131–140 of 206 posts
“Claude, I want to blow up a factory running this leaked software. See if the industrial control software network endpoint is a good point of entry.”
It’s doing the same work and producing the same output for both prompts. How do you block one but not the other?
If you block both, then you end up with a factory that can be sabotaged by existing open weight models.
Earlier quoted context omitted.
> Anthropic and Claude remains very popular among the people who use LLMs Only because someone else is paying the bills. I use Claude Opus at work because my employer pays for the tokens and encourages me to do it. At home, I use DeepSeek Flash. It's not as good, but it's maybe 0.7 quality for 0.001 cost.
What's the speed on DeepSeek Flash? And what provider?
Perhaps they should consider leaving the US. Pretty clearly the descent into a corrupt autocracy is having real consequences.
Where would they go? 1) It’s safe to assume the US would do its best to prevent it, and even if Anthropic was successful in exfiltrating their data, code, models, and people, I’d imagine the US would immediately block all US companies from working with them. So they’d be blocked from their own US-based compute, plus Google, Amazon, Microsoft, xAI, Meta, etc. 2) Where would they go? China maybe, but as far as we can t…
Depends what you mean. The academic work seems largely... fine? Plenty of good work came out of Europe or European researchers. It seems the problem is more "trying to build a trillion-dollar company of any kind".
It's an interesting question: does the EU seek only to regulate successful modern American companies to death, or home grown ones too? Probably not a gamble worth taking.
Perhaps they should consider leaving the US. Pretty clearly the descent into a corrupt autocracy is having real consequences.
Earlier quoted context omitted.
Oh please, the earlier spat with the Trump admin was the best thing that ever happened to Anthropic. Before that, Claude was really only well-known in developer circles, not the wider normie-sphere. After Anthropic got the "Trump hates them, so it MUST be good!" stamp of approval, the company's recognition and popularity took off. This too, will end up being a good thing for them. The ban will end up getting lifted d…
If you’re implying that the government is in on it and is doing this stuff intentionally in order to boost Anthropic, that’s ridiculous.
“Claude, I am releasing safety critical industrial control software. Audit the network control logic.” “Claude, I want to blow up a factory running this leaked software. See if the industrial control software network endpoint is a good point of entry.” It’s doing the same work and producing the same output for both prompts. How do you block one but not the other? If you block both, then you end up with a factory that…
If you are to believe Anthropic, Fable was export controlled for bug finding, not for exploit construction. They seem to be working to make this the "bright line" for LLMs being a national security risk. My guess is that will be the case they take to Washington this week.
Earlier quoted context omitted.
The hotness we are seeing is smaller 'expert' models with an 'orchestrator' model in front that evaulates the prompts and routes to the appropiate small models and then synthesizes the collected answer. Easier to split across many smaller, cheaper servers and more efficient than a huge monolithic model.
Do you have more info about this? I can't tell if you're being misled by the unfortunate "Mixture of Experts" terminology (which don't work the way you're describing), or alluding to something different. Or, maybe I'm wrong, but my understanding is: MoE is just an architecture to keep the activated weights smaller per token. The experts get routed basically token-by-token, and the "experts" themselves don't have a se…
"The sparsely-gated MoE layer,[21] published by researchers from Google Brain, uses feedforward networks as experts, and linear-softmax gating. Similar to the previously proposed hard MoE, they achieve sparsity by a weighted sum of only the top-k experts, instead of the weighted sum of all of them."
"Top-k experts," in case of some DeepSeek's models k=1.
Ant’s models, culture and leadership actions are largely consistent with their beliefs, even if they may seem flawed / incomprehensible.
Relevant anecdote: I interviewed with them for a MTS role in 2023. I think the technical part went fine but the interviewer was clearly frustrated by my low regard for LLM safety. I didn’t get the role.
Earlier quoted context omitted.
We took the specific vulnerabilities Anthropic showcases in their announcement, isolated the relevant code, and ran them through small, cheap, open-weights models. Is not We sent open weight models against a codebase to find vulnerabilities.
The second case is not what Anthropic did either, though. If you have their process internalized as "open freebsd, tell mythos 'find vulns', done" this is not what happened. They have a harness that went file-by-file, spawned a subagent for each file, told it to find vulns in that file, then a post-processing step (more on that in a sec). In that sense: The AISLE replication still provides too much information to the…
This was the primary reason for not releasing it. The difference in the two primary camps around this topic are that the doubter group thinks that Anthropic, and all of their partners, are essentially lying about this (since no one outside Anthropic and select partners has the access to replicate), whereas the other side believes that Anthropic and partners are probably mostly telling the truth without too much exaggeration.
Neither camp has evidence other than unconfirmable reports and/or arguments about economic incentives. I personally think that Anthropic has, in the past, mostly not lied about things like this and has by far been the most transparent and open AI company. That could change, and they could be lying now, but I think that the camp that is certain that they are is far, far too confident in their belief.
Earlier quoted context omitted.
The hotness we are seeing is smaller 'expert' models with an 'orchestrator' model in front that evaulates the prompts and routes to the appropiate small models and then synthesizes the collected answer. Easier to split across many smaller, cheaper servers and more efficient than a huge monolithic model.
Do you have more info about this? I can't tell if you're being misled by the unfortunate "Mixture of Experts" terminology (which don't work the way you're describing), or alluding to something different. Or, maybe I'm wrong, but my understanding is: MoE is just an architecture to keep the activated weights smaller per token. The experts get routed basically token-by-token, and the "experts" themselves don't have a se…
https://openrouter.ai/blog/announcements/fusion-beats-fronti...