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There is a natural tendency to hype basic research as having human applications because perhaps that will attract funding. But most of us are reading science news without any practical use for it. It's useful to have a succinct reminder to avoid getting too excited about it.

Wouldn't at least some shipping companies have the technology to track their trucks pretty closely nowadays?

They do. But the LTL trucks are easy to load and unload.

So you have tracking devices in the cab, the trailer, the pallets, and the boxes, and things STILL disappear.


With the low cost high quality cameras and broadband mobile communications, it seems almost impossible to not be able to hold a specific person accountable at each transfer.

Haiti is a weird choice. There are much nicer places.

Also, moving to a different state in the US is a lot easier.


It should be a federal law, no sheltering behind any states.

This essay is unnecessarily gloomy because it doesn't talk about success stories. For example, it's well-known that many vaccines work very well. It's not that hard to find interventions that work outside of psychology and education.

Without mentioning Effective Altruism, it explains why it's important. Yes, there are a lot of expensive, failed interventions out there.

If you want to fund something that works, the simplest way is to copy GiveWell's answers.


The owners of existing data centers might make more money if new data centers are blocked, because there is currently plenty of demand and they will have less competition. Or maybe not. There are a zillion other considerations like this. Do you really think you can figure it out?

For retirement savings, index funds are hard to beat, and it's hard to say whether tech stocks should be over- or under-weighted compared to the index. Tech stocks went down recently, but maybe it's a good time to buy? People who invested in 2008 did well.


Design is sometimes important, but what we might call product-market fit (for a "market" of one) probably beats it. Sure, a calculator app is generic so you might as well use one that's well-designed. If there's an existing app you like, it's probably not worth rebuilding it. But personal apps can do things that an off-the-shelf app won't do.

I recently used a coding agent to build a TV-like YouTube player for my mother, who is quite elderly. It's inspired by channelsurfer.tv, but runs on the Google TV Streamer in my living room. Unlike any set top box I've seen, it has on-screen diagrams that tell her which button to press on the remote to change the "channel." It doesn't have ads. The UI will never change unless I ask the AI to change it.

You can't say that about most apps in an app store. They will do a UI redesign and you're out of luck if you preferred the old version.

Do you really think Google or Apple or anyone else will build this app? Maybe some self-hosted media box out there would be similar, but I can't be bothered to search for one and I'm doubtful that any of them were designed for an elderly parent who isn't good with technology. It's still work in progress, but at least she can use a single remote to turn the TV on and watch TV without being bombarded with things she doesn't understand and doesn't care about.

There are downsides that make this app less compelling for other people, but I didn't build the app for them.


If I ask an AI for help to download some public data to make a graph, and then I publish the graph on my website, is that consuming or producing? Seems like both?

For me at least, an AI "produces" when it makes meaningful decisions. Do if you found the data, understood it, chose how you wanted it presented, but got the AI to write the code that generated the actual graph, then the scope of AI decision making is relatively small - it's reasonable to say that you produced that graph (with AI assistance). But if you got the AI to find some data that supported your article and present it as a graph, then it's making pretty much all the decisions there - which data set to use, how to graph it, even which parts of the article to support with that data. That's an AI-produced graph, for me at least.

Not a very well accepted or reasoned Philosphic counter answer, but to keep it simple, current LLMs consume information and regurgitate it without understanding.

So they currently sit somewhere in the neighborhood of the infinite monkey theorem. Toward the better side of it than pure Random. But you need to take that with a grain of salt with things leaking out about human intervention, and the Hallucinations we still get.


It consumed the data and you produced the graph.

It wrote all the code. I asked for changes and edited some of the text to reduce slop.

You have a deterministic path from published data to graph output which you signed off on, and the AI wrote the code. In my view the AI did not produce the news any more than the script did.

You’re being obtuse. The code generated the graph. The LLM generated the code. The transitive property does not exist here.

Writing the prompt is producing?

> If I ask an AI for help to download some public data

They only describe the LLM as helping withdownloading data, this means the creation of the plot could be done by hand.

I agree that the rest of the post then proceeds to ask a question in a way implying the machine also created the plot, but that's not actually in the stated premise.


Everytime i see the "?" on this website i just know im about to read an "add nothing, teacher look at me" kind of question.

We all know the specific situation matters, we already know, we also know thats not what we are talking about.


What information is it producing in this instance? More like transforming

Do you have a source for that? The linked article just says “certain existing stockholders.”


Technically true, but while they might not be onscreen, sometimes you have a thousands of rows that the user can scroll through, and each row might have multiple input widgets. A UI framework should have a good way to handle large scrolling lists.

There are also photo apps where you can scroll through decades of photos.

Also, text editors should be able to handle large files, and filesystem widgets should handle large directories.


AppKit had ways of handling this 30+ years ago. NSTableView can easily handle millions of rows.

I wonder if Regulation E has anything to do with slow adoption of new tech that's a fraud risk?

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