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williamtrask

Re:No Signs of AI Payoff Outside the Tech Sector on Saturday October 24, 2026 @04:40PM (#50225020)
"You are not at the beginning of the curve like you were in the"

Note: on an exponential, you can always say this. People will look back on today with the same "aww cute" eyes.

Re:YC's Biggest Scandals on Sunday May 10, 2026 @05:28PM (#48088265)
The scandals/year page has a little more umph to it than the main page https://ycombinator.fyi/timeline
Re:Local AI needs to be the norm on Sunday May 10, 2026 @05:26PM (#48088243)
Yeah... probably right. I do hold out hope that this is mostly a timeframe thing. Like, the library, printing press, etc. all had their moments of centralization. But eventually they federated.
Re:YC's Biggest Scandals on Sunday May 10, 2026 @03:48PM (#48087185)
fwiw - i think the design looks good.
Re:Local AI needs to be the norm on Sunday May 10, 2026 @03:47PM (#48087171)
I wonder if a popularization moment for local AI will ultimately be the pin-prick that pops the AI bubble. Like the deepseek or openclaw moments but bigger/next.
Re:Ask HN: What are you working on? (May 2026) on Sunday May 10, 2026 @03:45PM (#48087152)
A non-profit to deconcentrate power over AI through better infrastructure for external auditing/oversight, and better infrastructure for local/federated inference/training https://openmined.org/

Also, we're hiring engineers and PMs (the eng position is about to be up). https://openmined.org/careers/#brxe-zgsziy

i like your comment better than mine. more please.
i'm not sure it's productive to think this way. senators could be making more money on prediction markets. they took a nice step which will lead them to make no money on prediction markets (less money overall). it also sets a precedent which could easily be applied to the stock market.

what you're saying is probably on the mind of at least one Senator, but all things considered, this feels like a net-positive move which they didn't have to do.

Re:Mike: open-source legal AI on Thursday April 30, 2026 @01:34PM (#47965744)
Sometimes I find joy in noticing the importance of comma placement:

Everything the incumbents ship, in an open codebase your firm owns.

vs

Everything the incumbents ship in an open codebase, your firm owns.

Re:Decentralized AI in 50 Lines of Python on Wednesday April 08, 2026 @10:46AM (#47690988)
<3 - have ambitious plans to release a new video/blogpost each week, but that's pretty ambitious we'll see
Re:A website to destroy all websites on Thursday January 01, 2026 @07:34PM (#46459937)
...with a price :)
"Conclusion Our monorepo isn't about following a trend. It's about removing friction between things that naturally belong together, something that is critical when related context is everything.

When a feature touches the backend API, the frontend component, the documentation, and the marketing site—why should that be four repositories, four PRs, four merge coordination meetings?

The monorepo isn't a constraint. It's a force multiplier."

Thank you Claude :)

tried searching for "noodlesUK" and didn't find anything meaningful
Re:A History of Large Language Models on Thursday October 09, 2025 @04:48AM (#45525135)
Nit: regarding (2), Phil Blunsom did (same Blunsom from the article, and who was leading language modeling at DeepMind for about 7-8 years). He would often opine at Oxford (where he taught) that solving next word prediction is a viable meta path to AGI. Almost nobody agreed at the time. He also called out early that scaling and better data were the key, and they did end up being, although Google wasn’t as “risk on” as OpenAI on gathering the data for GPT-1/2. Had they been history could easily have been different. People forget the position OAI was in at the time. Elon/funding had left, key talent had left. Risk appetite was high for that kind of thing… and it paid off.
Re:Unlocking a Million Times More Data for AI on Thursday September 25, 2025 @12:01PM (#45374507)
"This is not the reason, the reason is that this data is private. LLMs do not just learn from data, they can often reproduce it verbatim, you cannot give medical records or bank records of real people, that will put them at a very real risk."

(OP) You make great points. I think we're actually more in agreement than might be obvious. Part of the reason you need to "give" data to an LLM is because of the way LLMs are constructed... which creates the privacy risk.

The principle of attribution-based control suggested in this article would break that principle, enabling each data owner to control which AI predictions they make more intelligent (as opposed to only controlling which IA models they help train).

So to your point... this is a very rigorous privacy protection. Another way to TLDR the article is "if we get really good at privacy... there's a LOT more data out there... so let's start really caring about privacy"

Anyway... I agree with everything in your comment. Just thought I'd drop by and try to lend clarity to how the article agrees with you (sounds like there's room for improvement on how to describe attribution-based control though).

Re:Unlocking a Million Times More Data for AI on Wednesday September 24, 2025 @08:30PM (#45367753)
With you on this one. I do think ABC is a step in the right direction to improve things. <3
Re:Unlocking a Million Times More Data for AI on Wednesday September 24, 2025 @06:22PM (#45366662)
"The claim that humans need petabytes of data to develop their mind seems completely indefensible to me."

And yet every human you know is using petabytes of data to develop their mind. :)

Re:Unlocking a Million Times More Data for AI on Wednesday September 24, 2025 @06:21PM (#45366655)
I'm relatively close to publishing my PhD thesis which is broadly a survey paper of what you're describing. Will share (almost done with revisions).

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