I recently wrote a very esoteric Python script. 100 lines of code. No classes, no functions, but yes argparse.
I've tried out the latest open source models on the task. They go bananas. It's like Enterprise fizzbuzz (https://github.com/enterprisequalitycoding/fizzbuzzenterpris...). They love classes and imports and reinventing the wheel. A great way for me to tell trash AI slop code is it'll define a useful constant then 15 lines later do it again with a different name.
They love making code that looks impressive. "Wow look at all the classes and functions. It's so scalable. It's so dynamic. It validates every minutae against multiple schema and solves a problem I never thought about." But it was trash code. One really was 400 lines and it didn't even look like it would work. Can't even imagine what it means for 4.5M moderately good human lines to become what? 27M fluffy filler repeat lines that don't even make sense?
Yeah maybe I need to do the old "you are a veteran engineer" nonsense. I've had some success telling it to implement everything it suggests and be production ready. I hate when it takes a shortcut and says I'll have to change it. That's kinda the whole point of me not writing the code...
Agreed. Last time I was sick I said my fevers were pushing up to 100 and they said it's not a concern until 100.4. felt like an odd number. It's 38 C. Because my dramatic undersampling of my temperature was 0.4 degrees lower than their rounded threshold through some unit conversions, I clearly didn't have a fever. That's not a very human touch
Maybe you had trouble re-reading your own comment but I can tell by how you responded here (a cascade of links/references) and a snarky comment ("I can keep going if you'd like") that I'm sure the doctor was glad to be rid of you.
You didn't say the doctor disputed you had a fever. You said the doctor told you the fever wasn't concern until 100.4. Which I'm guessing is your fault for misinterpreting. If you google around, it's very easy to see the fever thresholds.
Here, I'll even paste a summary for you, and I can keep going if you like:
Key Temperature Thresholds
- 100.4°F : The standard definition of a fever.
- 103°F : Contact a healthcare provider
- 104°F : Seek medical attention, particularly if it does not come down with - treatment.
- 105°F : Emergency; seek immediate care.
In one of your own links (clevelandclinic.org), here's an excerpt for you:
When should a fever be treated by a healthcare provider?
In adults, fevers less than 103 degrees F (39.4 degrees C) typically aren’t dangerous and aren’t a cause for concern. If your fever rises above that level, make a call to your healthcare provider for treatment.
They aren’t objectively incorrect. You are conflating two things:
- You aren’t considered to have a fever until you get to 100.4. Anything less than that isn’t considered a fever, let alone a concerning one
- A fever isn’t considered concerning (ie dangerous) until it reaches about 104. Anything between 100.4 and 104 is just a regular fever and isn’t considered concerning.
A fever is 38c, great. What the parents said was that you may have misheard because a fever isn't serious until 104. Which is line's up with the language you used.
> and they said it's not a concern until...
Parent is not suggesting that a fever isn't at 100F, they're suggesting that it's not "a concern" until 104F, a number strangely similar to 100.4 that you claim you heard, presumably, while you had a fever.
Not sure I agree with your second sentence, at least in the US. I may see "cheese product" or "dairy product" or "cheese flavor" but if it says real cheese, it's real cheese. My favorite example was seeing "onion (then in tiny text 'flavored') rings"
It may be real cheese, but the cheese may not be where you expected it to be. A friend of mine was served a snack pack on a flight that had some breadsticks and a cheese dip, and the box said it was made with real cheese.
She read the ingredients list and found that the real cheese was part of the breadsticks. The cheese dip had no cheese.
We should just put non-dairy on all beverages that are non-dairy. Non-dairy Mountain Dew. Non-dairy sweetened lemon beverage. Non-dairy gin. Non-dairy water.
Should probably also mark gluten and lead while you're at it, among other things. Also what about radioactive isotope content? We know how important that is thanks to Intel.
Do we know how many people were in the community? Maybe I missed it in the article? 2000 people worth it food a day is hard to put into perspective otherwise. Though it's all very impressive regardless
Based on 20g rdv, they could be estimating ~40kg of rendered fat for 2000 servings. I can't tell from the wording whether they don't know the population and are implying that's a possible maximum or are just trying to relay the observed production capacity.
Look into pre-Colombian grease trails, which we have much better logistical records for.
It's an important point. I went from 4c/8t and 32GB to 16/32 and 96GB. Dramatically less memory per thread. Some software (looking at you, Vivado) can take incredible amounts of memory per parallel job thus mandating some projects can only run with a subset of my cores. At least until I stepped up my work laptop to 10.66 GB/thread. That seems to be manageable
Yeah, ignoring the whole fragmentation that keeps happening on the desktop stack, The Year of Desktop Linux will never happen if only computer nerds get to build such systems, as it has always been.
Instead normies get The Year of Linux kernel deployed with all kinds of consumer devices, and The Year of Linux VMs on retail.
I think for real cables the delta could also be explained by damage or just a bad plug-in attempt, so even if you're not trying to detect counterfeit cables it could be useful to know:
I recently wrote a very esoteric Python script. 100 lines of code. No classes, no functions, but yes argparse.
I've tried out the latest open source models on the task. They go bananas. It's like Enterprise fizzbuzz (https://github.com/enterprisequalitycoding/fizzbuzzenterpris...). They love classes and imports and reinventing the wheel. A great way for me to tell trash AI slop code is it'll define a useful constant then 15 lines later do it again with a different name.
They love making code that looks impressive. "Wow look at all the classes and functions. It's so scalable. It's so dynamic. It validates every minutae against multiple schema and solves a problem I never thought about." But it was trash code. One really was 400 lines and it didn't even look like it would work. Can't even imagine what it means for 4.5M moderately good human lines to become what? 27M fluffy filler repeat lines that don't even make sense?
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