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donpark

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https://twitter.com/donpark http://blog.docuverse.com

[ my public key: https://keybase.io/superdon; my proof: https://keybase.io/superdon/sigs/x8N-xeM2DR6Qs9kHK_Sjoc0fGeYUZZpbtGwj1f4GzXg ]

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Let users flag toxic users. Use the resulting toxicity score to filter out messages based on each reader’s toxicity tolerance level. Both the toxicity score and the tolerance level are driven by user flagging, with score decay over time to account for improved behavior.

Decay and losses are just two of the many constraints that could be mixed like paints to create new systems.

Limitations, artificial or not, are not always bad. Walls, for example, can be seen as limitation or protection depending on how it's used.

That's a contract between users and HN. Airtrain is a 3rd-party.

If HN API exposes personal information publicly through their API then there is a problem.

And AFAICT the only way for HN to prevent user comments from being used by 3rd-party is preventing access to those comments, meaning a) sign-up will have to be more stringent and b) visitors will have to sign-in just to read (or scrape) comments.

Pricing doesn't look right, particularly the monthly subscription model.

What is the target market? Is there a hidden market where people need to create logos often enough to justify the subscription?

Data selection depends the use-case. Two contrasting use-cases I see are:

- Emulation

- Advisor

In case of MTG player emulation for example, I think it makes sense to group data by some rankable criteria like winrate to train rank-specific models that can mimic players of each rank.

I think OpenAI's founding nature is about research so it will disappear when it either runs out of key problems to solve or funds, whichever comes first. I see its commercial efforts as driven primarily to maximize their research runway. Operating ChatGPT commercially also helps research into ML-related UX and operational related problems.

That said, I cannot rule out purely commercial ventures with tenacity necessary to compete spinning out of OpenAI.

It 'feels like' like seeing. There is sense of dimension and position in the space and objects. I can imagine people I know and places I've been to with amazing details but visual details like texture are limited to where I'm focusing. Rest of the view is filled with 'feels like they are there'. It's not retrieval because when I try to focus on non-memorable parts of a face, I can tell that details are made up on-demand using common variety.

And what I 'see' is affected by light over closed eyelid as well as inner blood vessel, minor debris and micro organism floating over the cornea, meaning input from the eyes does play a role even with eyes closed.

While I have very vivid imaginations, I don't think I have photographic memory because what I can recall is rather too creative.

Svelte 5: Runes 3 years ago

Unless I misunderstood, Svelte 5 'runes' appears to be just 'markers' making explicit what used to be implicit with two noteworthy benefits:

- simpler compiler implementation - easier to identify moving parts

If so then the intro article needs a rewrite to be simpler without unnecessary districting details.

I agree that LangChain is pointless for experienced ML developers building products. For the rest, I disagree as just getting to the point where same observation can be made is worthwhile.

Respect is also a useful tool. It reduces conflicts just as diplomacy reduces violence. Yes, respect can be set aside but, when you do, expect controversy.

Why would anyone want to invite unnecessary controversy when writing a spec?

Transfer of ownership nor CC licensing explains the lack of attribution, a sign of disrespect and disregard.