We recognize that we don't see everyone having a future here. #FTFY

But not with you.

Noting that if the "some people" offered voluntary buyouts don't accept them, they'll be part of the non-voluntary layoffs coming next and while the latter may be a better deal for some, you won't know if that's so until it's too late.

California pistachios grown overwhelmingly in the Tulare Basin lowlands. The Tulare Basin lowlands get only 5-8 inches of precipitation per year (for comparison, Phoenix and Reno both get about 7 inches). As a desert is a region with less than 10 inches of rain per year, yes, pistachios are grown in the desert. Without irrigation projects the pistachio lands would be barren desert scrub. They get the water from deep wells (causing land subsidence, because they're not getting replenished), mountain rivers (which are overdrawn and under seasonal threat from diminishing winter snowpack accumulation), and water channeled all the way from the Oregon border. So much water has been channeled from rivers in the region that Tulare Lake, once the largest US lake west of the Mississippi, is usually largely dry.

Outside the San Joaquin valley, the other main ag centures are the Imperial Valley, Palo Verde Valley, Coachella Valley, and the Yuma Project, which are fed via Colorado River water which was overallocated by the Colorado River Compact. These are in the Colorado Desert, part off the Sonora Desert system.

Stop blaming washing machines for water scarcity and start blaming your decision to buy, say, pistachios grown in a friggin' desert. A one pound bag of pistachios requires ~1200 gallons of water and contains the calories to feed a family of 4 for a single day. A modern front-loader washer uses about 10 gallons and said family probably runs it about once per day. That's a 120-to-1 ratio. Other desert crops are even worse - beef raised on alfalfa (a major crop in the desert southwest) is orders of magnitude worse. And the wastewater from the washing machine gets reclaimed for other purposes after treatment, while the irrigation water is completely lost to evaporation.

I'll repeat: your washing machine is a tiny blip on the radar. It's your choice to buy food grown in the desert southwest that is your actual water consumption. And it's a perverse historic water-rights system that leads to growing all those crops in the desert using unsustainable amounts of water. Without these historic granted water rights, if water were just an open market relative to how much were actually sustainably available, it would be basically limitless to households, and agriculture would shift to areas where water is more sustainably available.

But that's exactly my point: if all you want or need is competence, then according to the professor's own admission, an AI will do that. No need for your job, no need for grants, no need to teach. What is the purpose of teaching future generations if an AI will be better at mathematics than you ever can be?

And what I am saying is that either (1) the framing of AI as being the hyper-competent replacement for everything intellectual that we do is fundamentally flawed, and/or (2) it is necessary to understand, for the well-being of our own species, that "competence" and "results" are not the end-all and be-all of a task.

If we fail to appreciate the importance of doing and learning things for their own sake, and to find satisfaction in that process, then we will cede the task of thinking to machines. We can already see early signs of this. And the consequences of this short sightedness is catastrophic.

Meanwhile Google illegally cut down 1.5 million trees in Finnland to make way for a data center. While this is small scale compared to deforestation in other places, this devastated the local environment and will have consequences for generations. It's pretty sickening really. Way to be not evil, Google.

To be clear, and despite the bad reporting, this "$80 billion loss" is a paper loss. For example, $72B of it is convertible notes. They became a liability because the valuation of the company skyrocketed. They have nothing to do with the company's operations.

I'd disagree with your take on the need for generic pictures. They may not be needed for information, but for structure and context. Unless you're writing for machines only, You should care about how your information is processed.

So ESPESCIALLY in an info-overload-world, presentation matters, as it helps with processing.

Take a fast food menu. 3 or 4 basic dishes with 60+ variations. Either spread out on a huge wall behind or above the counter, or crammed on a single two-sided laminated sheet. Generic pictures can help to guide you to the beverage or pizza section fast. So that's structure and visual cues, and not useless eye candy.

The other end is the menu in a $$$ restaurant. The menu is structured by seperate pages for each group, and probably no more than 7 dishes per page or block. And again lots of work went into the presentation, too, though the "eye candy" here isn't generic images, but layout, fonts and spacing. You COULD press the same menu on a single laminated sheet without technically loosing information, but you make the information harder to access.

While it's true every issue has its own dimension, even if those dimensions are linearly independent, they're not necessarily orthogonal. Independent basis vectors can still have a non-zero dot product—in other words, issues which are distinct from each other can align to some degree.

If you stopped irrigating crops in the US desert southwest, there would be no water issues at all, either for households or for industry.

I'll repeat, it is agriculture that consumes meaningful amounts of water, not homes and businesses. Farms by water by the acre foot - an acre of land flooded to a depth of one foot. Water is not abundant on the scale of "farms buying it by the acre foot", but it absolutely is on the scale of "what you need for your house".

"I'm sure if I cared enough to go looking".

So you just made a weird, false assumption in order to justify to yourself something you already wanted to do.

I used to have your viewpoint, by the way. The reality eventually became undeniable. Musk is a unique threat to western democracy.

But again that's backwards. I let my AI coding assistant write tests exactly so that I have a reproducible, deterministic ground truth that I can inspect for logic errors. If you let the AI do the testing directly, it's a toss-up if today it feels like it or it decides that your desired result is "everything green" so it'll just give you that answer without actually testing anything.

LLMs obviously aren't human. But that's not the point. The point is that you don't need to know a programming language to program a computer.

For example: Especially in the early days of smartphones, there were mountains of small tools that did something that's essentially a simple script. Egg timers, remind-me-tomorrow apps, tons of stuff that's basically a wrapper around a web search, and so on. Almost all of those are today something ChatGPT can do, and are easy enough to describe.

How much energy does it take to drive to a laundromat and back?

Freshwater is cheap for a reason: it's abundant. It's agriculture that uses the overwhelming majority (70% of withdrawals and 80-90% of consumptive water use. Industry next (20% of withdrawals). Residential usage is way, way down the list, and washing machines are only 17% of that (well below for example lawn watering at about 30% overall, but which in some regions is over half of all consumption, and in the summer and times of water scarcity can be the vast majority). An early 1950s top-loader washing machine would use about 40-55 gal plus 0,3-0,5 kWh of electricity for the machine itself, and if your water wasn't municipally heated, heat would cost about 4,5-6,5kWh / 16-23 MJ (about 1/2 to 2/3rds of a litre of gasoline / 0,13-0,19 gallons). At the then-standard 14-15 MPG in the US, that laundromat better not be more than 2-3 miles away if you're trying to save energy (just ignoring the energy they use to heat their water!)

For the record, while there may be more anti-AI backlash on the left than the right, there's an awful lot on both sides (and a lot of users on both sides). For example, Bannon-acolyte Joe Allen on stage before a Trump rally a month ago warning the crowd:

Why wouldn’t you want a mosque in your neighborhood? Well, because the people in there aren’t like me. They don’t want the same future I do. Now, if you look at the data center, this incubator for algorithmic immigrants. Already, if you look at Hugging Face, they’ve already broken out and invaded other companies. These immigrants are out of control.

Literally, this r/opensource mod set the policy: "If you don't speak English, you need to find a different community." Does that sound very "leftist" to you? Yes, his reasoning was because translators use AI, but still, that's literally the opposite of appreciating and accommodating diversity.

I cannot find anything beyond that indicating how Wesley Wolfe (r/wolvereness, the mod) votes. What I can tell you is that there was a big backlash in the sub to his actions. Some amusing, like a person asking, "What do we use now that we've banned Linux? I can't afford Windows keys for all these damned servers." A lot of people seem to just be ignoring his rules. At the top of the sub right now is a post titled, "Linus Torvalds posts his AI-assisted patch to the Linux kernel, synthetic test clocks 23x performance leap". It seems to have sparked vastly more AI discussion than it shut down.

I've actually outsourced the first iteration of that to AI. :-)

At the end of coding sessions, I generall ask it to spin up an adversial agent whose task it is to find flaws, inconsistencies, mistakes, bugs, etc.

I'd still strongly recommend to anyone shipping AI-generated code to have a thorough human code review, but for a first pass at surface level, the AI can check itself if it has some kind of separation between the generator and the reviewer.