i.e., welcome to Constitutional law, where divining the effect of a amendment written in 19th century prose lives and dies on jurisprudential philosophy, rather than decided case law. (Is that what you mean by the “(and common law?)” parenthetical?)
Fascinating to think about the logistics with avoiding ROM – model compatiblity must've been a PITA! I'm even thinking about how to identify models – I know there's a pre-Gestalt Toolbox routine that doesn't need any Toolboxes, I guess?
I would give my left leg to learn how the permissions system worked – do end users (and PHBs) get to edit the rules directly? I fully expect some HR ass to go:
> Also...these things tend to have fuckin terrible documentation. Good luck figuring any of this out. And you can't google it and your AI is just as lost as you
I convinced my boss to hire an intern for the summer to do this. They said: "wouldn't internship projects that involved actual coding be more attractive?"
I replied: "Well, they'll be having to do a lot of experimenting to figure things out..."
> I do not like the R language at all myself, but to be fair there are reasons it is widely used in higher ed.
In the same boat... from a PL perspective, yikes (especially the macro mechanism that somehow never seemed to be planned, but somehow exists). As a working statistician? It really does get work done quickly.
To pass inputs with complex unevaluated syntax, I've seen...
– ad-hoc string parsing (lavaan etc.)
– formulas (which somehow the tidyverse doesn't use),
– base R syntax manipulation by round-tripping between as.list and as.call;
– and whatever wheel reinvention with bizarre semantics that the tidyverse uses.
Even though I've dealt with this, I'm genuinely appreciative of requirements: out of many stipulations, packages that monkeypatch are prohibited (I have a few ones that add diagnostics to advance analyses), online API access needs robust error handling... and there is a conformance/diagnostic suite.
> Curing cancer is one of the only things I’d take a pay cut to do.
Send an email to this head-and-neck oncologist's lab. I saw a talk he gave at a Chicago-area national lab on open-source models for identifying malignancies in scanned pathology slides, and was smitten.
Which is why I pause when they say they're not looking for investor money – in medicine you'd at least have to phrase things in terms of "what already exists, and what's our contribution"? From that lens, I'm not sure what they're trying to contribute: instead of increasing the predictive value of full-body imaging, they're just making it cheaper?
> And Anthropic seems to be leaving OpenAI behind so there might be only 1 in the near future.
Well, in domains like SWE where Anthropic's putting in the effort. I don't they'll make the claims that OpenAI makes about how their models are pushing the life sciences forward, for example.