation—ostensibly what you are looking for (“your axiomatic foundation is just another opinion of some”).

> You haven't [..] backed up your opinion

In the spirit of “respond to the strongest plausible interpretation” and good faith, I think you may have missed the argument I was making above. :>

I am positing a reformulation/distillation of “positive trade balance preference” as “preference for foreign investment,” drawing on Palgrave, although perhaps controversially. The former is controversial, especially if seen as a-priori; the latter mundane.

:>