I work at a pretty progressive company (comparatively but definitely not perfect) and DEI there has nothing to do with preferential treatment, nor does it need to be.

The fact is that if you want to hire the top X people in the labor market, but your hiring and business practices exclude, say, half of that market, you absolutely will not get the actual top X. You will have to reach deeper into your half and be forced to pick people that are less qualified and/or capable.

So DEI, at least where I’m at, is about widening that pool so that you can actually get top talent. That means reevaluating your business practices to figure out why you’re excluding top talent. Maybe your recruiters always go to specific colleges for recruitment and certain websites. Maybe just the way they’re talking to candidates is more attractive to a certain type of person. Maybe you’ve got hiring requirements and an interview process that is not actually predictive of success. Maybe candidates are looking for some benefit that you’re not offering. Everything needs to be looked at.

For example, “Women just want more flexible working arrangements so that’s why we can’t get them” is something I hear often. Well, have you actually evaluated why your company is so inflexible? Is it actually necessary? Or are your executives a bunch of people who learned how to manage in the 20th century and haven’t changed since then? Maybe there are things you can do to enter the 21st century and make room for more women, not just because they’re women, but because you gain access to people who are actually better at their job than the ones you’ve had. Not every company can be supremely flexible, of course, but the number of times that inflexibility is actually necessary of much smaller than its prevalence.

The demographic breakdown of your workforce is a quick and easy weathervane to help figure out how these efforts but of course they’re not everything. Diversity comes in maybe forms, not just skin color and genitals. But in my company they’re used in a backwards looking manner, to see how new policies are working, not for quota filling and preferential treatment.

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That’s… the point? Civilizations with that kind of tendency may very well destroy their planet and/or themselves long before they advance to the point where they are detectable to an outside observer many light years away.

The human race is at the moment in a race against time. We’re hoping that we can develop new technology to save ourselves faster than we destroy everything around us. This kind of race has probably happened countless times across the vast universe and perhaps the laws of physics ultimately make the race unwinnable. These laws limit how much technology can do for any species, no matter how smart, so it would be a universal filter.

If the only way to win the race is to slow down the destruction of the environment to the point that the species is undetectable, that solves the Fermi paradox.

ITT: A bunch of people who have never heard of information theory suddenly have very strong feelings about it.

Models are not improving? Since when? Last week? Newer models have been scoring higher and higher in both objective and subjective blind tests consistently. This sounds like the kind of delusional anti-AI shit that the OP was talking about. I mean, holy shit, to try to pass off “models aren’t improving” with a straight face.

Love that the picture associated with this article is Trump staring into the eclipse. Fucking moron.

If we’re in a simulation, it’s probably a massive universe-spanning one. We’re just a blip, both within the scale of the space of the universe and within the history of time of the universe. In that case, we’re not important enough for a simulation creator to even care to adjust our capabilities at all. They’re not watching us. We’re not the point of the simulation.

It can’t be expressed in any integer-based notation without an infinite number of digits. Only when expressed in some bases which are themselves, irrational. It’s infinity either way.

The number which famously has an infinite number of digits? I thought we were arguing against the real-ness of infinity.

Also note: the method I was describing is one of the ways in which pi can be calculated.

It destroys meaningful operations it comes into contact with, and requires invisible and growing workarounds to maintain (e.g. “countably” infinite vs “uncountably” infinite) which smells of fantasy, philosophically speaking.

This isn’t always true. The convergent series comes to mind, where an infinite summation can be resolved to a finite number.

It’s quite useful, though, to understand a curve or arc as having infinite edges in order to calculate its area. The area of a triangle is easy to calculate. Splitting the arc into two triangles by adding a point in the middle of the arc makes it easy to calculate the area… And so on, splitting the arc into an infinite number of triangles with an infinite number of points along the arc makes the area calculable to an arbitrary precision.

Is enshittification the scummiest thing you can think of? While other multinationals are paying for goon squads that kill people in other countries? While banks reorder daily transactions from largest to smallest so they can charge more overdraft fees, literally stealing from poor people? Even if enshittification is literally your biggest problem, you’d have to be living under a rock to think Google’s products are the most enshitified of all the garbage out there. You’ve never heard of anything from Meta? Amazon? Netflix? Microsoft?

I don’t know man. There’s a lot shittier business practices out there than paying to be the default search engine - which is laughably easy to change on any browser. Like marketplaces and services that pay to be exclusive sources of content and then use the fact that they’re the only source for most content to force extortionate deals on content creators and enshitify every aspect of the end user experience. Just to name one.

I think also one thing to remember is that phonics and word sounds are not reading either due to the fact that English is a Frankenstein language where any letter or combination of letters often has a myriad of ways of being pronounced. You cannot learn to read without a healthy dose of memorization and contextual cluing. Letters are, at best, just another clue as to what the word could be.

I have a son that’s learning to read right now so I’ve got some first hand experience on this. This article is making a lot out of the contextual clues part of the method but consistently downplays or ignores that phonics is still part of what the kids are taught. It’s a bit of a fallback, sure, but my son isn’t being taught to skip words when he can’t figure it out.

He’s bringing home the kinds of books mentioned in the article. The sentence structure is pretty repetitive and when he comes across a word he doesn’t know he tries to look at the picture to figure out what it is. Sometimes that works and he says the right word. Other times, like there’s a picture of a bear and the word is “cub” (but I don’t think my son knew what a bear cub was), he still falls back on “cuh uh buh” to figure it out.

So he still knows the relationship between letters and sounds. He just has some other tools in his belt as well. I can’t say I find that especially concerning.

Because even if it winds up being a bad study, it still evokes a deeper, more important “truth.”

I’m being sarcastic but that’s actually what’s going on here.

Brother, if you can’t even get a sizable chunk of people to join you now you sure as fuck aren’t coming out of an armed revolution on top. There’s no shortcut to going where you want to go. You gotta put in the work to convince people at the ground level.

It’s like the dumbest version of the trolley problem where the tracks are reversed. You could do nothing and people will die. Or you could pull the lever (convince a bunch of people not to vote for Harris) and a lot more people will die but, hey, at least you can say you did something.

No mention of Gemini in their blog post on sge And their AI principles doc says

We acknowledge that large language models (LLMs) like those that power generative AI in Search have the potential to generate responses that seem to reflect opinions or emotions, since they have been trained on language that people use to reflect the human experience. We intentionally trained the models that power SGE to refrain from reflecting a persona. It is not designed to respond in the first person, for example, and we fine-tuned the model to provide objective, neutral responses that are corroborated with web results.

So a custom model.

When you use (read, view, listen to…) copyrighted material you’re subject to the licensing rules, no matter if it’s free (as in beer) or not.

You’ve got that backwards. Copyright protects the owner’s right to distribution. Reading, viewing, listening to a work is never copyright infringement. Which is to say that making it publicly available is the owner exercising their rights.

This means that quoting more than what’s considered fair use is a violation of the license, for instance. In practice a human would not be able to quote exactly a 1000 words document just on the first read but “AI” can, thus infringing one of the licensing clauses.

Only on very specific circumstances, with some particular coaxing, can you get an AI to do this with certain works that are widely quoted throughout its training data. There may be some very small scale copyright violations that occur here but it’s largely a technical hurdle that will be overcome before long (i.e. wholesale regurgitation isn’t an actual goal of AI technology).

Some licensing on copyrighted material is also explicitly forbidding to use the full content by automated systems (once they were web crawlers for search engines)

Again, copyright doesn’t govern how you’re allowed to view a work. robots.txt is not a legally enforceable license. At best, the website owner may be able to restrict access via computer access abuse laws, but not copyright. And it would be completely irrelevant to the question of whether or not AI can train on non-internet data sets like books, movies, etc.