therealdrag0

What’s nefarious about attracting users?

> deliberate destruction of every civilian possible.

Clearly not? Sometime like 2% of gazans have been killed. IDF could kill many many more if it wanted.

The median used to be worse, but we always had ideals. Iirc the Bible comments of donky abuse.

20$ subscriptions offer “top up” too I’m pretty sure.

It’s a trade off of productivity and control.

It’s like learning to delegate and let go. The more senior I got the more I had to learn to let other engineers make decision i thought were suboptimal but mostly good enough. That positioned me well to be comfortable with agents. It’s contextual how much I’m willing to give them control and how much to review afterwards.

Why not? Benchmark all the things!

Pretty good idea, especially if it had a business size floor.

The human impact of those is a fraction of fossil-fuels. So it’s not fair to judge nuclear for being expensive if we don’t hold other fuels to similarly rigorous standards

It looks pretty consistent? At least within reason for a stochastic model. Or am I missing something?

Low is good if you’re working in a tight loop. But more risky for more agentic stuff you want to let cook for 30 minutes or more.

Due to this release note, I used it once to rewrite a doc, and was disappointed.

Ya it’s annoying to have to manage this.

But effort is basically how much extra internal scratchpad to use and how much extra questions to ask and answer before producing a result, Exploring more hypotheses, validating consistencies, calling more tools.

If you’re happy with your token spend on Astra then keep doing what you’re doing. but if you feel the need to conserve tokens, then you can do that by switching to smaller models like Luna when the task is straight forward.

I feel the need to self sensor my writing when phrases sound like AI. Pretty annoying.

It misses the forest for the trees. It feels the need to highlight details not understanding what details are most relevant to a human reader and how to survey the larger problems in a cohesive way that emphasizes the right parts without cliche and undue emphasis.

Would Jev be good for this?

Did you see the Jev model demo where played wiki racing against GPT, Claude and gpt hallucinated links in Wikipedia pages?

Even worse is having to telling people to do stuff who then turn around and use AI to do a poor job without the human rationalizing the problem or result.

Oh wow I remember having the same feeling there. I had forgotten about that, thanks for the memory.

It’s a silly semantic debate. It’s an argument about what other peoples words mean in their mind and the smug comments about it are incredibly banal.

Some people have more diverse backgrounds than others, both in total or relative to a particular subject.

A lot of people are making factual universal claims about ads in this thread that are directly contradicted by my personal experience talking to people.

Thanks for sharing.

They can talk about AGI without claiming the current model is AI. They can talk about emergent intelligence without claiming it’s AGI. And businesses can work on multiple things with different goals without being contradictory.

HN lives in a bubble. I am certain many people will happily use these.

The “AGI” bar comments are so tiring.

Interesting. For example, GitHub’s built in Copilot review for example will checkout the whole repo and do a broad review. I found it to be WAY better than our prior CI reviews that just looked at diff and had TONs of false positives. (We have also built our own review tools like Copilot that check out repo and they are similarly league ahead IMO than diff reviewers.)

I found diff reviewers so heavy in false positives, all my coworkers just ignored them.

I always felt this was over stated, but I think it’s become less true over time.

First different people treat their stuff harder than others. I basically never break or wear out anything, and I usually start with the cheapest option.

Second the quality of cheap shit made in Asia has gone up a lot over the last couple decades. And it is very difficult to know how to pay more for more quality.

That’s strange. So your policy is “trust me bro my local agent knows best”?

Only on the diff? Why? I found AI reviews garbage until they stopped being only on the diff and were actually able to query real context.

Whatever it is it should at least try to be data driven. And have a strong connection with harms and dysfunction. None of this 2% non-reproducible study BS.

More than 50% of boys admit to intentionally viewing poor, and most of them weekly.

Many think this is a slam dunk for a nanny state to step in. But surely we would have hard causal data on the need for it if that was the case? And I’m pretty sure we don’t.

Now let’s apply this simple bar to Claude, etc.

Heard. And Claude is even slower ><