donpark
donpark on Hacker News
Worse, data-driven. They researched what fat people preferred and concluded they prefer fat.
From the final notes section of their announcement blog post:
> One last thing: we're going to open source Kitesurf once we're ready — hopefully soon. Our goal is to let any customer deploy their own version of Kitesurf on their own accounts, if they want to.
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.
I suspect this CLI madness is just a phase, but if the trend continues, I trust AI agents to handle the necessary rewrites.
But I've read somewhere that KV cache for speech-to-speech model explodes in size with each turn which could make on-device full-duplex S2S unusable except for quick chats.
It’s just a technology that can be used for both civilian and military applications, not only by private entities.
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.
It's because AI is useful enough despite its current limitations.
Developers work with what we have on the table, not what we may have years later.
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.
KAIST is a top-tier South Korea university focused on science & engineering.
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.
Leaking original data would expose the company to direct copyright violation lawsuits. Changing T&S is simplest way to stave the legal risk exposure, buying time to implement technical remedies.
As ridiculous as it may seem, they're doing the right thing.
How does this differ from similar techniques previously applied to DNA and RNA sequences?
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.
Think about aging population. As to privacy, same problem exists with taking phone calls in public yet we somehow manage just fine.
Another good article on the subject:
Is the Kalman filter a low-pass filter? Sometimes!
https://jbconsulting.substack.com/p/is-the-kalman-filter-jus...
PS: I've used it to remove jitter in virtual camera movement while cropping video around faces in real-time, streaming detected face locations to a Kalman filter worker and get back stream of stable camera locations.
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.
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.
Very likely. Typical serverless hosts like Vercel times out at 5 minutes.
With me, it was around 5 years ago although first inkling started w/JSON support 8 yrs ago.
Pair junior developer with a senior, starting with an hour every other day.
I had more problems with junior developers who think they're senior developers (some experience, high-confidence) bc they don't ask for help when they should.
Importance of a feature depends largely on use-cases.
Chat is not just for business. Its use-case existed even before notion of business came to be.
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.
He is now asking. Are you saying it's too late?