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dev_hugepages

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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.

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.

How LLMs work 2 months ago

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.

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..."

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.

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

Keep Android Open 9 months ago

We don't call Google a monopoly, because there is Apple We call that a duopoly, which is similarly bad as a monopoly.