AI-assisted coding has been around for a little while now, and the gains people are claiming are absolutely massive. Yet where's the evidence? How come I haven't seen any meaningful change in any applications that I use on a daily basis? Where's the guy cranking out big new popular apps at an astonishing rate and just raking in the cash? The answer is simple: it's a scam. These claims are being made by people who are trying to get investment dollars, or who've received investment dollars and need to continually reassure their investors that the money didn't go to waste. Don't buy into it. At the very least demand some evidence.

The realism of that mission didn't have much to do with it being successful. It's not a documentary. It was essentially a Star Wars trench run, and they came up with it because it looked super-cool and worked for the plot. They did an excellent job of pacing that movie and building tension. We're told over and over again that the chances of success are slim. The second time I watched it, even though I knew what was going to happen, as they were approaching the coast I was still on the edge of my seat. That's hard to do.

No, that movie was about a bunch of relatable aspects of life. Pete's growing older. It realistically portrays the feelings a person has about passing the torch to the next generation. You have a lot of experience and you want to protect them from their own mistakes, but you know that you're not doing them any favors by holding the umbrella over their head. There's the regret over what could have been with Penny. There's the regret over what he did pulling Rooster's papers, even though it was Rooster's mom who made Pete promise to do it. And the competing responsibilities. These are all feelings that older people really have.

The first movie was aimed at teenagers, and it hit the bullseye. Those people are getting older now, and have a different perspective on life. I give the writers credit for creating a legacy sequel that follows up on a story with the same audience as the original, and keeping it relevant to them. They hit the bullseye again. If Disney had made this movie they'd want to rejuvenate the brand and make it cool for a new generation, and it wouldn't have worked as well as it did.

I like the idea, but from what I've read most of the plastic pollution in the ocean is actually fishing gear. I don't think making fishing gear out of plastic that dissolves in sea water is going to be commercially viable. The plastic they use for fishing gear is actually very expensive high grade plastic, and the ocean cleanup group actually collects it and sells it because it's worth money.

That's because Top Gun: Maverick is the last Modern Movie. Most of what they pump out now is Post-modern slop.

Don't forget "Mortgage-backed Securities"

There's absolutely no way that what they got out of the LLM was accurate. As humans we've been conditioned to view any output of a computer as infallible. I see that attitude in the people around me using LLMs right now in their daily lives. "It's really accurate," they say. But how do you know? Did you verify it yourself? Obviously not, because the entire point of using an LLM is that you didn't have time to do it yourself, so you clearly don't have time to painstakingly check it for mistakes. I suspect this is an investment company that's heavily invested in AI startups who is trying to prop up stock prices.

That's ridiculous. Nobody driving a stick is paying any attention to their cell phones, trust me.

If you thought users were frustrated with their computers and apps now, just wait until they have to spend hours and hours asking an AI to "fix" their app, only to have it create increasingly bizarre problems.

But what about the teaspoon full of plastics in our brains!

As someone who experienced this decline, I think the comparison to the Stanford Prison Experiment is very apt. It started out amazing and then became a private club for cruel people to claim their turf. But Stackoverflow is complicit in this. They actually encouraged it, not through the reputation system, but by specifically handing them the baseball bats they used to beat the newcomers with. Moderators were using any excuse to close new questions or shit on new users, even when just letting someone answer the question would have been both helpful and easy.

I maintain and develop on a large LOB application with many hundreds of thousands of lines of code. I find AI to be useless when trying to write a new function or class because it doesn't understand the architecture and structure of the codebase. Or maybe the context size just isn't anywhere near big enough. It also doesn't understand the specific aspects of the business that are important. We don't write our own accounting system because you can just buy one. But if you want to automate some process that's unique to the success of your company, there isn't going to be much out there in the training data for the LLM to draw from.

However, there are a lot of developers who spend most of their time writing greenfield code. Someone gives them an assignment or a contract that's very spelled out... "install a shopping cart on my such-and-such website". This is more like integration work and actual development. It's the same implementation repeated over and over for site after site. I can appreciate that this is an area where an LLM can probably provide a lot of value.

But not all developer work is so cookie-cutter.

You are naive if you think the Chinese grand strategies are about going green. They have huge unused solar farms up in the north/west which is unfortunately far away from where their industrial centers are, and they're over-producing EVs wastefully at a huge rate, which is why they're trying to dump them in foreign markets. They did it because they have to import massive amounts of oil from the middle east and it makes them strategically vulnerable to interruptions in that supply chain. Meanwhile they have massive reserves of coal for electricity generation, and they invested in solar so they can keep cars moving in the event of someone blockading their oil supply when they decide to make a move on Taiwan. There are two countries who could easily do blockade (USA and India), neither of which are on great terms with China right now, and there are a bunch of other countries that are investing in the ability to interfere with Chinese oil imports (Australia is one) just so they have some leverage over the Chinese when the start making moves in the area. Xi is certainly not making decisions based on what's good for humanity.

The Chinese government gave massive subsidies to those EV companies, and also massive subsidies to the battery manufacturers, which is why the Chinese EV market is so far ahead. That's a form of market interference, so the US and EU responded with their own market interference in the form of tariffs to level the playing field. Losing their domestic auto industry would be a big strategic loss. These are the same factories that are converted to build military trucks, tanks, artillery and bombs in the event of a war.

Pay attention. We were talking about global research, not nation-specific research.

Worldwide we have an aging population and that means by definition that we're going to retire far more people over the next 10 years than we graduate from school. The workforce as a percentage of the population will decrease. The graduates of the next decade have already been born.

The point is that it'll force more of our resources towards paying for people who aren't participating in the workforce. Either we'll stop taking care of our elderly parents (not likely) or every other part of our society is going to be forced to take a budget cut. This isn't all just about luddites who don't want to fund research. This is about shrinking resources. We knew this was coming decades ago. It's not news. It's not surprising (except to the people who weren't listening). Most importantly there's absolutely nothing we can do about it. Demographics is one of the most predictive disciplines.

There will be less resources spent on research, whether we like it or not.