I was on-site for users learning our new program. Watched them do something, a dialog came up, and faster then i could catch what it was, they closed it. Dialogs are warnings or confirmations you know, and they did not know what it was…
So yeah, sometimes I do think there should be a wait time on the OK button.
I’m not saying there will be mass deportation, indefinite detainment, and possibly executions of unwanted people, but they sure are lining up for it. For example ramping up execution of sexual predators, while at the same time labelling LGBT and drag as being predators, just for existing near children…
Like if Elon is a nazi, then we may very well see a DOGE squad hunt down “un-American” people in the darkest timeline.
I don’t think it will happen, and especially not for something this high profile, but Jury Nullification is essentially the “he did it, but we don’t see his actions as punishable”. It’d be a huge uproar if that happened too.
How do you view diffs and merges when you say you don’t use git GUIs? External tool or terminal/command line?
I use Jetbrains IDEs and most of my life has been IDE based git interaction. And I honestly love it, easy access to see my diffs, the most common commit, push and stage(or shelve as Jetbrains does it, which is better than visual studio). Hassle free and available beats writing anything to me.
My own disks won’t survive the house burning down, and while obviously feasible, aren’t accessible when I’m not home. I don’t need it often, but sometimes I do. But the extra safety of a cloud disk is nice.
Just got reminded of the silencer gun battle scene in one of the John Wick movies. That was perhaps the most unrealistic thing I’d seen in those.
What do you think the effective power generation and heat production is for whatever that reactor is producing, when not in a suit?
If memory serves correctly, the entire outer shell is a round metal cylinder, so that’s a fairly large surface area to transfer heat to the body. Tony might not need winter clothes if he’s got a portable heater in the chest.
If you use it frequently, I suggest getting a GUI that have profiles or remember options so you don’t have to mess with commands all the time. I wrote my own little command line wrspper which is Windows only since I don’t have Linux to test on. Though it shouldn’t take much effort to add support.
Makes it much more convenient when you don’t have to specify things like archive (ignore duplicates), filename to be “artist - title” (where possible), download destination, etc. Just alt-tab, Ctrl-v, Enter. And the download is running. And mine also has parallel downloads and queue for when you got many slow downloads.
Compute becomes cheaper and larger undertakings happen. LLMs are huge, but there is new tech moving things along. The key part in LLMs, the transformer is getting new competition that may surpass it, both for LLMs and other machine learning uses.
Otherwise, cheaper GPUs for us gamers would be great.
Didn’t want to install something to move stuff of my laptop yesterday. Took a USB which has both a boot partition and a data partition, which worked on my W10 computer and moved it to the W11 laptop and it wouldn’t recognize it…
Long story short, I had to manual set the partition id for the data part using diskpart for the data partition to be recognized. But that was a lot more effort than expected to move a few files over.
I actually decided to use avif on my project. But both this and webp is as fast as I know, not supported in any default image viewer on windows. Which is rater annoying, but I moved on to better programs for tgat anyways.
Avif is second to jxl though, some of the downsides of being a video format is that you loose progressive loading (only top to bottom iirc), degrades on re-encodes, and some other things I can’t think of. Avif gets a win because if you have a av1 decoder you already have a avif decoder too! But since it is a video frame essential there are some downsides since some image specific features can’t or won’t be added.
Quick google shows that Kanban is a method. Mainlu around picking up things as the come, but also limiting how much can happen at once.
The project I’m has a team that uses Kanban for the “Maintenance” tasks/development, take what is at the top of the board and do it. Adapt if higher priority things comes around, such as prod bugs. Our developments teams are trying to implement Scrum, where interruptions are to be avoided if possible during sprints. You plan a sprint, try to do that work, and can present it, and iterate when users inevitably changes criteria.
In the meme, kanban does somewhat make sense, since getting armrests is never going to get a high priority as part of building a rocket. Scrum isn’t exactly right, but I can see where it’s coming from. They are all agile methods though.
I kinda get where he is coming for though. AI is being crammed into everything, and especially in things where they are not currently suited to be.
After learning about Machine learning, you kind realize that unlike “regular programs” that ML gives you “roughly what you want” answers. Approximations really. This is all fine and good for generating images for example, because minor details being off of what you wanted probably isn’t too bad. A chat bot itself isn’t wrong here, because there are many ways to say the same thing. The important thing is that there is a definite step after that where you evaluate the result. In simpler ML you can even figure out the specifics of the process, but for the most part we evaluate what the LLM said or if the image is accurate to our expectations. But we can’t control or constrain the output to exactly our needs, because our restrictions largely are just input in a almost finished approximation engine.
The problem is, that companies take these approximation engines, put them in their product and consider their output fact. Like Ai chatbots doing customer support, and make up facts like the user that was told about rules that didn’t exist for an airline, or the search engines that parrot jokes or harmful advice. Sure you and I might realize that these things come from a machine that doesn’t actually think about it’s answers, but others don’t. And throwing a “*this might be wrong because its AI” on it is not an acceptable waiver of accountability.
Despite this, I use chatgpt and gemini a lot to help me program, they get a lot of things wrong but also do great. It’s a great tool, exactly because I step in after the approximation step, review and decide. I’m aware of the limits. But putting these things in front of “users” without a review step means you are advertising that you are either unaware of this flaw, or just see the cost-benefit analysis and see that if noting else it’ll generate interest during the hype.
There is a huge potential, but throwing AI into a situation where facts are needed when it’s only making rough guesses, is the wrong way about it.
I’ll take any birds like that, hell even crows, but I got seagulls and they scream from the top of their lungs at 5am.
Easily achievable if you only take calls in working hours. Then all working hours will have more than average calls per hour for a day.
It probably makes sense if the program they came from is a badcase, but at least ours don’t go over board. It’s always a “you are probably doing something wrong, but we will allow it if you want to” or a “please confirm you want to do this thing that may have huge consequences”. With what they were learning, they were not touching anything related to the latter. So they probably were doing something wrong.