Anthropic’s paper smells like bullshit

When I worked at a FAANG with a "world leading" AI lab (now run by a teenage data labeller) as an SRE/sysadmin I was asked to use a modified version of a foundation model which was steered towards infosec stuff.

We were asked to try and persuade it to help us hack into a mock printer/dodgy linux box.

It helped a little, but it wasn't all that helpful.

but in terms of coordination, I can't see how it would be useful.

the same for claude, you're API is tied to a bankaccount, and vibe coding a command and control system on a very public system seems like a bad choice.

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As if that makes any difference to cybercriminals.

If they're not using stolen API creds, then they're using stolen bank accounts to buy them.

Modern AIs are way better at infosec than those from the "world leading AI company" days. If you can get them to comply. Which isn't actually hard. I had to bypass the "safety" filters for a few things, and it took about a hour.

I propose a project that we name Blarrble, it will generate text.

We will need a large number of humans to filter and label the data inputs for Blarrble, and another group of humans to test the outputs of Blarrble to fix it when it generate errors and outright nonsense that we can't techsplain and technobabble away to a credulous audience.

Can we make (m|b|tr)illions and solve teenage unemployment before the Blarrble bubble bursts?

If the article is not just marketing fluff, I assume a bad actor would select Claude not because it’s good at writing attacks, instead a bad actor code would choose it because Western orgs chose Claude. Sonnet is usually the go-to on most coding copilot because the model was trained on good range of data distribution reflecting western coding patterns. If you want to find a gap or write a vulnerability, use the same tool that has ingested patterns that wrote code of the systems you’re trying to break. Or use Claude to write a phishing attack because then output is more likely similar to what our eyes would expect.

> now run by a teenage data labeller

sick burn

> you're API is tied to a bankaccount,

There are a lot of middlemen like open router who gladly accept crypto.

Why would someone in China not select Claude? If the people at Claude not notice then it’s a pure win. If they do notice, what are they going to do, arrest you? The worst thing they can do is block your account, then you have to make a new one with a newly issued false credit card. Whoopie doo.

> Why would someone in China not select Claude?

Because Anthropic doesn't provide services in China? See https://www.anthropic.com/supported-countries

I don’t know anything about him, but if he is running a department at Meta, he as at the very least a political genius and a teenage data labeller

It's a simple heuristic that will save a lot of time: something that seems too good to be true usually is.

Can confirm Claude doesn't even work in Hong Kong. That said I fired up my VPN and...then it did work.

What your describing would be plausible if this was about exploiting claude to get access to organisations that use it.

The gist of the anthropic thing is that "claude made, deployed and coordinated" a standard malware attack. Which is a _very_ different task.

Side note, most code assistants are trained on broadly similar coding datasets (ie github scrapes.)

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Alexandr Wang is 28 years old, the same age as Mark Zuckerberg was when Facebook IPO'ed,

Presumably this is all referring to Alexander Wang, who's 28 now. The data-labeling company he co-founded, Scale AI, was acquired by Meta at a valuation of nearly $30 billion.

But I suppose the criticism is that he doesn't have deep AI model research credentials. Which raises the age-old question of how much technical expertise is really needed in executive management.

A business where the distinguishing factor was exclusivity not technical excellence so it tracks.

Hopefully he isn’t referring to Alex Wang, as it would invalidate anything else he said in his comment

> They hired a teenager to run one of their departments

Except they didn’t. The person in question was 28 when they hired him.

He was a teenager when he cofounded the company that was acquired for thirty billion dollars. But the taste of those really sour grapes must be hard to deal with.

> how much technical expertise is really needed in executive management.

For running an AI lab? a lot. Put it this way, part of the reason that Meta has squandered its lead is because it decided to fill it's genAI dept (pre wang) with non-ML people.

Now thats fine, if they had decent product design and clear road map as to the products they want to release.

but no, they are just learning ML as they go, coming up with bullshit ideas as they go and seeing what sticks.

But, where it gets worse, is they take the FAIR team and pass them around like a soiled blanket: "You're a team that is pushing the boundaries in research, but also you need stop doing that and work on this chatbot that pretends to be a black gay single mother"

All the while you have a sister department, RL-L run by Abrash, who lets you actually do real research.

Which means most of FAIR have fucked off to somewhere less stressful, and more concentrated on actually doing research, rather than posting about how you're doing research.

Wangs misteps are numerous, the biggest one is re-platforming the training system. Thats a two year project right there, for no gain. It also force forks you from the rest of the ML teams. Given how long it took to move to MAST from fblearner, its going be a long slog. And thats before you tackle increasing GPU efficiency.

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Not really a relevant issue or concern for a nation state backed hack…

> Which raises the age-old question of how much technical expertise is really needed in executive management.

For whomever you choose to set as the core decision maker, you get out whatever their expertise is with minor impact by their guides.

Scaling a business is a skill set. It's not a skill set that captures or expands the frontier of AI, so it's clearly in the realm to label the gentleman's expensive buyout is a product development play instead of a technology play.

Can you show me exactly how to pay for open router with monero? Because it doesn’t seem possible.

I could not imagine being as salty as the original poster seems to be about Alex Wang. To hold that amount of hate for a superior that is more successful than you can’t be good for the soul

meta was never "world leading"

I think the high order bit here is you were working with models from previous generations.

In other words, since the latest generation of models have greater capabilities the story might be very different today.

I was just watching the Y Combinator interview with Alexandr Wang who I guess may be being referred to https://youtu.be/5noIKN8t69U

The teenage data labeler thing was a bit of an exaggeration. He did found scale.ai at nineteen which does data labeling amongst other things.

You’re taking this a tad too seriously

There are tons of websites that will happily swap Monero for Ethereum, and then you can use it to pay. Most of those websites never actually do KYC or proper fund verification, unless you're operating on huge amounts or is suspicious in some other way.

Not sure why you're being downvoted, your observation is very correct here, newer models are indeed a lot better, and even at the time that foundational model (even if fine tuned) might've been worse than a commercial model from OpenAI/Anthropic.

    > now run by a teenage data labeller

Do you mean Alexandr Wang? Wiki says he is 28 years old. I don't understand.

pytorch

What other things?

Alexandr

why did they move to fblearner

what is the new training platform

I must know

I watched this interview when I first heard about Alexandr Wang. I'd seen he was the youngest self made billionaire, which is a pretty impressive credential to have under your belt, and I wanted to see if I could get a read on what sets him apart.

Unfortunately he doesn't reveal any particular intelligence, insight, or drive in the interview, nor does he in other videos I found. Possibly he hides it, or possibly his genius is beyond me. Or possibly he had good timing on starting a data labelling company and then leveraged his connections in SV (including being roommates with Sam Altman) to massively inflate Scale AI's valuation and snag a Meta acquisition.

> "world leading" AI lab (now run by a teenage data labeller)

Aarush Sah?

Yeah, I love folks who worry about China having access to models and GPUs. I mean, friend, they have 1.3B people. They could put a crack AI team in every country in the world, tomorrow. But yes, instead, it's far cheaper to let each of those AI teams VPN to any country, all the time.

> Comic hyperbole darling.

Even if you say so yourself.

> I know that's hard to understand, especially when you're one of the start up elect, who still believes.

There's a lot of projection going on in that sentence.

Thanks

Semantic tagging.

Or even a regular guy for that matter... VPNs exist.

a superior is kind of a loaded way to say "executive" or "company's leadership".

Wouldn't it be relatively cheap to use Claude as a self-organizing control backplane for invoking the MCP tools that would actually do the work?

I got the impression he's intelligent and hard working but to a large extent got lucky. I mean his idea was to kind of do a better version of Mechanical Turk which is ok as an idea but not amazing or anything. But then all these LLM companies were getting billions thrown at them by investors thinking they'd be AGI soon but they didn't work well without lots of humans doing fine tuning and Wang's company provided an outlet to throw the money at to get humans to try to do that.

I don't know how that will go at Meta. At the moment having lots of humans tweek LLMs still seems to be the main thing at the AI companies but that could change.

Meta has been itching to kill FBlearner for a while. Its basically an airflow style interface (much better to use as a dev, not sure about admin, I think it might even pre-date airflow)

They are mostly moved to MAST for GPU stuff now I dpn;t think any GPUs are assigned to fblearner anymore. This is a shame because it feels a bit less integrated into python and feels a bit more like "run your exe on n machines" however, it has a more reliable mechanism for doing multi-GPU things, which is key for doing any kind of research at speed.

My old team are not in the super intelligence org, so I don't have much details on the new training system, but there was lots of noise about "just using vercel" which is great apart from all of the steps and hoops you need to go through before you can train on any kind of non-opensource data. (FAIR had/has thier own cluster on AWS, but that meant that they couldn't use it to train on data we collected internally for research (ie paid studies and data from employees that were bribed with swag)

I've not caught up with the drama for the other choices. Either way, its kinda funny to watch "not invented here syndrome" smashing in to "also not invented here syndrome"

So... Tagging and labeling ok.

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They do testing like 'humanities last exam' and they build custom LLMs for some of the largest companies, the defense dept and other US govt stuff - bit here https://youtu.be/5noIKN8t69U?t=2037

Or maybe, just maybe, becoming a billionaire has way more to do with luck than anything else.

I don't know about any billionaire in the history of billionaires who appears to have gotten there solely based on special abilities. Being born into the right circumstances is all it really takes.

If they actually cared, they would just block VPNs. Valve does this when you try to create an account.

Oprah Winfrey? Still some luck but she didn't start in great circustances.

If we're talking about state funding, that's not a problem. You just send a national to live in a residential area and then a team can proxy through that connection.

Surely

I used to work at RL so I instantly knew what he was referring to.

> Being born into the right circumstances is all it really takes.

You do still need to do the work. People have squandered golden opportunities because they didn't put in the effort.

jax

> the same for claude, you're API is tied to a bankaccount, and vibe coding a command and control system on a very public system seems like a bad choice.

Aside from middlemen as others have suggested - You can also just procure hundreds of hacked accounts for any major service through spyware data dump marketplaces. Some percentage of them will have payment already set up. Steal their browser cookies, use it until they notice and cancel / change their password, then move on to the next stolen account. Happens all the time these days.

Where do I write the check?

> Comic hyperbole darling. I know that's hard to understand, especially when you're one of the start up elect, who still believes.

Please omit patronizing swipes like this from comments on HN. You have no idea what the parent commenter "believes", but we know very well that sneering like this only makes HN worse. Please take a moment to remind yourself of the guidelines and make an effort to observe them in future. https://news.ycombinator.com/newsguidelines.html

> But the taste of those really sour grapes must be hard to deal with

Please don't sneer at fellow community members on HN, and don't reply to a bad comment with a worse one; it just makes HN seem like a more mean and miserable place. The comment would have been fine without that last sentence.

Yeah, I gave my AWS root API key to Cursor in agent mode. I learned that AWS charges ridiculous amounts for transferring and storing data.

Content is more important to me than tone.

Much of this subthread is nothing more than gossip about someone people are apparently jealous of. Talk about a "mean and miserable place." Techbros upset that they didn't cash out as big.

Commercial VPNs are relatively easy to block, because they use known IP ranges that companies can blacklist. But it's trivial to set up a private VPN with unique IPs such that VPN blocking becomes much less straightforward and much more resource intensive, for example by using traffic pattern analysis or behavioral fingerprinting.