We're going to need more than a "I knew a guy" here
HN user
dev_hugepages
What parameter would you advise for min_p?
You can't treat it with opioid agonist therapy (buprenorphine, methadone, ...) to suppress the withdrawals like you would with most other cases of opioid dependency?
Because it sounds like the average LinkedIn poster and we don't want it to invade spaces outside LinkedIn.
He makes a point, though: bug bounties exist to incentivize people to find and report bugs to a company. We talk about white, gray, and black hats, roughly based on their level of ethics. For black hats – and some gray hats – money is one of the big reasons they look for vulnerabilities.
They are different drugs in the sense that methamphetamine will cause more serotonin release and will act longer than amphetamine, but they will both cause increase in blood pressure, increase heart rate and increase internal temperature. The rest of your comment is right though.
I read your blog and I can't agree, i've installed arch Linux before and only had to read the arch wiki page on it and it worked fine with none of the issues you described.
Same thing with gentoo, that I am daily driving now.
I sure had hickups but I managed to solve them by sitting and reading the manuals/wikis of the distros directly, or the programs I was dealing with. Maybe the problem is that you read an obscure forum to get your answer? I don't know.
Yes, most things are better (or at least too different) than they were 15-20 years ago.
Then, you are obsolete in the AI age.
Predicting a word is the final objective, as in the output of the model is a probability distribution of the next token. However, choosing the right token is more complicated than just regurgitating the training data (and you won't encounter an exact example in the training data, so you need to interpolate). This makes the model learn abstract representation of things that it is able to manipulate before outputting this back into token. RL also complicates this because the "fitness" is now some arbitrary metric computed over an entire sequence of tokens.
He's talking about the derivatives (nicknamed Pyros because they're related to Pyrovalerone) like α-PVP, MDPV and others.
So this is obviously vibe coded, may we obtain the source to see how that works?
Probably a provider thing. Looking at https://help.kagi.com/kagi/ai/llms-privacy.html, they're using deepinfra.
Looking at https://openrouter.ai/deepseek/deepseek-v4-flash/providers tells us that the deepseek provider achieves 49tps of throughput while deepinfra 19tps.
If anyone else is looking to make graph with typst, this can be done with https://cetz-package.github.io/ -- which is inspired by Tikz from the LaTeX world -- or https://lilaq.org/ which seems more appropriate for this type of data plotting
I took a look at the repo and it's probably the fault of the the SVG of the graphs, not of typist itself. Now, you could have used typst libraries to generate the graphs but back then (2 years ago I think?) it was probably a struggle.
The problem is that humans use this as a coping mechanism for things they don't understand: I don't understand why the printer doesn't work, so I give it a mind of its own.
This is harmless for inconsequential stuff like a chair, but when it's an LLM, people should at least understand it's behavior so they don't get trapped. That means not trusting it with advice meant for the user or on things it has no concept of, like time or self-introspection (people ask the LLM after it acted, "Why did you delete my database?" when it has limited understanding of its own processing, so it falls back to, "You're right, I deleted the database. Here's what I did wrong: ... This is an irrecoverable mistake, blah, blah, blah..."
And now, because we all upvoted and commented on it, the vibe coded slop of the new user is on the front page now.
Unrelated, but I was pleased at how fast the page opened: it felt pretty much instantaneous!
I opened the network log, disabled cache and reloaded to see it only transferred 8kb.
Keep up the good work!
No, the cache is a few GB large for most usual context sizes. It depends on model architecture, but if you take Gemma 4 31B at 256K context length, it takes 11.6GB of cache
note: I picked the values from a blog and they may be innacurate, but in pretty much all model the KV cache is very large, it's probably even larger in Claude.
On HN, I often see comments like this, complaining about Cloudflare blocking access to pages. It makes me wonder if it’s due to a particular setup that triggers bot detection – like Tor or no-JS – that HN readers often use, or if Cloudflare has too many false positives.
Time to gather a dataset and train your own model!
Yeah the habit of discarding typography and polish as a "proof of humanity" is worrying to say the least
I’m more hopeful that MIDI completion/in-filling models will be easier for musicians to control and use. But right now, the most popular tools are things like Suno, where you barely have any control and it spits out an entire, possibly mediocre song. It’s the same vein as ChatGPT image generation vs. Stable Diffusion, where you can do much more controllable inpaints with the latter.
Nicotine itself is carcinogenic in the mouth:
Nicotine in tobacco can form carcinogenic tobacco-specific nitrosamines through a nitrosation reaction. This occurs mostly in the curing and processing of tobacco. However, nicotine in the mouth and stomach can react to form N-nitrosonornicotine, a known type 1 carcinogen, suggesting that consumption of non-tobacco forms of nicotine may still play a role in carcinogenesis
They're not very skilled
I kind of understand where they come from: science vulgarization in pop news has been riddled with misinterpretation or lack of depth which can mislead the general public.
God fucking damn it send me a PDF with a QR code like a reasonable human being
You may have untreated myopia, or need to use a bigger font size (HN is guilty of this!)
:(
We don't call Google a monopoly, because there is Apple We call that a duopoly, which is similarly bad as a monopoly.