I feel like it's 50/50 between people doing that, and people that have spent a lot of time tuning a system they are pointing at focused and well specified problems.
Absolutely true. But the OPs statement is not without merit. While there is a lot of professional software for which GUI is the correct choice, there is also a lot of "GUI slop" which is just a GUI to look good on marketing and to be easier to onboard new users at the expense of long term effectiveness.
The thing is, for a guided interceptor, the speed ratio between the interceptor and it's target has an extremely strong effect on how difficult the intercept is. In practical situations increasing speed is the best way to increase intercept chance.
The premise is a bit of a stretch to begin with, and the idea that people would not believe a fable transcript circa 2020 (as long as explained as 5 year future tech) is absurd. But even if I take that "AI can do all cognitive and physical work, at human level or better, and cheaper than humans" is true, the article seems to silently layer on "and can run autonomously, indefinitely", then "can also operate independently of any instructions", and finally layers on "has emotions, has moral values, is a conscious being"
> the idea that people would not believe a fable transcript circa 2020 (as long as explained as 5 year future tech) is absurd.
I’m certain I would not have believed a Fable transcript, or an Opus 4.8 or a GPT 5.5 one, for that matter. Is it so hard to imagine ourselves back then?
Ilya Sutskever said in 2017, whilst building OpenAI:
> Within the next three years, robotics should be completely solved, AI should solve a long-standing unproven theorem, programming competitions should be won consistently by AIs, and there should be convincing chatbots.
There was a viral YouTube video from 2014 called Humans Need Not Apply [1], which made a very strong argument that mass unemployment was right around the corner.
I actually think people from the past would be surprised at how slow AI has progressed in the end. Although the domains where it's turned out to be most effective - code, images, videos, music, etc. - would probably surprise them.
Seriously. At that point it was a stuff of science fiction with the early models being on level of Markov chains. Today they are more helpful that the computer in Start Trek.
I remember an episode of TNG were Riker was instructing the computer to come up with an algorithm to search the surrounding space with certain sensor in a specific pattern, I don't remember the exact words but it was something like a sphere with growing radius with the enterprise at the center.
we now, basically, have that, except for the space ship.
At no point are the words emotion, moral or conscious used in the article, that last part is purely your own addition.
Also consider: if "AI can do all cognitive and physical work, at human level or better", doesn't that simply entail the AI being able to run 'autonomously, indefinitely' and 'independently of instructions' in the same way as the current state of being run by human overseers?
If we take the initial premise as plausible, for the sake of this argument his thesis seems to hold together very well.
For the purposes of chess the domain knowledge is the game rules. And from this pov there is really not much to describe, knowing en-passant exists is the peak of domain knowledge.
The other things you describe, such as endgame tables, are really more related to the domain of chess-computing, a subdomain of algorithms, and likely something you exceed your friend's knowledge in.
Getting to a high rank in chess isn't about better domain knowledge, is about application and experience.
I don't know how you can say application and experience isn't domain knowledge. If it isn't, I have no idea wtf we are talking about and I'll have to accuse you of moving goalposts.
IDK if it's just me, but I also find Claude, whether it be the model or the harness, is a lot more "forgiving" of poor prompts than many of the open models
