Curious why the large majority of the clips are about water. If that's spontaneous, maybe it's interesting psychologically.

If you walk very early in the morning looking for something to capture while everyone is asleep, chances are the water bodies (ocean, river, lake, ..) are somewhere you know that you can plan to go to, and also they are reliably in the same place - so if say you forgot and took dead batteries, your cable failed or you got the wrong mic, you can try again on the next day.

Capturing other things may be harder - a bird may not be there, the wind may change from day to day and so on. Water is usually satisfying to hear and a good subject to experiment and explore when you are beginning in field recording.

there's just more of them. the freesound api-based parser searches for tags related to nature•

Just want to point out this comment is highly ironic.

This is all a computer does :P

We need llms to be able to tap that not add the same functionality a layer above and MUCH less efficiently.

> We need llms to be able to tap that not add the same functionality a layer above and MUCH less efficiently.

Agents, tool-integrated reasoning, even chain of thought (limited, for some math) can address this.

You're both completely missing the point. It's important that an LLM be able to perform exact arithmetic reliably without a tool call. Of course the underlying hardware does so extremely rapidly, that's not the point.

The computer ALREADY does do math reliably. You are missing the point.

Could you explain why that is?

A tool call is like 100,000,000x slower isnt it?

No idea really, but if it is speed related I would have thought that OP would have used faster rather than importance to try and make their point.

It's both. Being dirrctly a part of it makes it integrated into its intelligence for training and operation.

That would be cool. A way to read cpu assembly bytecode and then think in it.

It's slower than real cpu code obviously but still crazy fast for 'thinking' about it. They wouldn't need to actually simulate an entire program in a never ending hot loop like a real computer. Just a few loops would explain a lot about a process and calculate a lot of precise information.

"This AI child knows about the world more than we do since it has been trained on the whole internet, but it doesn’t have millions of years of evolution, genes, or a nervous system to back up its morality and empathy. This means we need to install morality in AI from scratch. But how do we install something in a software system that we can’t even define ourselves?"

Two things jump out to me. First, there's a vast amount of information about morality in that internet-scale data dump. It's not some mystical thing orthogonal to knowledge, which ties directly into the second thing: maybe the author can't define it, but many others can and do, especially philosophers, though YMMV given which philosophy and philosopher.

viz: "What is morality, or ethics? It is a code of values to guide man's choices and actions—the choices and actions that determine the purpose and the course of his life. Ethics, as a science, deals with discovering and defining such a code."

There are different systems of ethics, and those themselves can be reasoned about. We should want one that values rational human life. And among that vast data dump, there's no doubt that those ethical ideas have been extensively written about - so it can be used as a reference point to actively emphasize and select the ideas.

Have you gotten any nastygrams from Wolfram about this? They're pretty protective of their IP. Not saying I think that it's some violation of it, but I could see them being alarmed.

And those are all auto-generated?

Of course they are not. That is the whole point.

The author confirms that they ARE, so what's your "of course they are not" about? You might have misunderstood my obvious meaning: is the output webpage fully generated without human tweaking just from the paper alone?

You asked that on a post with examples of data journalism articles which are obviously not AI generated. So when you say ask about „those“ it was clear to me that you meant these examples.

All of the links I posted were published before ChatGPT, no AI.

If by "auto-generated" you mean, does the LLM generate the output from the input, then yes.

Yes, exactly what I mean. Thanks.

I think this is extremely impressive if it's totally auto-generated. Is there any human guidance or is it completely automated - PDF in, web page eventually out?

Yea, I was surprised by the output myself. It's all auto-generated.

I'm considering some ways to direct the LLM but we're in this funny period where models are getting better on subjective things like look-and-feel. And if I direct too much, I may wind up over-fitting for today's models.

Fun hack, sure, but why on earth isn't the focus on porting the accounting data to a new, currently supported accounting system?

Based on some reading in a study group using both the Hays and Waterfield translations, I'd definitely recommend Waterfield over Hays.

Interesting. I have read quite a few translations of Meditations by Marcus Aurelius and also found a clear favorite. But I am actually not even sure which translation of Letters from a Stoic my current book is. I have just always liked the language in it.

This misses a hugely important advantage of C# in Blazor WASM (beyond the IMO obvious fact of the huge superiority of C# vs. JS/Typescript) - namely, the ability to use an enormous number of NuGet packages in your browser page. And that covers a very broad range of capability.

But why are you? Unless it requires interfacing with a JS library or some JS operation on the DOM, the goal of a Blazor app is to write in C#, not JS. What's your JS code doing that it requires passing C# objects to it? (That said, Blazor supports JS Interop, see https://dev.to/rasheedmozaffar/intro-to-js-interop-in-blazor...)