That's true. The question is whether the produced pattern has any value. LLMs are incapable of determining this, and will still often hallucinate, and make random baseless claims that can convince anyone except human domain experts. And that's still a difficult challenge: a domain expert is still needed to verify the output, which in some fields is very labor intensive, especially if the subject is at the edge of human knowledge.

The second related issue is the lack of reproducibility. The same LLM given the same prompt and context can produce different results. This probability increases with more input and output tokens, and with more obscure subjects.

The tools are certainly improving, but these two issues are still a major hurdle that don't get nearly as much attention as "agents", "skills", and whatever adjacent trend influencers are pushing today.

And can we please stop calling pattern matching and generation "intelligence"? This farce has gone on long enough.

Productivity should be measured over time and take into account the cost of maintenance, reliability, amount of issues, etc.

What's the difference? The end result is equally unreliable.

In either case, the value is determined by a human domain expert who can judge whether the output is correct or not, in the right direction or not, if it's worth iterating upon or if it's going to be a giant waste of time, and so on. And the human must remain vigilant at every step of the way, since the tool can quickly derail.

People who are using these tools entirely autonomously, and give them access to sensitive data and services, scare the shit out of me. Not because the tool can wipe their database or whatnot, but because this behavior is being popularized, normalized, and even celebrated. It's only a matter of time until some moron lets it loose on highly critical systems and infrastructure, and we read something far worse than an angry tweet.

If you demand remuneration for all your work, then it's only fair for you to also pay for every single piece of software you ever use. If OTOH you're willing to trade some of your time and effort for the time and effort someone else spent on the software you enjoy for free, then you might appreciate that a financial transaction is not required for value to be created in the world. What is required is fair collaboration.

But deleting something is just one action you might not want it to take.

The recent "agentic" craze is fueled by the narrative pushed by companies and influencers alike that the more access given to an LLM, the more useful it becomes. I think this is ludicrous for the same reasons as you, but it is evident that most people agree with this.

We can blame users for misusing the tools, and suggest that sandboxing is the way to go, but at the end of the day most people will favor convenience over anything else a reasonable person might find important.

So at what point should we start blaming the tools, and forcing "AI" companies to fix them? I certainly hope this is done before something truly catastrophic happens.

The issue isn't with the amount of guardrails in place to perform an action. Yes, it is obvious that there should be some in place before doing any critical operation, such as deleting a database.

The issue is that the "agent" completely disregarded instructions, which in the age of "skills" and "superpowers" seems like an important issue that should be addressed.

Considering that these tools are given access to increasingly sensitive infrastructure, allowed to make decisions autonomously, and are able to find all sorts of loopholes in order to make "progress", this disaster could happen even with more guardrails in place. Shifting the blame on the human for this incident is sweeping the real issue under the rug, and is itself irresponsible.

There are far scarier scenarios that should concern us all than losing some data.

Funny, I thought that the major hurdle is improving accuracy and reliability, as it's always been. Engineering is necessary and useful, but it's a much simpler problem, which is why everyone is jumping on it.

This industry has become a parody of itself, and people are celebrating.

Proof that something doesn't exist? Ever heard of Russel's teapot?

The burden of proof is on the claimer.

> What exactly do we mean by God?

Absurd question. Pick up any holy book, or ask any believer. An atheist is simply a person who doesn't hold those beliefs.

A famous Dawkins quote is apt in this discussion:

> We are all atheists about most of the gods that humanity has ever believed in. Some of us just go one god further.

> Having certainty something that can be perceived as God by believers cannot exist in our universe is in the end a belief, with no proof.

Again, you're mistaking what atheism is. It's not being certain that a deity cannot exist—it's not having any reason to think that it does.

People who claim certainty in either direction are equally delusional. The problem is when a belief crosses into realms of reality, defines the identity and culture of people, and influences the rest of society. Based on history and personal experience, theists are far more prone to this than atheists.

You have a mistaken understanding of what atheism is. It is not a belief in anything, but an absence of belief in a deity.

> there are a whole lot of things that we all go around everyday "not believing."

Sure, and yet theism is part of 75% of the world population and influences everything from education to politics. It's perfectly reasonable to talk about atheism within appropriate settings.

I'm glad companies like Noctua exist that put so much thought and care into their products. I don't even mind being advertisted to when that's the case.

Now that the internet is flooded by machine-generated content, which is often published and promoted autonomously as well, all content should be scanned and labeled with a value that indicates the likelihood of it being machine-generated and published.

I'm thinking of JSON fields like `machine_gen_probability` and `machine_pub_probability` returned by the API. Then the frontend should expose settings to show these labels next to each post and comment, and filtering rules to decide what should be done with content above a certain value (hide, adjust feed rank, etc.). Some people might even want to boost this content, for whatever reason, so making the system flexible would be smart.

The scoring system of course won't be perfect, but I figure that a company like YC should know a few talented individuals that could do a solid job of implementing this. They've certainly profited from investing in companies that cause this problem.

But... considering HN is merely a promotional tool for YC that runs on limited resources as it is, I wouldn't hold my breath that such a system would ever be implemented. So all we're going to get are changes to "guidelines", and hope that the system won't be abused. Which is laughably naive in this day and age. So this forum will most likely be overrun by the noise, and end up with minimal participation from reasonable humans, as is happening and will continue to happen on most online platforms.

Knowledge comes from doing the hard work, not from being spoon fed information. All these fancy graphs represent a tentative mental model produced as a result of research and learning. Everyone's model is different based on their own experience and focus, so trying to present it as a unique map will more than likely not be conducive to understanding at all. Besides the fact that it will almost certainly miss important details or be hallucinated.

HN users: stop upvoting and promoting this garbage. HN mods: please give us tools to label and filter this content.

A company that goes against their self-proclaimed values... What a shocker.

So like any LLM?

Nevermind the fact that these tools are nowhere near as capable as their marketing suggests. Once companies and society start hitting the brick wall of inevitable consequences of the current hype cycle, there will be a great crash, followed by industry correction. Only then will actually useful applications of this technology surface, of which there are plenty. We've seen how this plays out a few times before already.

No, it's not.

While I don't dispute that new models may perform better at certain tasks, the fact that someone was able to use them to solve a novel problem is not proof of this.

LLM output is nondeterministic. Given the same prompt, the same LLM will generate different output, especially when it involves a large number of output tokens, as in this case. One of those attempts might produce a correct output, but this is not certain, and is difficult if not impossible for a human not expert in the domain to determine this, as shown in this thread.

Long breaks help. Take your mind off of things that bothered you. Do things you enjoy. Which may include tech work, but on your own terms.

I wouldn't be surprised if you decide to not go back. The status quo of most organizations is grim. But there are still people who care about the same things as you. You can seek them out and work together, much like you did 15 years ago. This is more difficult now among the noise, but you can tune that out. The industry will never recover altogether, but this current period is a blip of high insanity, which will subside in a few years.

Good luck!