rekrsiv

Out of curiosity, was that before or after LLM agents?

Oh right, I keep forgetting about those useful-but-historically-mentally-draining-to-update sources of truth. This might be extremely useful when paired with an agent.

My theory is that most problem solvers are bad at solving problems, and most managers are bad at managing, and it doesn't matter how evolution created them: They'll make mistakes, they'll have finite time and energy, a finite context window, they'll lie and internally rewrite their own internal narratives as needed, and forget things, and drop balls, and they'll go in circles trying to find a bug they created but are too close to be able to see, and they're going to need a lot of external tooling to get through the day without forgetting anything, and constant reminders from others to get shit done. And this dynamic fundamentally creates peaks and valleys in productivity.

Wait, were we talking about humans or AI?

...

Everyone seems to be assuming either the humans or the AI has to be special. What if neither are?

No, AI wasn't supposed to solve all that drudgery. The hypothesized AI singularity would, but an ordinary AI agent running an LLM is just a problem solving automaton with no will of its own, just like a fleshy brain solving computer problems is just a code monkey.

Yet another statistically misleading headline.

Time is finite and regression testing always gets punted to the back of the line when humans are excited. This simply reveals a staggering level of humanity.

The endgame in programming is reducing complexity before the codebase becomes impossible to reason about. This is not a solved problem, and most codebases the LLMs were trained on are either just before that phase transition or well past it.

Complexity is not just a matter of reducing the complexity of the code, it's also a matter of reducing the complexity of the problem. A programmer can do the former alone with the code, but the latter can only be done during a frank discussion with stakeholders.

A vibe coder using an LLM to generate complexity will not be able to tell which complexity to get rid of, and we don't have enough training data of well-curated complexity for LLMs to figure it out yet.

I agree with everything you said except that the US is able to stop it. Think about it: Wouldn't Israel simply use these same tools in the US to install a puppet president they can easily manipulate?

Can we even prove it hasn't already happened?

A bribe in a low trust society is not the same as a bribe in a high trust society.

In this context, a bribe is irrelevant compared to the act of election interference by a foreign actor.

Quick question: Could they also be manipulating this message board's voting?

You are correct. Robustness requires a system that is working within it's tolerance margin, and stressing that inevitably leads to failure. A fault-tolerant system in this case would require a large amount of redundant humans. Unfortunately, the capitalist mindset prevents accepting any amount of "waste" as tolerable, which makes a robust system impossible to implement over time. Every system touched by a capitalist optimizer will eventually fail.

The idea that waste must be reduced is killing society, and this mindset must be addressed first before any other safety-critical system can be made reliable again.

I am alarmed at the high number of supposed engineers on this thread that are seemingly unaware of how safety-critical systems work. Literally every other piece of this system has redundancy built into it. Robustness is never optional in a scenario involving human safety.

When did this lunacy become an arguable position?

Can a single human being reliably and robustly maintain a safety-critical system alone under any circumstances, ever?

Ever?

A terminal still offers a more composable interface than a GUI. Analog feedback is still a concern for high level pilots. You are confusing power tools with entry-level instruments.

It is still called the Department of Defense.

On the other hand, as long as the entire internet goes down when Cloudflare goes down, I'll be able to host everything there without ever getting flack from anyone.

You forgot to provide a counter-argument to the author's position while you attacked them personally.

You're ignoring the fact that going outside to protest wasn't something you could just decide not to do, just like buying groceries. BLM protests and gathering indoors for fun are not equal.

If it quacks like a Markov chain...

Not all artificial neurons are LLMs. Machine learning can be applied to any kind of large data set, not just human prose, and will start finding useful patterns before a human brain has time to learn how many fingers it has.

We use logic to design our technology, but evolution does it by literally shaking all the atoms into place, no design involved. Our brains were created randomly.

But we don't even need a human brain. We already have those, they take months to grow, take forever to train, and are forever distracted. Our logic-based processes will keep getting smaller and less power hungry as we figure out how to implement them at even lower scales, and eventually we'll be able to solve problems with the same building blocks as evolution but in intelligent ways, of which LLMs will likely only play a minuscule part of the larger algorithms.

On the other hand, a large part of the complexity of human hardware randomly evolved for survival and only recently started playing around in the higher-order intellect game. It could be that we don't need so many neurons just for playing intellectual games in an environment with no natural selection pressure.

Evolution is winning because it's operating at a much lower scale than we are and needs less energy to achieve anything. Coincidentally, our own progress has also been tied to the rate of shrinking of our toys.

Development is often divided into 80% known unknowns and 20% unknown unknowns. AI can only help with one of those, and it's the one that takes the least amount of time to complete.

Research and thinking is always going to be the bottleneck.

Feel free to point to said data.

I believe this is true for literally anything that replaces practice. We're meant to build muscle memory for things through repetition, but if we sidestep the repetition by farming it out to another process, we never build muscle memory.

This a supply and demand problem, supply will continue until Americans stop needing drugs.

Maybe stop creating situations where people need the drugs in the first place?

While I agree that it's very easy to create too much code, I think one of the bigger sources of debt we face as an industry is poorly fitting our tools to the tasks at hand. Sure, a SQL database is nice if you need to query the data in undefined ways in the future, but there's a vast set use-cases that won't benefit from all the features that come with it and could bankrupt you if you decide it needs to scale.

I wonder how many servers Company A and Company B are running.

At the end of the day, rationales like this are moot when the final deciding factor will be an envelope full of cash to some politicians.

Both of those have trillions of dollars more in counter-initiatives, and that was before the global democratic backsliding started snowballing. I don't think it's going to happen this century.