u/PracticlySpeaking

Counterpoint:

House 1 - This is a greedy owner, probably an 'accidental' landlord with limited experience, exploring least-effort vs most-profitable. Could work out, but there will certainly be hassles later.

House 2 - A very popular property where they are struggling to deal with the volume of applicants. Yes, it can be like that. Pay to play always sucks, even if the place really is that nice. Brokers on commission are effectively the same thing, btw, just with a friendly face hiding the fee.

House 3 - Definitely a nightmare avoided. Changing your move date costs the prospective landlord $$$$ (apologies won't fix that). You need to know your move date, but there's no excuse for verbal abuse like that.

Volunteer -> Meet people, Work with tools -> Learn.

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We have no education or experience requirements. We only ask that you be reliable, kind, and excited about our mission.

Sorry it's not *exactly* the thing you asked for — you might get more out of it than finding a class.

Good to know this is still a thing.

Is there a particular local / oss classifier that you recommend?

Was just looking at the workshop post about it.

Have you checked out Chicago Tool Library?

This

how do you handle the case where the people using it aren't the person paying

What are you asking here — is the question data segregation ('I can break things') or metering?

🤣

Hey, now — plenty of us real people like em dashes!

Have you found that Honcho personas do anything useful?

Anyone else — are there good alternatives, or is the 'secret sauce' Honcho's proprietary models?

FUD is dead, Long live FUD.

It was a few years ago, I was one of the first ones on my block in Logan to get Astound.

Their BS with sending a statement showing "paid" then just cutting it off with no notice happened twice in two years.

why are the tow truck companies that aggressive?

Mo tow, Mo money.

Count on JuliusP for the worst takes.

DCA has nothing to do with price up or down, only your cost vs current price.

THIS.

Case in point — they sent me a statement that my bill was paid, but it really wasn't because there was a glitch with the auto-pay. The next statement was like this... https://imgur.com/gallery/astound-ing-rate-increase-XQYM82W

Check this one... https://imgur.com/gallery/astound-ing-rate-increase-XQYM82W

surprise fees, or billing headaches

Absolutely plan on these.

Twice there was a problem with my auto-pay - two years apart. Twice they sent a statement saying my bill was paid, then cut off my service with no notification. Hours on the phone where they refused to re-run the payment, insisting on a different one.

The second time... https://imgur.com/gallery/astound-ing-rate-increase-XQYM82W

Awesome, thanks

This is a good point — a human intern would probably take more than a few months to become second-brain-level useful.

Memory systems also matter a lot. If you want your agent to "get to know you" (and maybe other people), look at ones like Honcho that actually identify and maintain profiles of "who" they interact with.

GLiNER is for Named Entity Recognition — language processing, not decisioning.

Because LLM vs System One is what matters to anyone actually running anything.

Congratulations, you have mastered the obvious — Clef is more expensive than Jev!

Anyone running at scale today was also running at scale two weeks ago. And two weeks ago, they were using an LLM.

You are still trying to make a distinction without a real difference.

$0.001 is 10x $0.0001

Both are a trivial cost.

I wouldn't read too much into the wording.

Yes, classifiers do the same job, but they do it differently and at different levels. The 'need fine-tuning' is generally true for BERT and other generic classifiers trying to make context-specific decisions.

The examples that I have seen are like "does this code affect authentication" or "is it part of a PR" — BERT is never going to be able to ingest a repo and answer questions like that.

The System One models are also multi-modal (or, some of them — not Jev). This is why one of the early demos was playing Doom — lots of decisions, all visual.