you are absolutely right. my title is very bad. I'll update it to a very less absolute statement. sorry for that.
I am now trying to sweet spot things with 27b model + tubo8 so I guess should have plenty quality context left.
the error I made in my tests is to stop with a working configuration that maximised my hardware use, and missing real deep software tests. The one shot 3D app I generated with previous setup is exactly telling this : I did not try my setup on real software development cases.
So thank you for guidance. I am not new using agentic code, but when it comes to proper setup with deep understanding of real trades off on inferences engines, I need more deep undestanding to make better decisions.
The 27b Q6_K turbo 8 for ~150K context should give me a real improvement on this stack. It's test party time :D
Edit : oops, I also found I cannot edit anymore my bold wrong title :/
Maybe it is just me, but : these emails are spam. Marking them as spam should be easy in a common email box nowdays. Marking these undesired emails as spam lowers email sender reputation, then finally gives real insight to the spamer soon or later. Meanwhile you have no more emails from them.
This is unperfect because of ressource waste and the underlaying unsolved law compliance of these services. But at least you get job done easily this way.
As many things in life this is compromise, not perfect solution. In between using this simple trick I can spend my time on more interesting things.
I respect anyway the fact that people try to fight against the intrusive AI default communication mindset. In the end, i think this post need to be heard rather than having a solution.
High level langages like js or python have a lot of bad design / suboptimal code... as well as some java code in many places.
Some bad java code (it just needs to be a sql select in a loop) can easily perform thousand time worse than a clean python implementation of the same thing.
As said above, once c was high level programing language and still is in some places.
I do not code in python / go / js that much these days, but what made me a not so bad developper is my understanding of computing mechanism (why and how to use memory instead of disk, how to arange code so cpu can use it's cache efficiently...)
As said in many posts, code quality even for vibe coded stuff depends more on what was prompted and how many efforts the PR diff is human readable to get maintainable and efficient softwares at the end of the day.
Yet senior devs often spend more time reviewing code instead of actually writting some. Vibe coding ultimately feels the same for me at the moment.
I still love to write some code by hand, but I start to feel less and less productive with this approach while at the same time feeling I don't really lost my skills to do so.
I think I really feel and effectively am more efficient at delivering thing with appropriate quality level for my customers now that I have agentic coding skills in my belt.
Not sure it is your case but I think I sometimes had to solve many of them when I am in my daily task rush. My hypothesis is that I solve them too fast for "average human resolving duration" recaptcha seems to expect (I think solving it too fast triggers bot fingerprint). More recently when I fall on a recaptcha to solve, I consciently do not rush it and feel have no more to solve more than one anymore. I don't think I have super powers, but as tech guy I do a lot a computing things mechanically.
I did not find other comments like this in this thread.
6% M2 cpu (even single core) is a huge computing budget for such a small feature.
At this point I don't really understand why OP seems happy with this result (sorry).
I think even a naive canvas implementation can really and quite easily cut most of this computing budget.
Also, a pure css animated thing should use mostly gpu in a right DOM implementation. I think some issues remains in this result.
Maybe OP displays it's app on a 240hz external screen which makes browser compute DOM animation at 240 fps requiring slighly more compute in a passive way (4o-mini suggests this, I am not sure browser works like this)
I remember too much of my pentium 1 166Mhz let run entire age of empires 2 game in 1997
It does not seems to appear in comments yet and maybe it is a bit out of context but android devices nowdays streams almost perfectly services like geforce (video hardware acceleration is a basic feature on phones) now and it is relativiely easy to setup a proper moonlight / sunshine as android client / remote home gaming pc to get "on premise cloud gaming" .
As some other comments says pc games have way better quality and infinitely less ad / bloat / pay to win shit that is the norm on android (and maybe a large part of ios games). There is also a huge game choice for these platforms that supports very well gamepad controls.
These systems are not perfect as they require a "descent internet connection " and a physical gamepad (imo) to have a decent mobile gaming experience. So it.may not fit the case "I want to play games lost in alaska".
Note however that the required connection has argably quite low expectations like ~3 mbps bandwidth and average and less than 150 ms latency to run smoothly with basic resolution (480p). This can be enough on a phone device standard size.
All of this let you play any pc game / retro gaming with possibly high end game renderings for decent hardware / saas prices. (You run games with with small resolution because it targets a phone screen so hardware can compute extra visual effect for a cool rendering on phone)
I searched last result page on a google search with 1M results announced. On page 20 or so it is shown "display more results" then I clicked it and it still shows 1M results or so. Then I go to last page and it is only on page 40 with few hundreed results in the end.
I guess google knows this and I wonder what is the intention to display 1M result available and let users reach so few in reality. Is it commercial argument ? I hardly belive this is an error. Does it reveal how maybe very fewer data google indexes / retains to keep result efficiency ? Does it reveal some sort of data management / algorithm mechanics from their search engine ?
Thank you for this constructive answer. I understand here that indeed there might have answers in NLP for my question. I also mainly understand that there are no simple answers. It's a very hard question that should be splited in many sub topic to have a true response overview, what looks to me to hard for a proper answer. I think now I have to dig the internet a lot to have a more accurate response ;)
I can elaborate more on my inital question by rephrasing as following : "Does short messages systems (messenger like / sms) in 2020 provide better human communication (more efficent, better comprehension) than legacy long messages systems (emails, letters, books) ?
Rephrasing makes me understand that the question is still way to large as it need a lot of definition ans asumption to hope an simple answer.
I am now trying to sweet spot things with 27b model + tubo8 so I guess should have plenty quality context left.
the error I made in my tests is to stop with a working configuration that maximised my hardware use, and missing real deep software tests. The one shot 3D app I generated with previous setup is exactly telling this : I did not try my setup on real software development cases.
So thank you for guidance. I am not new using agentic code, but when it comes to proper setup with deep understanding of real trades off on inferences engines, I need more deep undestanding to make better decisions.
The 27b Q6_K turbo 8 for ~150K context should give me a real improvement on this stack. It's test party time :D
Edit : oops, I also found I cannot edit anymore my bold wrong title :/