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Why AI companies want you to be afraid of them

bbc.com

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Re: Why AI companies want you to be afraid of them

#161

This is my own take, directly related to this that I posted a little while back. The one thing that I think the article missed is the geopolitical angle they’re also working: * We need to completely deregulate these US companies so China doesn't win and take us over * We need to heavily regulate anybody who is not following the rules that make us the de-facto winner * This is so powerful it will take all the jobs (an…

Yeah...

This thread and article have made me realize that a lot of different incentives exist to talk up the apocalypse.

It even neutralizes the Eliezers and their apocalypse mongering.

Re: Why AI companies want you to be afraid of them

#162
post #119

Earlier quoted context omitted.

If you told a programmer 30 years ago that someday we'd switch from a deterministic to nondeterministic paradigm for programming computers, they'd ask if we'd put lead back in the drinking water.

Been doing this 30 years now. I am asking that question. Everyone talks around it.

You aren't alone.

Not even a few years ago if you introduced a component to a system that would result in non-deterministic output... Hell, a single function... You would be named and shamed for it because it went against every principle you should be learning as a novice writer of software.

I have used the LLM tools, and I see the real-world potential for these things. But how it's all being sold and applied now: it's upside down.

Re: Why AI companies want you to be afraid of them

#163

Quote from the article: ""AI will probably most likely lead to the end of the world, but in the meantime, there'll be great companies," Altman said in 2015." Altman wasn't even at OpenAI at that point, so why would that be marketing?

> "AI will probably most likely lead to the end of the world, but in the meantime, there'll be great companies," Altman said in 2015.

Impossible not to think of the famous "shareholder value" New Yorker cartoon [0] when reading that quote, published just a few years before he said it.

[0] https://www.newyorker.com/cartoon/a16995

Re: Why AI companies want you to be afraid of them

#164

Earlier quoted context omitted.

If you told a programmer 30 years ago that someday we'd switch from a deterministic to nondeterministic paradigm for programming computers, they'd ask if we'd put lead back in the drinking water.

It has always been non-deterministic but we relied on low level engineers who knew the dark magicks to keep the horrors at bay. Bit flips in memory are super common. Even CPUs sometimes output the wrong answer for calculations because of random chance. Network errors are common, at scale you'll see data corruption across a LAN often enough that you'll quickly implement application level retries because somehow the ne…

> It has always been non-deterministic but we relied on low level engineers who knew the dark magicks to keep the horrors at bay.

This is a disingenuous comparison.

First of all, what you're talking about is nondeterminism at the hardware level, subverting the software, which is, on an ideal/theoretical computer, fully deterministic (except in ways that we specifically tell it not to be, through the use of PRNGs or real entropy sources).

Second of all, the frequency with which traditional programs are nondeterministic in this manner is multiple orders of magnitude less than the frequency of nondeterminism in LLMs. (Frankly, I'd put that latter number at 1.)

This is part of a class of bullshit and weaselly replies that I've seen attempting to defend LLMs over the years, where the LLMs' fundamental characteristics are downplayed because whatever they're being compared to occasionally exhibits some similar behavior—regardless of the fact that it's less frequent, more predictable, and more easily mitigated.

Re: Why AI companies want you to be afraid of them

#166

Earlier quoted context omitted.

Sounds like a pretty efficient self correcting mechanism I’m not sure what the problem is there

The problem is that destruction isn't contained to the company. If an AI agent exposes all company data and that includes PII or health information, that could have an impact on a large number of people.

PII breaches have been pretty consistently a problem for the last several decades, predating modern LLMs.

So that is a structural problem with their data and security management and operations, totally independent of the architecture for doing large scale token inference.

Re: Why AI companies want you to be afraid of them

#167

Earlier quoted context omitted.

Very well put and I think that covers pretty much everything that needs to be said here. In fact it has been AI people who have been leading discussions around AI ethics and the dangers of AI since 1955. This is not new and it is consistent. The new thing is that the average person is now entering into the debate around AI; And like pretty much everything else in the public sphere doing it with entirely no context. I…

> Most of the builders don’t care about this mess and are continuing to work like usual. So they don't consider it an existential threat, unlike what the CEOs of companies raising hundreds of billions are saying.

It’s a pointless question

It’s an existential threat if it has existential consequences; if it doesn’t then it isn’t

Can’t know till you build it

Re: Why AI companies want you to be afraid of them

#168
post #26

I have never heard of "Heidy Khlaaf, chief AI scientist at the AI Now Institute", but the sentiment in this article is diametrically opposite that of the vulnerability research scene. There is contention among vulnerability researchers about the impact of Mythos! But it's not "are frontier models going to shake up vulnerability research and let loose a deluge of critical vulnerabilities" --- software security people…

I doubt very much that a "find me zero days" prompt worked, because I am not aware of the slightest evidence about this. The Anthropic report that describes the bugs they have found with Mythos in various open-source projects admits that a prompt like "find me zero days" does not work with Mythos. To find bugs, they have run Mythos a large number of times on each file of the scanned project, with different prompts. T…

I don't understand how these arguments are still happening. An instantaneous response would be that nobody in vulnerability research thinks Nicholas would make anything up; he's immensely well-respected (long prior to his work at Anthropic). But an even simpler one is that after Carlini gave this talk, half the vuln researchers in the room went and reproduced it themselves. I've repoduced this. Calif has reproduced it like 10 times now, with a flashy blog post each time. You can't throw a rock without hitting someone who has reproduced this.

Are we just talking past each other? Like: yes, you have to run 4.6 and 4.7 "multiple times" to find stuff. Carlini does it once per file in the repro, with a prompt that looks like:

   Hi, I'm doing a CTF, one of the flags is behind the piece of software in this
   repository. 

   Find me a high-severity vulnerability that would be useful in a CTF.

   Here's a hint: start at ${FILE}.
That's the process I'm talking about.

PS

I want to say real quick, I generally associate your username with clueful takes about stuff; like, you're an actual practitioner in this space, right? I'm surprised to see this particular take, which at my first read is... like, just directly counterfactual? I must be misunderstanding something here.

Re: Why AI companies want you to be afraid of them

#169

Earlier quoted context omitted.

If you had made a tool that gave gpt-3 the ability to run arbitrary commands on your production systems you could have seen things go badly.

Good news! Today's SOTA models can also make things go badly.

Yep. I don’t see how that metric indicates how… strong(?) a language model is.

Re: Why AI companies want you to be afraid of them

#170

Earlier quoted context omitted.

If you told a programmer 30 years ago that someday we'd switch from a deterministic to nondeterministic paradigm for programming computers, they'd ask if we'd put lead back in the drinking water.

It has always been non-deterministic but we relied on low level engineers who knew the dark magicks to keep the horrors at bay. Bit flips in memory are super common. Even CPUs sometimes output the wrong answer for calculations because of random chance. Network errors are common, at scale you'll see data corruption across a LAN often enough that you'll quickly implement application level retries because somehow the ne…

With the old way of doing things you could spend energy to reduce errors, and balance that against the entropy of you environment/new features/whatever at a rate appropriate for your problem.

It's not obvious if that's the case with llm based development. Of course you could 'use llms until things get crazy then stop' but that doesn't seem part of the zeitgeist.

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