61 karma · joined May 27, 2020
I find it interesting that LLMs seem pretty good at spitting out SQL that works well enough. But on the other hand LLMs seem pretty awful at working with CSS. I wonder if this is due to a difference in the amount of training data available for SQL vs CSS, or is this because CSS is a finicky pain in the ass when compared to SQL.
However I've come to the conclusion that LLMs are terrible at decision making. I would much rather have an intern architect my code than let AI do it. It's just too unreliable. It seems like 3 out of 4 decisions that it makes are fine. But that 4th decision is usually asinine.
That said, I now consider LLMs a mandatory addition to my toolkit because they have improved my developer efficiency so much. I really am a fan. But without a seasoned dev to write detailed instructions, break down the project into manageable chunks, make all of the key design decisions, and review every line of code that it writes, today's AI will only add a mountain of technical debt to your project.
I guess I'm trying to say: don't worry because the robots cannot replace use yet. We're still in the middle of the hype cycle.
But what do I know? I'm just an average meat coder.
I'm guessing that the answer is "not much" since deer lineup too and they (probably) don't have magnets in their stomachs.
I still think this deserves the Mythbusters treatment, right?
https://www.npr.org/2009/03/16/101945271/power-lines-upset-c...
My understanding is that this is because the denim is stacked and then die cut in the factory. Since denim is highly deformable, the cut outs from the top of the stack are not the same size as the cut out from the bottom of the stack. And this can lead to considerable size variance within the "same" pairs of pants.
That's why it's a good idea to try on two pairs of the exact "same" pants if the fit is close, but not quite right. YMMV.
Furthermore, Edmunds tested the Teslas at temperatures that are roughly 14F lower than the 68F used by the EPA. This can make a big difference in the range you get.
My point is that these articles are acting like they are comparing apples to apples--the EPA test vs the Edmunds test--but they're not.
I admit that I'm a Tesla fan and shareholder. But my first loyalty is to the truth. Ding Tesla and Elon when they mess up. Nobody is above reproach or constructive criticism.
So let's not pretend that Edmunds (or The Drive for that matter) are either. Edmunds ran what appears to be a not very scientific test, and came to a highly debatable conclusion that Tesla vehicles don't meet the EPA mileage guidelines. I think the tests are not comparable. Maybe that's just me.
[1] https://www.fueleconomy.gov/feg/pdfs/EPA%20test%20procedure%...
Two ideas to consider: (1) give option for one time purchases (2) raise your price (I'd pay more)
Good luck!
1) It solves many different universal, infrastructure-level problems. 2) More people are using containers. K8s helps you to manage containers. 3) It's vendor agnostic. It's easy to relocate a k8s application to a different cluster 5) People see that it's growing in popularity. 6) It's Open source. 7) It helps famous companies run large-scale systems. 8) People think that it looks good on a resume and they want to work at a well known company. 9) Once you've mastered K8s, it's easy to use on problems big and small. (Note, I'm not talking about installing and administrating the cluster. I'm talking about being a cluster user.) 10) It's controversial which means that people keep talking about it. This gives K8s mind share.
I'm not saying K8s doesn't have issues or downsides.
1) It's a pain to install and manage on your own. 2) It's a lot to learn--especially if you don't think you're gonna use most of it's features. 3) While the documentation has improved a lot, it's still weak and directionless in places.
I think K8s is growing more popular because it's pros strongly outweigh it's cons.
(Note I tried to be unbiased on the subject, but I am a K8s fan--so much so that I wrote a video course on the subject: https://www.true-kubernetes.com/. So, take my opinions with a grain of salt.)
Once you know K8s, it's not very difficult to use. Plus, it provides solutions to a lot of different infrastructure-level problems.
I still recommend demo magic. But use it with eyes open if you're mistake-prone like me.