Though the chance someone other than you dies from you taking a shit is pretty far fetched, and I’m not liking having to try to conceive of how that happens.
But a lot of activities are this way. Getting on a ladder in public could kill someone, just breathing around other people could kill someone, etc etc.
But what about monster HDMI cables?
Well, driving to work is basically that. Non zero chance someone dies.
Also, a bunch of shit is about ready to burst out because they somehow decided to use wallpaper to hold a bunch of stuff to the wall instead of putting it in a closet. But it looked fine in the moment, so decided it was good enough.
So being drunk affects how you use light/dark mode?
Based on my experience with LLM and developers I personally know, my only assumption is they don’t have the skills in the first place…
In corporate world there are a lot of “developers” that actually act kind of like codegen. They just throw plausible sounding bullshit into an editor and hope for the best. Two examples:
Once asked to help a team speed something that ran slow, even by their low standards. Turned out they had made their own copy file routine instead of using the standard library one, and sucked the file into memory, expanding array 512 bytes at a time, and then wrote it out, 512 bytes at a time. I made the thing nearly instant by just making it a call to the standard library function to copy a file.
While helping with a separate problem, I noticed their solution for transferring some file with an indeterminate version number in the middle of the file name. It was a huge mess, but the most illustrative line was the line in their Java application declaring a string “ls /path/with/file|grep prefix.*.extension”…
Lots of human slop out there that AI can actually compete with.
I just don’t get it, even the purportedly best models screw things up so much that I can’t just leave them to the job without reviewing and fixing the mess they made… And I’m also drowning in pull requests that turn out to be broken as it proudly has “co authored by Claude” in it… Like it manages to pass their test case but it’s so messed up that it’s either explicitly causing problems, or had a bunch of unrelated changes randomly.
I feel like I’m being gaslit as I keep reading that there are developers that feel they successfully offloaded the task of coding.
Closest I got was a chore that had a perfect criteria “address all warnings from the build”. Then let it go and iterate. Then after 50 rounds each round saying “ok should be done now, everything is taken care of, just need to do a final check”. It burned though most of my monthly quota doing this task before succeeding. Then I look at the proposed change… And it just added directives to the top of every file telling the tools to disable all the warnings… This was the best opus 4.6 could do…
Now sure, I can have it tear through a short boiler plate and it notice a pattern I’m doing and tab through it. But I haven’t see this “vibe” approach working at all…
While CATL has done work and has made real world solutions, I wouldn’t take their marketing material over the broader scientific consensus.
I am totally willing to buy that the market ends up between NMC and Sodium with LFP left behind despite having some advantages over sodium. Of course as solid state becomes a thing, that will be more of a factor than Na v. LFP v. NMC.
I think I’ll need a citation, from what I can find, the LFP chemistry still is more dense than CATL sodium, which makes sense because, well, the physics are what they are, sodium is about three times more massive than lithium. The best argument I could see on this point is debating whether there’s a space in the market between sodium and NMC for LFP (if you are already compromising on density, then what’s another further compromise to get the other qualities you mention for sodium).
less performant
Well this is a matter of how you define “performant”.
It’s got lower energy density, which is generally considered a critical measure.
No no, he said “rated for atlantic crossing”, so it’s got to be good, right?
Technically over a decade, but feels like that’s an understatement.
In the 1940s some people called a machine to play NIM as “Artificial Intelligence”. People talked about opponent AI in checkers games before most of us were born.
Certainly by the 80s using “AI” to describe the manipulations of enemy characters was all-in.
there is no ballast, not even a dedicated bilge space, and with the shallow draft, I am uncertain how the boat in OOP isn’t too top-heavy to stay up-right. Forget the “Sovereign Living” bit at the end, I’mma need to see some solid design and build data before listening to another word from that guy.
Don’t worry, he said up front it is “rated for cross-atlantic” so it’s all good.
Frankly waiting for the news story where he gets killed “proving” his concept…
The first warning bell was “rated for cross-atlantic”… “rated” by whom?
Of course then there’s the latter part where he talks about the next one is going to be super amazingly polished autonomous vessel with everything up to and including a sauna from the solar… And of course the sovereign citizen take…
Cool doing a project like this, but it smells of overconfidence in what it currently is and how trivial it will be to get to something much much more…
Welcome… to rapture!
Yeah, but the real developers regard it with disdain. I guess he thinks its only an image problem and a rebrand will fix it.
I’ll say “vibe coding” to me implies the operator has zero awareness of the actual code, and there is something wrong.
They treat the actual program logic in the same way folks treat assembly code as some arcane black magic they don’t have to think about. Problem is the tooling is not nearly so deterministic as a compiler, and the output is just too bad to be relied upon.
For certain clasesses of tasks, it may do a serviceable job, maybe at first. If you have ongoing evolution requirements, it can dig itself a whole that it can’t really dig out of. It can’t process the code that had been generated to extrapolate a code change to match the change request.
The GenAI coding needs supervision, and ‘vibe coding’ implies opting out of careful supervision.
This is just so fitting.
I keep getting merge requests now from people that their whole job to date had been too scared by the syntax to try coding.
It’s almost always a shotgun of way too many lines of code changed for a small thing, often with horrible side effects that would be unacceptable.
Someone wanted to tweak the CSS layout of one element, what should have been a one line change. The pull request had hundreds of css changes, basically touching everything. Clearly the model had started changing things and he kept saying it didn’t do it yet until finally it did and it never rolled back anything it did, including many of the rules being repeated 5 times in a row in the same place…
They felt like AI was making them so helpful because they could submit a code change directly instead of just asking for what they want. They proudly said “AI told me:” and then explain the brilliance of the AI finding. One time the AI finding was addressed over 6 months prior, the AI never thought to update the software, but instead proposed a really crap workaround that would have failed to cover a whole class of similar scenarios while simultaneously imposing crazy side effects on scenarios that weren’t tested.
I can use AI too, please just send me what you would have sent to the AI, and if AI can do it, I could use the AI. If you think the AI will figure out how you are using something wrong and don’t want to bother/wait for a human to help, fine, but if it gets to what it thinks is a software bug, just rewind and start from your problem statement when you come to me…
The plague of work chats now:
Here’s what ChatGPT/copilot had to say:
People can ask for themselves, you answering that way adds no value. Just say you don’t know.
In group chats, keep your mouth shut and let people that actually know answer. Don’t drown out the actual expert answers.
And holy hell the ones that will die on the hill that they are right because chatgpt agreed with them even when they are totally wrong…