374 karma · joined February 25, 2019
Today I find myself having less patience for it all, because things just tend to work a lot more often than they don't.
With AI, I find so many small businesses and others I deal with which have their own websites have started to have better design, better performance and while I don't know if they are really accessible but they tend to have more prevalence of aria labels.
Not to take away from your experiences, just sharing my anecdotes.
I am sorry for not being clear in my response but I didn't intend to twist your words. I am not sure where I did so. My response was intended to be a more general remark on the kind of discourse on this topic I see and that I think both sides are right from the context they are looking in with and also why I think both sides come out of this discussion exhausted of the other. Not discounting presence of bad actors but generally I think there are most engaging in good faith like you are probably.
Coming specifically to respond your last response, I don't think one needs all of these prerequisites to get value out of LLMs. In fact LLMs have helped me untangle some very messy ball of muds on projects where we previously deemed it not worth the effort and basically carried some codebases as legacy. Now we can write enough tests to feel confidence and do a port against those tests all in a span of few days, which we found impressive.
Now having said all this, I think I understand your perspective a bit better on your original comment.
While it's a very versatile hammer, if it doesn't work for your use case that's all great. I just think that a bit more patience though with honing it maybe could help you find areas where it could work for you. If not, cheers!
But a lot of people excited about new generations(including me, now) are not seeing it as a dichotomy but rather a spectrum where models are getting better and indeed once a year or even 6 months at times there comes a sudden growth which feels like an inflection point from what came before. Practically, it's a tool like any other, you evaluate it based on if it's worth the effort and cost for the benefit you get from it and if it is and has a good DX you use it. If the calculation doesn't work for you, it doesn't. For me, it has gone from a novelty, to good for some kind of quick manual search, to I guess it can debug some kind of errors at times in very specific conditions, to hey I think I am getting a bit addicted to autocomplete in IDE provided by them even if I don't use them for anything intelligent but it's becoming indispensable now but only this part, to it's good for areas I lack expertise in, to agentic sucks I will stick with discussing algorithms and architecture with it on greenfield projects, to holy shit it can do agentic decently well now, I am skeptic to give it access more than in limited cases, to now I am getting close to letting it run free on my device in not so distant future I guess. Some of these were big jumps, at each point I was skeptical of growth. Everytime I thought now the growth will slow down from days 2k context window to millions now. From basic chat completion to working on complex adaptive systems, game theoretic modelling, heurestics and constraint modelling and other things I throw at it. I am still needed in the loop, it can be so smart at times and then will do something so stupid, but the frequency of stupidity is rapidly decreasing. I am still needed, I don't think it could accomplish alone all that it has done for me. But I do at times at night remain awake reflecting on my self worth for the potential day when I don't add that value. When I have a harder time keeping up.
Also had someone told me not in even 2019 that in 2026 we could have NLP models do what they do today, I would have posited it all as sci-fi and here I am waking up in awe of the world we live in and how quickly we adapt.
And yes, in real machines we can't ever have true same states between multiple calls as system time, heat and other effects will differ but we define the state over the abstracted system model of whatever we are modelling and we define idempotency as the same state over multiple calls in that system.
A reality where we are talking about if the problem solved by the automated model using formal verification was too easy.
Don't get me wrong, I am not saying any of this means we get AGI or something or even if we continue to see improvements. We can still appreciate things. It doesn't need to be a binary. What a time to be alive!
Now none of this is meant to excuse the behaviour of all these large platforms for all the terrible practices they engage in. But at the same time, we never figured out how to safely deal with the power exposed by these APIs.
Regarding system76 I have heard really good things about their workstations but not about laptops. Have you used them? I recommend PopOS to anyone getting started with linux as the first distro though.
Framework is so close to having it all though.
Agreed about macs feeling bloated. I will not get overdramatic by calling latency in many functions unbearable but it is certainly quite high.
Geat to know this about your experience with thinkpads. Due to your familiarity with multiple such devices would you be able to recommend a starting point for someone who wants something light with budget not being a constraint?
Any suggestions for something well built but lightweight and that one could figure out how to get 8+ hours of actual daily usage battery life on?
I still like REST and try to use it as much as I can when developing interfaces but I am not beholden to it. There are many cases which are not resources or are not stateless and sure you can find some obtuse way to make them be resources but that at times either leads to bad abstractions that don't convey the vocabulary of the underlying system and thus over time creates this rift in context between the interface and the underlying logic or we expose underlying implementation details as they could be easier to model as resources.
RPi can be a compelling option if you need lower power draw. It does take some effort to squeeze out power efficiency but if the requirement can't be handled by a microcontroller then it is the most convenient of-the-shelf option.
For everything, RPi isn't a very compelling option. Even for GPIO, during RPi shortage I started experimenting with just using STM32 dev boards connected via USB to a NUC or an old PC and it worked well. But I just prefer to use ESP8266 or ESP32 for those tasks most of the time. Bandwidth and latency of USB communication/wifi to the main device has been low enough for it not to be a concern for me and I recon outside of very specific robotics cases it won't be for most.
CSI port is quite nice though and not many great alternatives.
However, I don't find that to be the case for most of the written content I consume and knowing where some content was created temporally is important context more often than not(at least in my experience). Now, I can't nor would I want to dictate what others do on their own hosted content(where they generously share their hard meticulous work).
Comments on HN and other places lamenting lack of dates however should be fair game to desire such additional context. But then again, you commenting back is just participating in the same dialogue so I guess my entire message has been just meandering.
However for those where it can work, I think Kagi Ultimate is a great deal.
I would love to pay for search again and not be the product but as of my last experiment(Nov 2024) Kagi wasn't that for me. Curious to know if anyone else had such an experience or perhaps something I need to re-evaluate.