_vertigo

This post does not read like LLM output though

The resulting image holds zero power compared to a realistic deepfake. A drawing or a crude photoshop is obviously artificial.

A deepfake can be used to blackmail, ruin someone’s reputation, or deeply unsettle them. The power of an artificial image along those dimensions scales exactly with how convincing it is.

An app that can generate convincing deepfakes quickly, cheaply, and easily is essentially a weapon.

Is this a real take? You don’t see a difference between an app that allows anyone to transform a picture of someone into a convincing nude within seconds with no skill boundary, and MS paint?

Do you think Google should get government sign-off on every change to its routing algorithm?

..you good bro? Anyway, things are improving but that doesn’t mean people can’t have a say in what tradeoffs they are willing to accept in return for progress.

A lot of progress has externalities and the benefits and downsides of progress are rarely equally distributed.

everyone’s seen ads before, mind if I put a giant ad in the sky for everyone to look at?

Not really seeing what this has to do with Meta or data centers. The bacteria was traced back to a contractor, not really clear to me what the link between bacteria and data centers is.

If the story was like, “water was polluted with waste chemicals produced during data center construction,” I think I could see more of a connection.

Great, a totally vibe-coded website with a slop “analysis” about AI touting a meaningless ratio with zero context

Rock climbing ethics is more complicated and dramatic than that.

Applying this logic about easements doesn’t really capture the whole picture, because you’re considering people only, not considering the mountain. I think some people who support chopping those bolts would argue that this is like restoring the Mona Lisa after some random guy painted their own painting over it. Yes, removing that guy’s crappy painting is technically a destructive act and removes the world’s ability to see that painting. But net-net, things have improved, even though there will always be some signs of the damage done by a fool.

iPhone 13. Did you change the slider at the bottom?

I could see it being good if it helps you estimate crimes committed by citizens. If you know where the gaps in your knowledge/data are, you can attempt to account for them. And that’s better than nothing.

I think misleading information is obviously bad, incomplete information is not necessarily misleading though.

On the other hand, it might be better to remove incomplete information if it is actively being used to mislead people.

Interesting — so in your opinion every country must build out datacenters or be left behind?

I think that’s fine, but 1) that mentality leaves you extremely vulnerable to being disrupted by LLMs and 2) IMO, if you are solving the same problems every day it means you are not making progress on solving the root causes of those problems. What you are describing is toil, not knowledge work

The article makes practical suggestions; you do not. This is just hand-wringing, abdication. Practically speaking this mentality will get us nowhere.

I see this dilemma with LLMs all of the time.

Should you use the LLM to do the thing directly, or use the LLM to implement a tool that does the thing?

I tend to reach for the latter, it’s easier to reason about.

What are some other better ways to normalize?

It’s not morally wrong per-se but just because you are working with your government does not mean what you’re doing is necessarily moral

That’s insane. There should be a big team of people at AMD whose whole job is just to dogfood their stuff for training like this. Speaking of which, Amazon is in the same boat, I’m constantly surprised that Amazon is not treating improving Inferentia/Trainium software as an uber-priority. (I work at Amazon)

It’s just an externality of online advertising

I lost all of my photos when I was a college student too. I was way too irresponsible to actually back anything up. Kind of a bitter lesson.

https://en.wikipedia.org/wiki/Seasonal_lag

I don’t think that is a good example. No one is debating whether LLMs can generate completely new sequences of tokens that have never appeared in any training dataset. We are interested not only in novel output, we are also interested in that output being correct, useful, insightful, etc. Copying a sequence from the user’s prompt is not really a good demonstration of that, especially given how autoregression/attention basically gives you that for free.

The blog post discusses this point directly. Did you read it?

You couldn’t design a better system for incentivizing leaks if you were trying. Hell, the CEO literally said as much. Not sure how you can conclude the markets aren’t the problem.

Rhetorical question: why do non-insiders still bet in these markets? Surely, after all of the focus on insiders, people will begin to realize that betting without insider knowledge is a fool’s gambit..

No schema changes. No new indexes. No query rewrites. Just telling Dapper the correct parameter type.

This was my exact thought process reading this. The business side of my company does not care or want to wait for complex solutions that sound cool to engineers. If anything, we have the opposite problem: convincing business stakeholders when complexity is in fact warranted.

We’re beyond parody or fiction at this point. This wouldn’t be out of place in Snow Crash

This is just a rant with zero actual content or insight. Maybe using an LLM would have made it more legible.

He produces value by refining a raw resource. I don’t want to go to the flea market on my Sunday morning, maybe I’ll pay his markup.