Prusa are clearly tools: you can fix it, modify it, and still have warranty apply. You can get after-sales parts, and service.
Bambu are appliances. They can work great out of the box, but appliances do not have upgrade paths. You do not upgrade a microwave, you throw it out and get a new one. Or maybe it's more like a fridge, you can limitedly repair some bits, but you cannot wholesale upgrade from V1 to V2.
Anyways bought the core one a few months ago, on kit, and did the whole assembly. The assembly was fun, and the resulting printer has been great. The print fails I had were all easily understandable, entirely due to adhesion issues to a dirty print plate.
I also ordered the indx and am looking forward to capabilities that are not possible with the AMS system. I'm more of an artist though, so I'm looking for interesting and cool ways to make things, not just 3D printing figurines or sculptures etc.
What value to a person does teaching "how to use it effectively" deliver?
How does that benefit their development, learning, society as a whole?
Before you start in with "it'll help them get a job", full stop - education as a public good isn't strictly vocational technician work. It's not a work training for companies.
I think "working product" is doing a lot of heavy lifting for you here.
I think anyone who has done serious product development wouldn't be so flippant and dismissive about the difficulties of even conveying WHAT to build, let along getting the right balance of quality, timeliness, and actual functionality.
The price hikes are going to be absolutely devastating.
Imagine oracle level price acuity along with 0 competition and utter dependence. This is the future the AI labs are drooling for. You will be charged based on the value it delivers. People will be start making trade offs on if hiring humans would be cheaper than AI, etc.
There's no way they're going to leave all that money on the table when there is all that investment to pay back.
That's the thing, often when people say stuff like "its banned" what they really mean is:
- the cost of mitigating the human health risk is too high
- competitors in low-environmental regulation places don't pay for those costs
- ongoing verification is expensive
I mean, let's face it, "self-regulation" of industries isn't really working that great. And for things that are health hazards that are basically borne by someone else, why should a local government make it easy to cheat and lie about this stuff?
The people arguing against this seem to assume that their right to have a business, make a profit, whatever, is a self-evident Good Thing, and rarely provide any additional arguments beyond "but the jobs". If they were at the VERY LEAST saying "we can make X safe" then maybe it'd be interesting. But as it is, the argument is basically asking us to mortgage the health and safety.
Paint VOCs sounds fine, until it's done at industrial scale, and it's also your neighbor, and also all the children in the neighborhood have asthma, and also healthcare is a lot more expensive...
This list isn't things you "cant do in california" but "polluting things you can't do in highly populated cities".
I'm not sure what the conclusion here is other than health is not important.
I've used chatgpt-shell, but I have since turned my LLM usage to gptel inside org-mode buffers. Every day I use org-roam-dailies-goto-today to make a new file and turn on gptel (the use of org-roam-dailies is 100% optional). Then I do my interactions with gptel in here, using top level bullets and setting topics to limit context.
I have 10 months of chats, and now I can analyze them. I even had claude code write me up a program do that: https://github.com/ryanobjc/dailies-analyzer - the use of gptel-mode allows me to know which parts of the file are LLM output and which I typed in, via a header in the file.
Keeping your own data as plain text has huge benefits. Having all my chats persistent is good. It's all private. I could even store these chats into a file.gpg and emacs will auto encrypt-decrypt it. Gptel and the LLM only gets the text straight out of emacs, and knows nothing about the encryption.
I found this better than the 'shell' type packages, since they don't always keep context, and are ultimately less flexible than a file as an interaction buffer. I described how I have this set up here: https://gist.github.com/ryanobjc/39a082563a39ba0ef9ceda40409...
All of this setup is 100% portable across every LLM backend gptel supports, which is basically all of them, including local models. With local models I could have a fully private and offline AI experience, which quality based on how much model I can run.
The "just generate go code automatically then check it in" is a massive miswart from the language, and makes perfect sense because that pathological pattern is central to how google3 works.
A ton of google3 is generated, like output from javascript compilers, protobuf serialization/deserialization code, python/C++ wrappers, etc.
So its an established Google standard, which has tons of help from their CI/CD systems.
For everyone else, keeping checked-in auto-generated code is a continuous toil and maintenance burden. The Google go developers don't see it that way of course, because they are biased due to their google3 experience. Ditto monorepos. Ditto centralized package authorities for even private modules (my least fave feature of Go).
It's kind of weird how you downplay tardive dyskinesia, as if it was kind of a no big deal, whatever kind of thing. Would you accept having tardive dyskinesia induced by a drug?
Is that really your position?
Your other words seem fine, but that is a standout sentence!
regarding #2: "Automate the dumb/boring stuff", I always think of the big short when Michael Burry said "yes I read all the boring spreadsheets, and I now have a contrary position". And ended up being RIGHT.
For example, I believe writing unit tests is way too important to be fully relegated to the most junior devs, or even LLM generation! In other fields, "test engineer" is an incredibly prestigious position to have, for example "lead test engineer, Space X/ Nasa/etc" -- that ain't a slouch job, you are literally responsible for some of the most important validation and engineering work done at the company.
So I do question the notion that we can offload the "simple" stuff and just move on with life. It hasn't really fully worked well in all fields, for example have we really outsourced the boring stuff like manufacturing and made things way better? The best companies making the best things do typically vertically integrate.
Apparently Mac sales are seeing a big growth spurt lately. This isnt obvious at the Apple bottom line because iPhone dominates, but they are growing that market segment!
The apple silicon has driven a ton of people to laptops, and the windows 11 migration nightmare has given people an option: why bother buying a new pc laptop to run windows 11, just switch to the apple macbook air.
There was a quote recently where Nadella was trash talking the apple AI stuff, and like yes sure, but also do we not realize that Nadella isn't a random third party CEO, he's literally financially incentivized to maximize AI usage because Microsoft is selling the stuff?
It's like listening to the Intel CEO saying that the new apple silicon is alright, but what would REALLY make them go is to migrate back to Intel x86.
I'm not really upset at Nadella for this, because it's what he should do. But for everyone else to breathlessly be obsessed with his word and forget his real job as salesman in chief is what's pathetic.
I think the reason why Apple hasnt come out with such a useful personal assistant AI is because the underlying technology just doesn't make this so easy.
Apple is the only company so far that seems to be unwilling to accept a poor user experience with generative AI, so their efforts have been "lackluster" in terms of "AI integration" - as if "maximally integrating generative LLMs" is the goal in and of itself!
Of course Nadella is critical of Apple's efforts: he selling the goods! It's like a Steel CEO complementing a new bridge but then "they should have used more steel" - well duh, but since when do we trust the purveyors of components as to what should be added?
The bottom line is "Agentic AI" is just unreliable. If you thought you hated Apple Intelligence now, then if they had gone whole hog, the unreliability would be astounding.
As a long time Mac and iPhone user, I just don't get all the complaints about innovation. Macs are as innovative as they ever have been, maybe more. Apple silicon has been an absolute powerhouse and godsend for battery life.
iPhones are great, and continue to be awesome. Airpods are so good they make bluetooth headphones look like the garbage they are.
When you look at the grand scope of thing, the primary thing the commenters are missing are the Jobs' pageantry and showmanship. Which I also miss. But in terms of capability, I am quite happy with what we have.
I think there are parallels with functional languages on the JVM. The parts that are the worst are the parts that were built for maximum interoperability. Not to mention that the JVM forces classes on you at the deepest opcode levels.
Compatibility with C++ is fine, but so far it seems carbon's safety story is entirely a wishlist rather than anything yet. Seems like Carbon might be a more of a place to demonstrate features for C++ committees than a real language?
Personally I have hand it up to here with lousy programmingn languages that make it easy for me to write bugs.
In addition to standard multi-color needs!