AStrangeMorrow
For me the main difference is now some people can explain what their code does. While some other only what it wants to achieve
Sure it is not as fast to understand as code I wrote. But at least I mostly need to confirm it followed how it implemented what I asked. Not figuring out WHAT it even decided to implement in the first place.
And in my org, people move around projects quite a bit. Hasn’t been uncommon for me to jump in projects with 50k+ lines of code a few times a year to help implement a tricky feature, or help optimize things when it runs too slow. Lots of code to understand then. Depending on who wrote it, sometimes it is simple: one or two files to understand, clean code. Sometimes it is an interconnected mess and imho often way less organized that Ai generated code.
And same thing for the review process, lots of having to understand new code. At least with AI you are fed the changes a a slower pace.
I had some pieces of code I wrote I was quite proud of: well documented, clear code yet clever designs and algorithm.
But really what always mattered most to me was designing the solution. Then the coding part, even though I take some pride in the code I write, was most a mean to an end. Especially once I start having to add things like data validation and API layers, plotting analysis results and so many other things that are time consuming but easy and imho not very rewarding
I can use them while charging my phone or working out. Can play a video while cooking and moving around the kitchen. Or while watching TV/playing a game in the TV where a cable can’t reach.
However when static I used wired. That’s mostly when on the computer, but like many people here I am assuming that’s a good part of the day.
I’ve had thing like a system that has a collection of procedural systems. I would say “replace the following set of defaults that are passed all around for system X (list of files) and in the managed (file) by a config” and it would do that but I’d suddenly see it be like “wait mu and projection distance are also present in system Y and Z. Let me replace that by a config too with the same values”. When system Y and Z uses a different set of optimized values, and that was clearly outside of the scope.
Never had that kind of mistakes happen when dealing with small contexts, but with larger contexts (multiple files, long “thinking” sequences) it does happen sometimes.
Definitely some times when I though “oh well my bad, I should have clarified NOT to also change that other part”, all the while thinking that no human would have thought to change both
Usually things go smoothly but sometimes I have situations like: “please add feature X, needs to have ABCD.” -> does ABC correct but D wrong -> “here is how to fix D” -> fixes D but breaks AB -> “remember I also want AB this way, you broke it” -> fixes AB but removes C and so on
At work I also always tended to send slightly longer but structured answers. I found that it allowed to skip over the irrelevant sections and focus on what the changes are. Eg a list of changes with in the format -> bullet point -> change name -> change details. So people could easily focus on changes they cared about. Instead of a dense paragraph that people often just skip.
Hell I even found myself wanting to add a typo just to give a more human fell, or skip final “.” to make my text imperfect and more human. That’s getting silly
Sure LLMs are getting better and better, and at least for me more and more useful, and more and more correct. Arguably better than humans at many tasks yet terribly lacking behind in some others.
Coding wise, one of the things it does “best”, it still has many issues: For me still some of the biggest issues are still lack of initiative and lack of reliable memory. When I do use it to write code the first manifests for me by often sticking to a suboptimal yet overly complex approach quite often. And lack of memory in that I have to keep reminding it of edge cases (else it often breaks functionality), or to stop reinventing the wheel instead of using functions/classes already implemented in the project.
All that can be mitigated by careful prompting, but no matter the claim about information recall accuracy I still find that even with that information in the prompt it is quite unreliable.
And more generally the simple fact that when you talk to one the only way to “store” these memories is externally (ie not by updating the weights), is kinda like dealing with someone that can’t retain memories and has to keep writing things down to even get a small chance to cope. I get that updating the weights is possible in theory but just not practical, still.
I highly doubt I was the first one (and I mean that was 4 years ago so the one from 2018 definitely precedes it), however it had a bunch of extra features like colors associated with the initial states and the colors would also propagate and merge alongside the cells
Stuff like that though always makes me curious
And I am confused about the “doing it any other way”? I don’t really see other ways to achieve the same result. Say painting and photography will both produce end results that are quite different. The skills are very different. The end material is also quite different. The same way stained glass is quite different from painting
He was a medieval Italian diplomat. And seems like when he was at the court of the Khan, we was trying to make a push of Catholicism and was getting into debates with other theologians, including one from a Islamic country and one from the Byzantine empire.
A bit later in the medieval times, you have https://en.wikipedia.org/wiki/William_of_Rubruck who was an envoy from the court of France (Louis XIV) to the Khan. Or https://en.wikipedia.org/wiki/Andr%C3%A9_de_Longjumeau (from France too)
Marco Polo is the most well know but far from the first one
One of the worst one was an allegedly “illustrated history” book. All Ads were of AI generated history book pages with tons of historical inconsistencies. Looked up the real book and it actually looked decent: hand drawn, well formatted etc. Why not use pictures of the actual book instead of whatever mess I was seeing.
However I also keep getting Ads for this other historical book that drives me nuts: https://www.kickstarter.com/projects/vilno/the-codex-book
I might be wrong but to me most of the art is looks AI generated, and the few pages they show just don’t make any historical sense. Yet they sell it as “hand drawn”. From the animations seems like some stuff was AI generated and then redrawn by hand? But the drawing themselves are plain weird: the nonsensical castle. The archers and scoped crossbow in a page about medieval crossbows, the silly submarine
I feel like that’s kinda how people imagined navigating whatever cyber domain when the first big cyberpunk novels came out
Eg you want to find a really good design. Designs are fairly easy to generate, but expensive to evaluate and score. Understand we can quickly generate millions of designs but evaluating one can take 100ms-1s. With simulations that are not easy to GPU parallelize. We ended up training models that try to predict said score. They don’t predict things perfectly, but you can be 99% sure that the actual score designs is within a certain distance of said score.
So if normally you want to get the 10 best design out of your 1 million, we can now first have the model predict the best 1000 and you can be reasonably certain your top 10 is a subset of these 1000. So you only need to run your simulation on these 1000.
Just curious because while the edit-1 space can be fairly big, I’d assume all edits have very different probabilities. So the squatted domains probably skew to a higher probability edit. By that I mean mostly keyboard edit typos, eg on a phone: the “cwt” typo is more likely than “cpt” for “cat” because of an and w keyboard proximity. Wonder what the squatting rate is when you filter for edit within one key stroke for example (only really change the add and replace types of edits, not delete or swap)
Like at a grocery store: “is that enough? That will do yes -> yes that’s perfect”
Some tasks I do enjoy coding. Once in the flow it can be quite relaxing.
But mostly I enjoy the problem solving part: coming up with the right algorithm, a nice architecture , the proper set of metrics to analyze etc
However if I just say “I have this goal, implement a solution”, chances are that unless it is a very common task, it will come up with a subpar/incomplete implementation.
What’s funny to me is that complexity has inverted for some tasks: it can ace a 1000 lines ML model for a general task I give it, yet will completely fail to come up with a proper solution for a 2D geometric problem that mostly has high school level maths that can be solved in 100 lines
OpenStreetMap and such have pretty good building footprints, sometimes enriched with building heights. Maybe that can be used for some correction
Now of course you I can’t blame people for wanting more money and better standards of living, and that’s always been a thing. But many jobs that used to afford you a middle class life don’t anymore for young people.
I saw my engineering school software engineer department going from the least sought after specialty to the most in one year. The number of people passionate about tech didn’t suddenly jump, but each year we have a report about the last promotion average starting salary and software engineering was at the top for the first time.
I feel like if these report included the price and severity instead of just the frequency of the maintenance it would paint quite a different picture.