My semicolon usage generally seems to vary with the language I am writing in. In C++, there seem to be quite a few. In python, very few. In Rust, somewhere in between. English is just a python-derived language.

Ho hum. Another article in a newspaper. Yes, at least the New York Times quotes some people who might know something. But this is not peer reviewed, rehashed garbage, and there appears to be nothing that has not been said in the last year. Of course the other comments I am reading are along the lines of "LLMs aren't AI, they never will be." Though most people were good enough to not say "never." I think this is both silly and probably wrong. We don't know when GAI will come, but just like with chess and go, it appears like a computer can "never" do something until suddenly, it can. There is no discussion here of why a neural network is any different than a physical neuron. I don't see why an "artificial" neuron is different than a wet one. Right now, the number of inputs is typically up to 1024, while physical neurons have more like 100k in our cerebral cortex. So there is a scaling issue. I think that as soon as we scale up neural network another couple of orders of magnitude, we will see further emergent behavior. It might take an improvement in training algorithms, but maybe not. Exactly when this happens is hard to predict, but anywhere from 10 to 50 years seems like the outer limit. Anyone saying it can't happen simply lacks imagination. This is not a linear process.

I used to ask lots of questions on stackoverflow. I answered quite a number at first also, but then the topics I knew were mined out. Even so, I was in the top 4% by asking great questions that would over time, get voted up. Today, I can get a lot of simpler questions answered faster with chatgpt, but when I am stuck, when I really want a human, they are always way more interested in playing gotcha and downgrading my question. They have such a narrow idea of what constitutes a valid question, and even when some people are willing to answer, I have had people delete their answers (fortunately I saw one first). The site is dominated by assholes trying to prove how smart they are. And the people running the site think they are absolutely right, so when I complained on meta, they basically agree with the way it is. This is exactly analogous to a restaurant which hires servers who are nasty and sarcastic, then acts surprised when people stop coming.

In some ways I like Duolingo. It is a great platform for drill and I have tested it on a range of languages. I definitely improved my French. But quality is already pretty low even before this announcement. They make mistakes, they create ridiculous, annoying sentences (that may be deliberate, since it garners publicity and some people like it). I don't mind being taught (Portuguese) how to say "My elephant drinks milk" but once you have it down, you really, really don't need to go back to it quite so much. Similarly in French the nonsense phrases about Bozo the clown are really annoying. There is no real way to complain, they aren't going to fix their bugs, everything is automated. Duolingo could be a lot better, and I don't understand how they can't review their materials with humans to fix the stupidity, it just isn't that expensive. It's ok to generate course materials with AI. But having no human editor, at this stage, generates an inferior product.

More efficient than traditional construction by hand, sure. But why on earth would you use a 3d printer to print individual houses when you can just fabricate pieces and lift them in place with a crane? If there is an advantage to building on site, then a mobile fab in a trailer, but molds, prefab walls, are much, much better. I am much more excited by panels being produced in a factory with a waterproof/fireproof layer, insulation, structures, these are fundamentally better than just squirting out concrete. You can see demos of houses that fold out, or just panels that are assembled onsite. Either way, I don't see that the printer is all that efficient. Yes, it prints fairly fast but you have to move it to each new house. Whereas if you have a factory, you can crank out modular panels 24 hours a day and ship them. It doesn't seem to make sense to build entire modules though, unless they are all identical, like on a ship or prison. Because the modules are typically big and bulky to transport. And the form factor means you have to limit the size of rooms according to the geometry of the container. But mass production of standard units that are assembled like Lego, that seems way, way better. My favorite is when the article talks about a chinese printer bragging that it is using industrial waste in the concrete -- just what people want to live in close proximity to...

Microsoft has always had code generators, wizards, etc. because the underlying code is poorly structured, inefficient, wildly complex. And Microsoft has orphaned many of their APIs over time, which is another reason to never invest in learning anything they do. So aside from general lack of quality of Microsoft software, it isn't a surprise there was a code generator that would generate some cases, but that's not even close to general programming. I'm sure if you asked it to do something it wasn't programmed to do, it would do nothing.

You can drop your LDL by way more by eating a bowl of oatmeal in the morning, taking phytosterols, lots of easy interventions. While interesting, playing up the title just plays to alcoholic tendencies.... And of course, smoking in bed can completely solve cholesterol.

Just yesterday Taiwan announced that they are outlawing Deepseek due to security risks, even though it is supposedly "open source." Open Source in an AI is meaningless, unless the training data set is open sourced. That allows us to repeat the training, and develop competitive models that are better. Without the training set, it's analogous to someone publishing the instruction set of a server, and allowing you to run the code remotely but not giving you the executable. It's meaningless. Yes, you can run the program repeatedly and try to figure out what it does, but you will never be able to prove you know everything, and testing is ridiculously expensive.

I assumed that open source meant that the code for deep seek is open source, and that the procedure to train it is laid out: Here is the terabytes of data, and you run the training algorithm and out pops deep seek 7 If that's not true, and only the code is open, then that barely counts because a vast majority of the result is the training set. It makes sense that it's not open, because if it were open, there wouldn't be arguments about the training data scraped from chatgpt. They would simply have each question and corresponding answer, and that would be the training data. It wouldn't be in dispute.

What do they mean "first nuclear battery?" I seem to remember seeing this on slashdot: https://en.wikipedia.org/wiki/... The chinese betavolt has been available for a while, and it was a spinoff from research done somewhere else. I didn't look at the specs, and it sounds like this one is better, but it certainly isn't the first. This article talks about thousands of years, which sounds a lot better than the 50 year lifespan of the chinese device. Of course this one is barely out of the lab, and the article smells like bullshit.

classic idiot CEO burning money while the ship is sinking. Whatever money was spent on this idiocy should a) have been spent on one more developer and b) should be taken out of the CEO's salary.

I just tried, and chatgpt works just fine with the request. What chatbot are you talking about? Tell me about David Mayer, the historian who was mistaken for a Chechen terrorist ChatGPT said: ChatGPT David Mayer, a British historian, became involved in a peculiar case of mistaken identity in the 2000s. He was erroneously identified as a Chechen terrorist due to a mix-up with someone who shared his name or had a similar identity marker. This confusion led to complications during his international travels and raised concerns about the accuracy of global security databases and watchlists. The incident gained media attention because it highlighted the potential for errors in security systems relying on shared names or incomplete data. It underscored the challenges of balancing effective counter-terrorism measures with the protection of innocent individuals’ rights and reputations. Mayer's case serves as a cautionary tale about the unintended consequences of data mismanagement and has been cited in discussions about improving intelligence protocols to avoid such errors. If you'd like more details about this or similar incidents, I can look them up for you.

I wonder what the CEO's salary is. In non-profits, all the employees get screwed because "we don't have the money" but the people at the top are always exempt, and almost always are the cause of most of the problems.

And shove every one up the CEO's ass

There isn't a roadmap to fully electric cars, let alone trucks. There isn't enough lithium-ion capacity yet, and other technologies aren't mature. I suppose it's possible that battery companies would get it going by 2035, but I think you have to make sure there's sufficient capacity before you do that. It's also currently very energy-intensive to build a fully electric vehicle. Wouldn't it be better to mandate hybrids or electric, since hybrids at the moment are more energy efficient for the first 300k miles, and let the grid and battery technology catch up, then go all electric?