ryandamm

There was a Supreme Court case that essentially established that Common stockholders can be practically ignored as part of leadership’s fiduciary duty. It revolved around an ex-employee suing for compensation for Common stock after a merger that paid out the CEO and preferred shareholders, leaving stockholders zero.

This is also partially why your common stock options can be valued significantly less than the price the company value would imply: because it’s not an even share in the business.

That's why you should prefer LPIPS to PSNR. LPIPS is a learned metric that uses subjective human input.

That said, it's limited due to the training set, iirc. So we still use PSNR regularly — it's an easily-understood metric with widely-understood limitations, which is in practice not too bad. Devil you know, etc.

“The world can remain irrational longer than you can remain liquid.”

Curious if the authors are hanging around here and how they feel about the recent Leiden Statement. (Late in the article it’s clear that this is at least partially a publicity effort around a new AI math tool, if I’m reading it correctly.)

On a personal level I’m very excited about AI getting good at math, but I’m a consumer of math, not a creator. My job gets easier as AI gets better on this front, so I can’t fully empathize with mathematicians who feel threatened or are worried about the sanctity of the discipline.

Your comment prompted to look into this further, thank you. The funding situation in California is complicated and weird, but yes, CA does spend a lot of money on public education.

There are weird relics of the underfunded past, but you can’t blame the educational failures on lack of budget.

Well I live in a basic aid district; Bay Area but firmly middle class. We’re just above the cutoff for federally subsidized school lunches iirc, and the schools are chronically short on money.

Part of it is declining enrollment, part of it is Baumol’s cost disease (a living wage is pretty high here! Teachers get paid well on a national scale and very poorly on a local scale).

But yeah… education is simply not well-run in California. I find that pretty indisputable.

This is interesting news to me, thank you. I'm curious if the per-pupil spending includes locally raised funds; the reality in California is that the state level funding is poor, and districts that are above some threshold don't get enough funding to operate. So public schools function as local charities and inevitably have fundraising arms to make up the shortfall. This has been true since at least the 1980s when I was in school, and is definitely still true today.

This already happens — my district when I was in school, and my son's district now, both have / had "alternative" high schools that kids get transferred to when they're struggling. Kids who are dropping out inevitably get transferred as part of the process; the high school they were originally attending has stellar graduation rates. The alternative high school has miserable graduation rates, but no one really cares.

Did people really believe this was a financial behemoth? Or was this just a larger bet on the conglomerate that is Musk’s quasi-meme-stock empire?

In his interview on the Hard Fork podcast, Palo Alto Networks’ CEO described the capability change from Opus to Mythos being more about availability; evidently it runs in a very compute-intensive, always-on mode. Unclear if the base model is significantly different, but Arora ascribed the difference mostly to that change.

In case anyone is wondering why this is important: the spherical harmonics are frequently most of the data in a Gaussian splat data set — as much as 80% of the data for good quality scenes.

The magic of Gaussian splats is their ability to render photorealistic outputs without material properties, explicit ray tracing, etc. They do this by synthesizing complex light transfer in the scene via these fuzzy blobs overlapping — but they need to be able to change color and transparency with view angle to recreate much of that light transport. Hence, relatively heavyweight data.

There are many approaches to reducing the data volume, and they get increasingly complex when you add a time component. Not even worth listing publications here because it's changing so quickly, just plan to look at the SIGGRAPH pre-prints in a couple of months. Exciting times!

It's worth signing up for Levine's free newsletter and listening to the podcast (though there is substantial overlap in the content, it's still fun to hear what you've already read).

His take on this, crypto, all things Elon Musk, and the current 'predictions market' are funny and insightful.

Because it acquires an asset worth roughly that much, it’s neutral. GME is (probably!) not doing a huge at-the-market offering, they’re creating the shares and immediately giving them to eBay shareholders.

In practice the price paid for the company being acquired is usually a bit higher than the market value (so the shareholders take the deal), and the market usually punishes the acquirer a bit and the resulting entity’s stock will fall a bit. (This is most definitely not investing advice.)

This is not atypical; smaller company “buys” the larger company with debt on the larger company’s books. The blended shareholder mix is mostly the larger company; management comes from the smaller company.

The one I was most familiar with was the Discovery “acquisition” of Warner Brothers. Though apparently that’s a little complicated because AT&T was divesting itself of Warner.