mvcalder

I’ll share a story. I wanted to make dxf files for some decorative metal gussets I needed for a project. I find CAD programs unintuitive and tried to use Claude as a tutor. That was a fail, it seemed to assume I was more knowledgeable than I am. So then I tried to describe what I wanted and have it emit python to draw it. Again a fail, it didn’t interpret my descriptions accurately and lacked aesthetic sense. Then I had Claude implement a simple DSL that captured my sense of the geometry and form I was trying to express. I ended up wth a very bespoke Logo like language that did exactly what I wanted. I believe there’s a larger lesson there in AI interaction.

This passage from Trading Bases by Joe Peta chokes me up everytime.

> There's an expression on Wall Street, often attributed to Warren Buffett, which goes, "They don't ring a bell at the top." There's tremendous wisdom in that adage, because while in retrospect it's easy to pinpoint the day that the market (or even a specific stock) reached an all-time high that looks unlikely to ever be attained again in the foreseeable future, at the moment it happened it was impossible to recognize. That's because, unlike market bottoms, which usually have a crescendo feeling to them accompanied by investor panic, a market top generally passes without fanfare, indistinguishable from the series of tops that preceded it.

> You know when else they don't ring a bell? For parents, they don't ring a bell the last time you read Goodnight Moon. They don't do it the last time you watch Sleeping Beauty and they don't do it the last time you help your daughter put on the same article of clothing she's wanted to wear every day as a toddler. Instead, a couple years after the fact, you find the book on a shelf, the DVD in a box, and the tights with the pink ballerinas on them in the back of a drawer. You can't for the life of you remember the last time you read the book, danced to "Once Upon a Dream" with your daughter on your feet, or helped put those tights on. But you do know that now she reads to herself at bedtime, she dances, alone, to Taylor Swift, and the tights—well, the tights wouldn't even make it over her knees.

There's a story sharing the front page right now about scaling laws, so it's not an unreasonable assumption.

https://news.ycombinator.com/item?id=48689744

Wait, my job is not cushy. I think hard all day long, I endure levels of frustration that would cripple most, and I do it because I have no choice, I must build the thing I see or be tormented by its possibility. Cushy? Right.

I really enjoyed the article and want to both praise and encourage the author.

You get it. It’s about value. Keep you eye on that north star and you won’t go wrong.

Whose value? How do I value? Can I reconcile disparite value? Yep, those are the right questions.

For me, I read this and want to give a shout out to Zen and the Art of Motorcycle Maintenance, but that’s just me.

I enjoyed the read, thank you.

It’s not “freedom of speech I agree with”, no one needs protection to speak agreeably.

My Massachusetts home has both radiant floor heating (water pipes in floor) and baseboard water pipe heating (separate part of the house). My son’s New York home has radiators driven by hot water. I can’t recall a home where heating was vented air and not circulating hot water in North East USA.

Nope, all human all the time.

“They say sixty-five percent of all statistics Are made up right there on the spot”

https://www.youtube.com/watch?v=IUK6zjtUj00

And there’s only one photon, vibrating like mad, singularly unable to contemplate its own magnificence.

It was an odd sight at that hour of the day. I wanted pictures as something to talk about with friends. I really wish I had been astute enough to take video.

I read several comments referring to: idiots, morons, delusional, and hysteria.

At the risk of being labeled a kook or an idiot, I photographed drones flying over my suburb of Boston neighborhood a few weeks ago. This was about 6am, definitely drones not regular aircraft. I assumed it was something flying out of Hanscom or the city mapping streets. And yes I took photos not video, sorry.

https://photos.app.goo.gl/Lwfn134LqdEp6xbG9

For the experts in the house: would it be possible for this to wrap around, so the highest and lowest level join? A torus of GoLs? Can such a thing, assuming it exists, have a finite number of layers? Just curious, this is amazing.

Does anyone know what the copyright status of LLM generated content is? That is, if I feed a NYT article into GPT4 and say, summarize this article, and then publish that summary, is there argument or precedent that says that is or is not copyright infringement? Asking for a friend.

I wrote up this analysis of cache one-hits after reading the FIFO is all you need paper.

https://www.polyscale.ai/blog/one-hit-expectation

Disclosure, I work at PolyScale.

Prepared statements work fine. Views can be tricky.

The statistical invalidation will in general disable caching on views since their results will change without any corresponding writes (because we only associate writes with the backing tables of the view). Currently our best answer to views is the new stale-while-revalidate flow which revalidates against the db while still serving a hit. With this feature enabled, one can turn off invalidation (if the resulting eventual consistency is acceptable).

More details about how invalidation works here:

https://www.polyscale.ai/blog/approaching-cache-invalidation...

Whenever this topic comes up I like to provide a citation to some work I've done:

https://towardsdatascience.com/gradient-kernel-regression-e4...

Not out of vanity (ok, a little) but because I think the idea has importance that has not been fully explored. The article's Bayesian perspective may be the whole story but somehow I don't think so. Unlike the article's author, my work left me feeling model architecture was the most important thing (behind training data) whereas they seem to feel it is ancillary.

If you, like me, often find yourself covered in pine sap. The product: Shout, for removing laundry stains will make quick work of removing sap from skin. Maybe the answer to your chemistry question is in there.

One of my favorite things to do in museums is to use Google Translate on artifacts. I find it so exciting to point my phone at a 500 year old vase and read what it says. Here are a couple examples from a trip I tool to the British Museum, it handled the Arabic and Chinese pretty well but the Rosetta Stone's Greek stumped it.

[1] Arabic: https://photos.app.goo.gl/jQw3QCdC5PrWQGkr9 [2] Chinese: https://photos.app.goo.gl/dXhsH7Xq6zpFS6Eq8 [3] Greek: https://photos.app.goo.gl/DBGWCDd8EhzuB2y67

I can't speak to the others, but pgvector indices can "break" hybrid queries. For example, if you select using a where clause specifying metadata (where genre = jazz) and order by distance from a vector (embedding of sound clip); if the index doesn't have a lot (or any) vectors in the sphere of the query vector that also match the metadata it can return no results. I discuss this in a blog post here [1].

[1]: https://www.polyscale.ai/blog/pgvector-bigger-boat/

Blog post about using PolyScale with pgvector.

Bruh

Professors Boyd and Vandenberghe really broke ground with this text. Prior to this, optimization algorithms and methods were very much locked up behind a metaphorical paywall: difficult to access literature with very high barriers to entry, and strictly commercial software offerings. They brought optimization to the masses and should be celebrated for it.