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The r/programming subreddit is what you may be looking for.

Would you explain farther how China winning the AI race would result in world war 3 deaths?

How is it unprofessional when it is simply someone giving their honest personal opinion on an issue that involves something that is valuable to them, on their personal blog nonetheless.

Is everyone a walking and talking brand now so that they have to always filter their words, walk on eggshells, hide behind corpo-speak so as to seem 'professional'?

More honest discourse is required in today's world, not less. It seems interactions online are becoming less and less authentic.

I'm glad LLM coding exists for people who want to move at an insane superhuman speed (perhaps they're trying to achieve escape velocity and launch into the stars or something) so that they don't grind down their fellow humans.

You can either do local optimization - a single individual moving as fast and as hard as humanly possible, or global optimization - a team working together and amplifying each other's efforts to produce something that is greater than the sum of its parts.

On the bright side however, one can easily vibe code a browser extension that automatically hides comments that are not aligned to one's needs, whether its American politics or comments complaining about it :-)

Generally, it seems like if you are not getting returns that outweigh your token spend, you are merely paying to train AI.

One annoying thing is how long it takes for things to sway back into equilibrium.

It's getting quite exhausting having to endure all these major events of the 21st century and their consequences - 9/11 and the Iraq war, the 2008 financial crisis, covid-19, and now AI.

But I guess it's better than all out war and conquest as was with most of human history.

You can find some video material from O'Reilly Media

Yeah, makes a lot of sense.

From what I've read from people with relevant experience, the only way to get a large organization change direction is to issue imperative decrees lacking nuance, because large organization by nature tend to be process heavy and are too incompetent to follow a nuanced direction.

If you have tens of thousands of employees the more complicated the communication is, the larger the variation of interpretation of its meaning, I suppose

With such kind of ATS systems, is it still a thing to optimize for a one page resume that is easy for a human reviewer to scan, or just include enough buzzwords and external links to try and please the LLM?

Even if they only fire the juniors and retain the seniors, they have effectively broken the pipeline that creates more seniors for the next few decades.

That is either betting on AI being better than humans then, or closure of the company.

I might be reading this differently, but isn't the acquisition a bet that Modular will become a manufacturer-agnostic software stack?

"We believe the future belongs to developer-friendly, horizontal platforms that can run across diverse compute environments and give customers real choice in how and where they deploy AI," Qualcomm CEO Cristiano Amon said.

Yeah, the whole AI industry is just people ripping off each other.. Started by AI companies gulping up all the information that technical or altruistic people shared on the Internet in the past 40 years to help other fellow humans, then moved to AI companies consuming pirated and copyrighted material and now its AI companies ripping off each other.

Information really does want to become free, but AI companies want to be gatekeepers. Long term I bet on the open weights to win, as the more sustainable approach.

without increasing educator workload substantially

Isn't this a good thing, employing more educators, building more schools?

Any sane society will always invest more into its future well being and incentivize investments into education.

It's likely the elected officials know nothing about AI the technology.

Depends on who has their ears in terms creating policies around technology.

Is that before or after the OpenAI and Anthropic pay off all the people and companies who's copyrights were violated when they used their works for free to train their models?

At least DeepSeek freely gives back the benefits.

Weird, isn't it? Microsoft owns all of LinkedIn, Github and NPM.

All three either have security or stability issues, which seems to get worse, not better, as microsoft goes more into AI. Where is the AI productivity (10x by some accounts!) within the company going to?

I use vanilla emacs and compile from source straight from master at whatever commit it happens to be in when I decide to do it.

Only once was there a noticeable breakage when a command like `git log` in the terminal would spit out all its output instead of displaying one screenful at a time. I'd expect someone following stable releases wouldn't experience any breakages.

From the article

Matz has said as much. He’s described Ruby’s design as starting from a simple Lisp, stripping out macros and s-expressions, then adding an object system, blocks, and Smalltalk-style methods. The features most Rubyists fall in love with aren’t the object-oriented ones. They’re the functional ones, dressed in friendlier clothes.

There are some attempts at this problem, like Bittensor, Akash Network etc

If I remember correctly, the original GPT was considered too dangerous to release to the wild.

With hindsight, does that hold? If not, then how would we know a model is truly dangerous to release?

Hypothetically if LLMs were possible in the early 90s, what would the software ecosystem look like today?

Would it be 80s technology everywhere but widely deployed? Or would things have advanced further - better compilers, more ergonomic languages, better platforms etc? I don't know. But I suspect we'd still have needed people studying computer science to advance the state of the art.

Now looking forward 30-40 years from now, will everything still run on 2020s technologies?

Don't tell me were going to rediscover progressive enhancement all over again after more than a decade. Back when we used to actually care about the end user whether you were programming frontend or backend.

Too much VC money and big tech influence in the JS ecosystem made the web worse in some ways.

The best outcome of the AI hype for was to be the investment into next generation nuclear power plants, ushering the world into a post energy scarcity era.

Maybe we'll get there, maybe not. These days I only hear of datacenter investments.

These became popular after Moore's law made it possible many years after C/Unix had become the standard.

And they became just good enough that more people didn't go into Lisp/Smalltalk instead.

I highly respect the Ken Thompson and the rest of the old UNIX hands, but wouldn't they admit that the real world is messy and the best solutions in isolation don't always win?

Their creation C and UNIX won over the more advanced LISP and Smalltalk systems because they were simpler to implement. Even their own more advanced Plan 9 based OSs could not displace the more widespread unix-like systems.

It seems distribution and 'good enough' to rely on always wins. IMO, dynamic languages like Perl, Python, Ruby, JavaScript, PHP and the heavily marketed Java provided good enough high level facilities that have prevented people from reaching for Lisp and Smalltalk.

Looking at it through this lens, perhaps C++ was the vehicle for strapping some high level facilities on a widely adopted low level performant language that made it just good enough of a technology for wide adoption.

I'd also prefer journalists not outsource their writing to AI and doctors not outsource their diagnosis to AI etc etc

While it is human nature to minimize energy expended on doing things, progress has always come from the minority who prioritize disciplined thinking and action.

While minimizing energy spent worked well in historic periods where survival was hard, in this era of abundance and a complex, interconnected and fragile civilization, the same instinct becomes harmful.

Outsourcing the work deprives you of who you become by writing it.

Just because AI can do something that resembles work should not mean outsourcing work to it. Mathematicians should not outsource their work to AI just like programmers should not outsource programming to AI.

Humans working with AIs in a tight loop means intellectual work becomes more high-level and creative, but a human should always own the work, validate it and stake their reputation to it. Simply ban any humans who produce low quality work using AI.