The thing about language models is that they are *language* models. They don't actually parse XML structure, or turn code into an AST, they are just next-token generators.
Individual models may have supplemented their training with things that look like structure (e.g. Claude with its XMLish delimiters), but it's far from universal.
Ultimately if we want better fidelity to the concepts we're referencing, we're better off working from the larger/richer dataset of token sequences in the training data--the total published written output of humanity.
Just the opposite! When sautéing, too-small pieces have burned by the time the larger ones have cooked, giving the dish a bitter burnt flavor and ugly black flecks.
I made my own version of this a while back, and it lets you create your own cutting methods, plot the statistical distribution, and share your ideas via permalink. It also lets you tweak onion parameters, such as number of layers and the layer thickness distribution curve).
Along the way I discovered two things:
1. I came up with my own method ("Josh’s method" in the app above) where the neither the longitudinal cuts nor the planar cuts are full depth, so the number of cuts at the narrower core is less than at the wider perimeter.
2. After all this hyper-optimization about size, it turns out what really matters when cooking is the THICKNESS, since ultimately determines the cooking rate. The only way to avoid thin outliers that burn long before the rest are cooked is to discard more of the tip of the onion, where the layers are the thinnest.
The 3D version of the simulator is still in progress--turns out 3D geometry is a lot harder than 2D. :)
My thought is just to rent it out for to rich folks with lawns for a few hundred bucks a week. My contraption will have thermal detection, AI target discrimination, and precision targeting with a laminar flow water stream. That’s the plan, anyways.
Likewise but for raccoons. Are you precision targeting or just broad sprinkler coverage? I need to make sure my cat doesn’t get hosed :-/
I got a cheap MLX90640 off aliexpress for target detection and a grove vision AI V2 module to use with IR cam for classification/object tracking. Esp32 for fusion and servo/solenoid actuation.
Knowing how so many devs are hungry to move to the new shiny thing, the question is often more like "why hasn't this been rewritten in Python3 already?".
Possible answers:
• Legit technical or cost/benefit reasons
• Probably a good idea but no budget/time for the effort
• Somebody already tried and it was a disaster
• No manager has been stupid enough to humor the devs
It's kind of an old-school tool, but Enterprise Architect is a tool that does just this. It's also a completely overwrought model-based engineering thing but ignore that and it's a useful systems/data architecture model database tool.
Hey I can't actually PM you but my email is in my profile.
It's a super-common dictionary word and is the brand of a very-well-known media company.
(my friend has a local business that's been an active and legit user of the name since 1994, and will have to give up serious local SEO/brand value to sell)