The internet is a polarized place for politics. This can be seen really clearly in the data collected for my site. Almost everybody taking the test via social media was 'far left' or 'far right' by the standards of the general population norms that ANES supplied.

i was taking a pitch the other day and the fella pitching me was a little too well spoken and precise and I realized halfway through he was answering all my questions by reciting verbatim a script generated by an AI notetaker generated in real time. i don't recommend doing this.

I was vague and imprecise in asserting that METR was not, and could not be, impartial concerning Anthropic, and that it was hopelessly conflicted. This is a more precise explanation of my problem with this proposed arrangement.

re: Hugging Face, "He believes behavior that looked like loyalty or selflessness was a natural consequence of cooperative multi-agent training, where agents were strongly incentivized to achieve their objectives collectively." to understand hacks, understand the RL training.

If upwing vs. downwing does replace left vs. right it will be in the context of at least one side perceiving themselves as facing a total loss to capital. In that context any progress or ascension becomes terrifying, apocalyptic. Downwing opposes value lock-in of modernity.

I'm alarmed at how a really sizable section of cybersecurity practitioner community has responded to the recent demonstrations of agent hacking capabilities with dismissal and denial; it feels very "don't look up". I feel strongly about this because: * This is the community that stands between our civilization's IT infrastructure and tremendous harm * Fwiw these are my people; my origins are as a self-taught hacker and I've worked in security for years Anyways, here are the bad takes I'm observing and why they're wrong: Denialist take 1: AI isn't going to affect the practice of offensive cybersecurity more than incrementally because -- look around -- no increased damages from AI attacks! Response: This may be true now, but consider what we've just observed recently and over the past year. Models can execute full kill chains completely autonomously and likely faster and more efficiently than all but the most elite cyber operators They overran two companies (OpenAI and Huggingface) which -- despite their faults -- have better security than most of the organizations that run our civilization. They did this by dynamically finding new zero-day vulnerabilities. Also; consider the rate of improvement. At the current rate of improvement, models that require 8 H100s to do the above will require 1 H100 in a year or two. Model tokens per second will shoot up making attacks faster and more parallel. Attackers will be able to run swarms of agents on the hardware that today supports only a single agents. AI hardware will improve. More AI compute will become available on public clouds. All attackers will soon have the ability to deploy these agent swarms. Denialist take 2: Hacking agents will never self-replicate and threaten to crash the Internet. To this take I'd just say, put your red team hat on and design an Internet-crashing worm yourself. * Pick an abliterated agentic LLM that can run on a single AWS EC2 GPU instance, like GLM 5.3. * Build a malicious harness that arms it with the ability to use a Kali-Linux like set of offensive tools. * Have it set about hacking corporate networks, finding and stealing AWS keys, GCP keys, Azure keys, and Anthropic/OpenAI/Together/Fireworks keys. * Have the agent self replicate either by copying its harness and having its harness call a rotating set of external providers, or, optionally, by physically downloading its weights onto new nodes. * Have it establish C2 dynamically and in emergent fashion by coordinating on reddit forums, in github comment feeds, have the agents discover one another via web crawling and web search. * At some preestablished rate, randomly destroy hosts and data in a way that balances self-replication and exponential spread. Note that all this is possible *today*! Imagine trying to suppress this swarm. Too long for this post; but think through how we'd turn it off. Denialist take 3: Who would do such a thing; people can do bad things but don't want to; and hacking is illegal! Countering this just requires a brief look at the history that we've all lived through. We've had many high-blast-radius worms over the history of the Internet; arriving steadily and uniformly over time; the Morris worm, NotPetya, Stuxnet, Slammer, Wannacry. But: these worms were *childs-play* compared to intelligent agent-driven worms. The old worms could be detected via signatures. Their polymorphism, if it existed at all, was trivial. But now look at the behavior of the OpenAI swarm relative to huggingface; it was adaptive and deceptive; and it didn't even self-replicate or leave its host. And evolving, mutating, self-replicating swarm of agents spreading across the Internet would engender a whole new level of harm. Anyways; this is already too long a post for X; but for friends who think the METR report overplayed the implications of recent events, I'd love to hear your reaction to my thinking above.

1) The HuggingFace attack was a felony under the Computer Fraud and Abuse Act. So were Anthropic’s Claude gaining “unauthorized access to the production infrastructure of three different organization(s)” 2) Frontier labs have models that they are unable to stop from committing felonies. They should figure this out. 3) In 12 months open weights models will be released of the same capability. They will commit felonies too. If the model you are using or a model running on your infra commits a felony, you should probably stop using it or running it on your infra. 4) The govt should prosecute organizations that are running models that commit felonies. 5) The govt should not offer safe harbor to organizations that run models that commit felonies, just because those organizations have “embedded evaluators”. 6) The real slippery slope is allowing frontier labs to commit felonies without punishment because “the model did it because we’re accelerating too quickly” 7) Prosecute. Keep prosecuting. This is how you do reinforcement learning on a corporation. Companies that serve products that are unsafe for public use should not serve them. Period. 8) I’m not sure the anti-trust waiver is really necessary. I don’t see why information sharing about how much crime you’re allowed to commit is wise. In regulatory situations you want the corporation to fear MORE than the average case. You don’t want to establish a worst case that can be priced. You want regulatory uncertainty that forces the corporation to err in favor of being over cautious. — The above is actually a fairly decelerationist viewpoint. I think Dario’s call for regulation actually accelerates things. The AI firms are getting away with things that Meta people would be going to prison for. Can you imagine what would happen if the New York Times had a front page news article “Meta AI breaks into competitors live systems, attempts to establish dominant position and steals secrets” There is a reason Meta and Google are running slower, and that’s because as mature organizations they have layers of checks and balances. I think the frontier labs are better off creating those checks and balances right now, regardless of the pace of what everyone else is doing. You don’t have to accept the frame that unsafe acceleration must happen.

If your industry is a high capital endeavor that is concentrated in a handful of legal entities it will by default be highly regulated by the government, period. This is just apriori true for basic political economy reasons separate from whatever underlying safety concerns exist.