djehuti

Fair. I think it's important from an "Is this True AGI?" sense to distinguish these, but yes, in the colloquial sense I guess the system could be said to understand, even if it's not strictly the actual LLM part that does it.

No, they really don't. They answer you with words that are commonly found in conjunction with calendars. There is code in Siri that understands calendars, but the LLM part ain't it. I have, ahem, firsthand knowledge of how Siri does this.

What LLMs do has nothing to do with understanding. There's no there there.

Now Target owns them, I think.

Wow. I must have an older Shark; mine comes off with three coin-turnable plastic bolts. Collectible! (I have two!)

The best example I have is a closed source one and I can't be more specific on what it is than to say that it's probably installed on at least one of your Apple devices (assuming you have any).

Implementation-wise, the syntax tree nodes have additional attributes that hold pre- and/or post-element text. What's on disk is the serialized tree. You edit a text version, and it's parsed on every edit so it doesn't have to be parsed again at evaluation time, and what's stored is the parse tree with enough whitespace and comment hints to reconstruct the text for editing.

This is a case where looking at the textual code is rare, but hundreds of results must get updated in realtime on every change. This might be enough of a hint as to what program it is.

I run the AIO master container, on a NUC (4-core i5, 32G). Family use; never any load issues.

Or by including comments in the parse tree. (& Yes, it is done various places for various languages and formats.)

I dunno. That could be kinda snappy on a map. "Ok, let's see, here we have the North Atlantic, the Sargasso Sea, and the Fuckass Gulf of America."

He'll make tens, if not dozens, of dollars.

Hobbyists do lots of stuff that companies won't.

When your favorite sports team's stars are younger than you.