nhaehnle

I believe the article exaggerates to make a point. Yes, good engineering can also be assisted with LLM-based agents, but there is a delta.

Good engineering requires that you still pay attention to the result produced by the agent(s).

Bad engineering might skip over that part.

Therefore, via Amdahl's law, LLM-based agents overall provide more acceleration to bad engineering than they do to good engineering.

My thought as well, but the question is: does it matter for what the survey is trying to achieve?

Some people will interpret it one way, some a subtly different way, but is there a reason that people's interpretation changes over time in a way that is more rapid and more significant than the underlying question of how good their life is broadly? Probably not.

There may be cultural differences that make it tricky to do comparisons between cultures / countries, but it should give something useful when looking at the same culture / country over time.

In particular, the bulk of the substantial text of the order has a pretty clear culture war bend with all the talk about how truthful AI is. This is in large part a fight over the political leaning of AI models.

That's the whole point. They aren't law, and they were (probably) never meant to be so far-reaching, and yet the clear purpose of this Executive Order is to tell the states what laws they can enact. The EO doesn't have the legal power to do that directly, but it clearly outlines the intention to withdraw federal funding from states that refuse to toe the line.

That's a fair and good interjection. The truth is probably that at society scale, both approaches are traditional.

The open sharing approach is traditional for research and academia, while the information restricting approach is traditional for business-oriented thinking.

So, a young field will typically start out fairly open and then get increasingly closed down. The long-term trajectory differs by field, and the modern open-source landscape shows that there can be a fair bit of oscillation.

We're seeing the same basic shape of story play out in generative AI.

It is quite interesting to ponder these usage statistics, isn't it?

According to their charts they're at a throughput of something like 7T tok/week total now. At 1$/Mtok, that's 7M$ per week. Less than half a billion per year. How much is that compared to the total inference market? And yet again, their throughput went like 20x in one year, who knows what's to come...

I agree on the first point. I clicked through to the previous blog entry which I also found to be really good.

If you'll look at the Guidelines for HN linked at the bottom of the page, you'll note that whether a submission is productive is not a criterion.

You could perhaps make an argument that among the flood of AI-related submissions, this one doesn't particularly move the needle on intellectual curiosity. Although satire is generally a good way to allow for some reflection on a serious topic, and I don't recall seeing AI-related satire here in a while.

Others have given some answer to who was made poorer by Ballmer holding Microsoft shares, but I'd argue that this is the wrong question. Instead of looking at a specific individual, we should look at systems.

A system that allows this kind of extreme wealth accumulation is quite fundamentally at odds with democracy because extreme wealth can be and is in practice used to influence politics in a way that undermines democracy.

Some people might not care about that, but if your goal is improving the outcomes of the largest number of people, then pretty much everything else is secondary to having a functioning democracy.

I just find it hard to take the 3x claims at face value because actual code generation is only a small part of my job, and so Amdahl's law currently limits any productivity increase from agentic AI to well below 2x for me.

(And I believe I'm fairly typical for my team. While there are more junior folks, it's not that I'm just stuck with powerpoint or something all day. Writing code is rarely the bottleneck.)

So... either their job is really just churning out code (where do these jobs exist, and are there any jobs like this at all that still care about quality?) or the most generous explanation that I can think of is that people are really, really bad at self-evaluations of productivity.

Good on you for having the meta-cognition to recognize it.

I've graded many exams in my university days (and set some myself), and it's exceedingly obvious that that's what many students are doing. I do wonder though how often they manage to fly under the radar. I'm sure it happens, as you described.

(This is also the reason why I strongly believe that in exams where students write free-form answers, points should be subtracted for incorrect statements even if a correct solution is somewhere in the word salad.)

I'm skeptical too, but at least accessibility and usability do show up in those four documents they link to.

I didn't see internationalization and localization, but I don't see anything fundamental about those that would be different.

Security, on the other hand, does feel like a different beast.