Okay, lets imagine it get enforced and every project is
scanned for compliance, with some false positives
and inability to prevent people from sneaking in AI code.\
Do you agree with it now?
The copyright/Anti-ai angle is likely an excuse and they're running
out of money for hosting, hence errors and anti-scraping blocks.
Its completely absurd to think they somehow waited years to ban AI for copyright, while deleting
anything they deem as copyright infringing.
Looks like those vibe-powered opensource projects will mighrate
to somewhere else.
IKEA beds are underestimated: these flimsy POS planks and their
insertion is entire artform that was likely engineered to cause pain.
The idea here is they are huge, finicky and depend on precise positioning
in multiple areas, there is no "easy shortcut" for their structural integrity,
everything has to be perfectly assembled.
The neglected part here is latency, speed itself can be masked
by progress bars/animations, but having visible lag ruins the idea
of speed and users treat it as slow vs animated loading bar.
Ok, suppose you have a "trash/low quality" article and
"this article has been deleted", the article with some info
will win over the audience as they search for it. Like "Worse is Better", the quality
will improve over time and the "deleted article" will stay at 0 recognition.
An average internet user will not complain about the Wikipedia
article, they just switch to Grokipedia and whatever AI-generated content it has,
since they now have it.
Don't know why you get downvoted, but this is how AI-based projects
win over time: they don't randomly decide to delete valuable data.
Grokipedia might be trash in terms of its quality, but at least it
it doesn't have omnipresent moral busybodies loitering in to "purify" it from knowledge.
GCC already solved it:
https://gcc.gnu.org/onlinedocs/gcc/Vector-Extensions.html
The operations behave like C++ valarrays. Addition is defined as the addition of the corresponding elements of the operands. For example, in the code below, each of the 4 elements in a is added to the corresponding 4 elements in b and the resulting vector is stored in c.
Here and on reddit, AI debugging is viewed as some weird shallow
pattern-matching that obviously fails to spot real stuff and
overload the maintainers. Instead of getting to "spotless record"
of zero flaws, the people start rationalizing that "X is not a real bug"
and inventing justifications for their(obviously bad) code,
which is critique they can't accept from AI, only through human
debate that they can't close with a WONTFIX.
Once the bug is actually usable, the tune changes completely.
IFUNC should be implemented by software itself,
like switching functions on runtime/compile checks.
Why bother having a slower, insecure version that is less
flexible than a function pointer? I have to agree with author.
Glibc is filled with even more nasty hacks ripe for new exploits.
Try to listen to music in language you don't understand.
The effects of having lyrics don't appear unless you focus on them to repeat the memory of song.
Of course instrumentals are better, but lyrics lift the mood by virtue of having some "virtual social context" simulation.
Sure, is there anyone nostalgic for debugging bash files by hand?
Any sense of grief for writing C++ template headers, with all boilerplate?
Hmm, does anyone like manually re-writing makefiles these days?
I suspect the enthusiasts of coding craft will struggle to maintain their wonder
after ~4h deep in any of these magical adventures, which surely
involve inventing ad-hoc duct tape and novel, never-before-seen algorithms.
When you make forums you compete with forum aggregators
with more history and social clout, i.e. a reddit replacement.
If someone made better Reddit, it could have a chance, however
reddit-type aggregators crypronite is hosting their own videos/media,
which makes it prohibitively expensive for small companies without
ads and sponsored posts which in turn make them less of "forum aggregator" and
more like facebook social feeds: mainly video/image based dopamine rides
instead of actual knowledge worth keeping.
This seems useful beyond agents.
It will save tons of traffic for scripts, text browsers, low-bandwidth connections,etc
markdown is incredibly compact and easy to parse.
The code written by AI in most cases is throwaway code to be improved/refined later.
Its likely to be large, verbose and bloated. The design of some agents
have "simplify/refactor" as final step to remedy this, but typically
your average vibe coder will be satisfied that the code just compiles/passes the minimal tests. Lines of code are easy to grow.
If you refine the AI code with iterative back-and-forth questions,
the AI can be forced to write much more compact or elegant version
in principle, but you can't apply this to most large systems without breaking something,
as AI doesn't have context of what is actually changing:
so e.g. an isolated function can be improved easily, but AI can't handle when complexity of abstraction stacks and interfacing multiple systems, typically because it confuses states
where global context is altered.
the article misses log-math and log-log-math which
would use 64-bit (d)oubles are exponents in 10^d and 10^(10^d) respectively,
which allows far higher range of possible values but somewhat more
awkward math operations(addition/subtraction), though much more practical & faster to compute.
There is a point in there, long-range analysis and debugging without AI
is much harder, AI spots lots of non-obvious stuff very fast.
If we consider "spotting non-obvious flaws" a skill, this will
atrophy as beginners will learn to use AI to scan code for
flaws,it is effective but doesn't teach anything, reading long blocks
of code and mentally simulating it is a incredibly valuable skill
and it will find stuff AI misses(something that is too complex, e.g. nested/recursive control flow,async
and co-routines/threads interacting,etc), AI goes for obvious stuff first and
has to be manually pointed to "identify flaws, focusing on X".
Quntity of exercise cannot build quality.
Its self-selecting the people who can handle running and injuries
better so they adapt. The rest get injured enough to stop.
II don't think trying to "push it to using 100% of potential" is
worth any long-term health risk, especially with no long-term reward:
so you win X race/competition once and then what?
It seems to be adding tons of articles, then some of them get deleted.
I assume it's been allocated lots of compute.
The entire model is outcompeting wikipedia on quantity per topic.
If wikipedia merges/integrates some article and Grokipedia has a
specific page for it, the search engine/LLM will get that version front and center.
Grokipedia seems to have no scope limit, so wikipedia "non-notable" entries
will be SEO-optimized towards sites with the topic-names, eventually
settling on AI content farms as primary destination.
Still, why many projects are exclusively on github?
Not a single mirror, everything tied to github working,
thousands of people not even considering alternatives..
This has the feeling of corporate feel-good PR release: its essentially
content-less AI-generated rehashing "our models are freer/more open-source"
which seems silly since they don't develop anything unlike DeepSeek/GLM/Qwen
the real open-source giants. Mozilla is a middle-man that could use open-source
agents, but it pretending to be the "gatekeeper" of "open AI".
Their key motivation is exposed in the middle of text:
"The Mozilla Data Collective is building a marketplace for data that is properly licensed, clearly sourced, and aligned with the values of the communities it comes from."
This is far away from Firefox roots, whatever corporate stewards are at helm of
mozilla now think exclusively in terms of marketplaces and "economics of data"..
Futher reading "so we’re deepening our engagement with governments and enterprises adopting sovereign, auditable AI systems. These engagements are the feedback loops that tell us where the stack breaks and where openness needs reinforcement."
Hard pass.