thousandautumns

Last November, DeepMind released the results of a generative AI model that created theoretical molecular structures for over 2 million undiscovered synthetic materials. Within days, materials science researchers were able to confirm 700 of them. The sheer number of these new potential materials discovered is greater than has been created in the rest of human history combined. These are materials that can be used in manufacturing, energy production, and other objectives that are critical not just for advancing human society, but avoiding the impending crisis we are already facing.

Similar AI endeavors have been underway for medicine and human health.

The author is making extremely shallow, flawed arguments that hinge on an ignorant (or possibly, deliberately narrow-minded) understanding of what generative AI is, how it is already being used, and the magnitude of what is already being achieved with it.

> We urgently need the expertise of social scientists to be able to make much-needed collective decisions about the future of generative AI that we want; we can’t leave it to business, markets or technologists.

> Kean Birch is director of the Institute for Technoscience & Society at York University.

Academic sociologist argues that AI should be controlled by academic sociologists. Color me surprised.

Southern Indiana has lots of hills and forested areas, including the Hoosier National forest. The Great American Rail-Trail mostly goes through the upper third of the state, however, so you miss that and are mostly in the corn belt section of the state. Its very flat and mostly farm land. Which is likely why the railways were built on that route anyways.

I personally can find flat farmland quite beautiful, but I can imagine biking through it for days might get dull.

Must vary widely, because I went in August and there was 0 line at all. A lot of places are on Spring Break in the US right now, so that may contribute to your experience.

I'm not sure millenials or Gen-Xers are any less materially obsessed, I think we just generally have less money to spend on the things Boomers did. It isn't like we aren't spending thousands on tech, clothing, etc. I hesitate to condemn Boomers too harshly for their lifestyle choices given the benefit of hindsight when I'm sure my generation will also be pilloried for the aspects of lifestyle we are living that will later be seen as moronic.

More like lol at assuming your rent doesn't cover the other expenses of owning a house. You think your landlord is just taking the loss? When you rent, you are paying, if not directly, for every expense associated with the house, plus extra for the landlords profit margin.

Landlords absolutely incorporate home repair costs into rent. I'm shocked at the number of people who assume that landlords just eat the cost of maintenance. Just because you aren't forking over the money directly to the repairman doesn't mean you aren't paying.

Its Brazilian Ju Jitsu, for those wondering.

God I hate this paper. Perhaps it was relevant at its time. But that was 18 years ago. The described dichotomy between the "two cultures" isn't nearly as pronounced, if it even exists, today. There are few statisticians today who adhere entirely to the "data modeling culture" as described by Breiman.

I'm surprised how often this paper continues to get trotted out. In my experience it seems to be a favorite of non-statisticians who use it as evidence that statistics is a dying dinosaur of a field to be superseded by X (usually machine learning). Perhaps they think if its repeated enough it will be spoken into existence?

> I am not an expert and am still reading thru the article, but why is it such a strong dichotomy?

There isn't. This paper is nearly 2 decades old and isn't nearly as relevant as you would think given how many times it gets trotted out. Any statistician under the age of 45 would not recognize the two cultures as they are described here.

> The standard best practices in STATS 101 is to compute R^2 coefficient (based on data of the sample)

> Null Statistical Hypothesis Testing (NHST), another one of the pillars of STATS 101

Best practices of statistics and what is taught in Stat 101 are not remotely the same thing. The problems with R^2 and NHST have been well documented they've been argued against for decades by the statistics community. But actual statisticians make up a small proportion of statistics practitioners, as statistics is the backbone of nearly all modern science. What gets taught in Stats 101 is not the "foundations of statistical best practices" so much as "a system of guidelines and rules of thumb that have been simplified greatly for the sake of the lowest common denominator". To make things worse, non-statisticians seem to over-estimate their statistical knowledge and prowess after having taken a handful of introductory stats courses more than any applied field I know of.

Only now after the magnitude and pervasiveness of the replication crisis has begun to be recognized by the broad scientific community are people starting to realize what many statisticians have been pointing out for years.

Too many excellent excerpts in this article.

> “It’s such a strange service — who wants to be in the cold? You need to hear about it from someone you trust,” said Michael Garrett, the head of Reboot, a spa that offers cryotherapy around the Bay Area. (Cryotherapy is when you make yourself get cold.)

And? The arguments about marketing are completely non-sensical. People treat pharma companies marketing budgets being as large as they are as some indictment of the industry, but its not like they are just throwing money at marketing because they like to burn cash. Money spent on marketing is money that the company has determined will result in a greater return in sales and is therefore a calculated investment. If the company were to learn that their marketing was more costly than the money it generated, they would be eager to cut back on marketing. The revenue then available for the company to use for operating expenses, including R&D, is therefore greater than it would be if the company conducted no marketing.

There are plenty of arguments to be had about how the pharmaceutical industry operates and how/should they be regulated in ways that other industries aren't, but the idea that marketing budgets are the reason for high drug prices is moronic.

You also see this kind of argument against housing a lot, which also ignores that housing is one of the few highly leveraged investments an individual can/will make, and that even if you don't buy a house you will have to pay for housing, all of which goes to someone else's pocket.