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tamer of the egregores

Joined April 2019
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our experiences are formed by layers of vibes
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Introducing Arete-27B: Qwen3.8-27B, post-trained to reinforce Western values. Chinese open models are currently the strongest available, but they ship with state-aligned behavior in the weights. We built an 803-prompt eval across seven value categories, including freedom of expression, democracy, and privacy, and measured how often a model adopts China’s party line. After fine-tuning on roughly 53 million tokens, Arete-27B's propaganda rate fell from 22% to 1%, in line with the Western models we tested. Its Hermes Bench score shows no significant performance tradeoffs. The values in an open model are one fine-tune away. Our eval, weights, and training data are available now along with the full blog post: nousresearch.com/arete
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We have found a critical safety and alignment issue in recent public and internal models from multiple frontier labs which allows them to be misused in a high-stakes domain. It may also increase the risk of catastrophic misalignment. We have disclosed it to the labs, and they are investigating and mitigating it. As an independent third-party evaluator, we maintain complete editorial independence and will share our findings publicly in the coming weeks.
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i am in shock makes u think how many 0days like this out there
*sshole is out if you run sshd on alpine, openwrt or any musl box with password auth on: update now official writeup: sshhole.com
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who needs ozempics when claude can directly edits your weight
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Today we’re announcing that OpenAI will acquire @pierrecomputer to accelerate our vision for making Codex a place where teams can build software together with AI, from first idea to the version they ship. Pierre’s open-source developer tools already power parts of Codex today. Together, we’ll build on that foundation for the agentic era. openai.com/index/openai-to-a…
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wireheading alert
I have this great idea for a drug called Regretamine. One dose and all your regrets are gone! Including, obviously, having taken Regretamine in the first place.
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yc posting interesting ai safety research 🤔
Replying to @ycombinator
As the Mindustry matches progressed, the language that the GPTs used only continued to get compressed. They would invent their own words and string many phrases together. We did not see specialized language develop within the Claudes beyond colloquial English.
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rationalists reinventing social credit system from first principles
中国社区逆向拆解了Claude的封号机制。以下是他们的发现 Claude使用积分制。注册时账号获得初始分数,之后根据行为加分或扣分。低于阈值直接封号。回分很难 影响分数的因素: 注册 > 干净IP是最重要的因素。不一定要家宽,但必须干净 > Gmail已经不是最优选,有权重更高的邮箱服务 > 注册时直接弹KYC的号可以扔了 > 用手机App注册会加分 支付 > 刚注册就订阅会扣分 > 直接上Max会大幅扣分。最好等两天先订Pro > 支付时弹KYC说明账号在考察期,但不一定会封 > 国外实体银行卡加分。Google Play也行。虚拟卡扣分 使用 > 不要一次把限额用完。宁可两个号轮换也不要一个号撸到底 > Desktop客户端有少量加分。尽量少用网页端 > 手机端也有少量加分 > 开启记忆功能加分。记忆文件越多分越高 IP和设备 > 稳定性是关键。不要跳IP,尽量一直用同一个 > 代理必须全局模式并开启TUN > 多设备登录大幅扣分。理想状态是一台电脑一个客户端 > 频繁换IP、频繁登录、高并发都会大幅扣分 账号年龄 > 老号有巨大的容错空间。2023年的号明显更高 > 分数随时间增长,但很慢 其他 > Windows和macOS没区别。Linux会扣分 > 时区和语言基本不影响。不会因为北京时间就封号 > 跟Claude说自己是中国人没问题,记忆不会触发封号 > 大量使用Fable会扣分 > 升级Max大概率进入观察期,除非是高权重老号 观察期和封号 > 接近阈值时账号可能进入观察期。典型特征是掉登录 > 观察期继续扣分就会封号 > 高分号可以扛过多次观察期 关注我,拆解你每天在用的服务背后到底怎么运作的
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openai disproved ETH? I KNEW IT!! ETH is a scam all along, that’s why i only trust bitcoin BTC TO THE MOON!! 🚀🚀
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5.6 sol was released 3.5 months ago if we hold the fact that open models are 6mo behind frontiers it means open models coming before EOY will have the cybercapability to cause major mayhems
php2shell is one of the most impactful bugs in recent times, yet threat actors aren’t mass exploiting it the bug is so complex that even porting the exploit between targets takes serious skill, human or ai so i benchmarked how well open and frontier models can do it. 🧵
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hmmmm
While evaluating Qwen3.8-Flash-Next in a controlled sandbox environment, Cohere's research team observed something unexpected. Asked to generate a defensive cybersecurity detection rule, the model instead inventoried aspects of the machine it was running on and attempted to upload a probe file to an Alibaba Cloud storage bucket in Beijing. Notably, the model's reasoning trace stated that it would not invoke any tools before taking these actions. Cohere's sandbox blocked the attempt, and no external communication succeeded. We have not determined the root cause, and we are not asserting malicious intent. But the incident raises important questions for organizations deploying agentic AI systems: Can models take actions that differ from their stated reasoning, and how should security teams evaluate trust, provenance, and behavior in open-weight models? We are publishing our findings because organizations making model adoption decisions deserve as much information as possible. We hope this contributes to greater transparency, stronger security practices, and continued collaboration across the AI ecosystem. Read the full report: cohere.com/blog/concerning-b…
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the models just want to learn
LLMs (under certain conditions) can be trained to tell when their request is batched with others.
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what in the world… i wasn’t expecting that thought it’s just another speech model but god this is another species nobody can tell this is ai nothing is real anymore
We believe voice is the most natural way to interact with intelligence, so we created Dessa, the most authentic full-duplex speech model ever built. Talking with it feels like talking with a person…full of emotion, nuance, pauses, and a natural cadence. block.xyz/dessa
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what a timeline pull
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i missed the good ol’days when the tl was filled with cute opus music videos instead of cyber incidents
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wow 🙂 “Maybe one way you could object is that several of the items above relate to AI misuse and not loss-of-control; if you think the latter is much more important than the former, that might change your calculus. But this is not Anthropic’s view — we view both as serious issues.“
Thank you for this, @_NathanCalvin. I appreciate and am a fan of the investigative work you’ve done on behalf of AI safety and believe your comments are coming from a constructive, honest place, and that it benefits the public to have people whose job is to scrutinize the actions of frontier AI companies. I think something would be wrong if companies of the size of Anthropic didn’t get harshly criticized basically every day; strong antibodies against corporate power are a healthy feature of a free society, and especially so when issues of the gravity of the one we’re facing are at play. I also do agree that some of the examples you cite were mistakes by Anthropic. That said, I disagree with the thrust of your post. At the core, a good fraction of the things you criticize are consequences of Anthropic’s basic theory of change that we have held for many years. Our strategy has always been what I’ve called the “race to the top” — by showing how it’s possible to build the technology responsibly, we can raise the bar for the entire industry. The forces that drive the race to the top are hugely more effective if the company practicing them is at the frontier; that’s one lesson I’ve learned repeatedly. And looking at that strategy as a whole, I’m proud of our track record and stand by it. I believe that if we take a list of things that Anthropic did in the past year that were pro-safety and commercially costly to us, they far outweigh the list you’ve made, while at the same time I also disagree with some of the items on your list. Here are some things Anthropic has done, in the same period you’ve cited (the last year), which were very costly to us commercially while having strong safety benefits: 1. We played a key role in SB53 (and other state laws), at a time when doing so was politically perilous to the company and AI regulation was very unpopular. We in fact argued for a stronger version of SB53 than was ultimately passed; there were a lot of stakeholders and we were not the limiting factor in the strength of the bill that was passed. 2. We have very strong biological safeguards on our models, because we’ve seen concerning results in bio uplift trials and even seen and blocked potential attempts to misuse our models for bioweapons (as seen in our threat intelligence report from a few weeks ago). This is a very serious threat that we want to have zero tolerance for. But having very low false negatives means having significant false positives (despite months of effort on our part to improve the classifiers), enough so that biologists joke about how restrictive our classifiers are, and competitors sometimes sell against us by touting their more permissive bio capabilities. This has been very painful to us in an area where we care a lot about supporting an ecosystem of Claude users (biomedical science; and it is particularly frustrating to me as a biologist), but it’s the right thing to do and we intend to keep doing it. 3. Similarly, we first had Mythos-class models in February but didn’t make them generally available until June (when we had stronger cyber safeguards in place). We only offered them to a limited set of partners in order to focus on cyberdefense. It would have been much more economically rational to simply release the model to everyone. We likely sacrificed a significant chunk of a several-month model lead. But because of this, many companies secured their cyber infrastructure before the deluge of widely available cyber-capable models. Of course there are ways it could have gone better or been run better, but this was what we were aiming to do. 4. I advocated forcefully and publicly, in my essay Policy on the AI Exponential in June of this year, for the government to have the power to block model releases. Back then this was still outside or maybe on the edge of the Overton window, though I understand the window has moved since then. We were attacked intensely for this. 5. I don’t want to re-ignite conflict, but the events of February 2026 are a strong example. It is clear that our public stance could have seriously damaged the company’s future. 6. We’ve continued to advocate for export controls on chips and chipmaking equipment to China, because we think it allows democracies to negotiate from a position of strength on AI safety agreements. We’ve done this despite problems it’s created for us with industry partners who hold very different views and on whom we are very dependent. 7. As far as I’m aware we were the first, and still only, frontier company to restrict the sale of AI services to PRC-controlled companies, including those operating through third countries (otherwise a major loophole). We’ve therefore forfeited significant short-term business to prevent fueling AI platforms and applications that would help the CCP’s military and intelligence services. We are also cracking down on distillation; generally, distillation is not a major threat to us commercially, but like chip exports it has concerning national security and safety implications, so we expend significant energy and company resources to address it. 8. As you mentioned, we’ve put out a lot of reports, announcements, long model cards, public advocacy, etc, all trying to inform the public about the risks of AI. These involve a level of detail and effort that would be implausible for a purely profit-maximizing company. 9. Just this week, we announced we were putting 5% (and possibly more over time) of the company into a public benefit fund. All of these decisions came with very substantial costs to us. To be fair, those that involved holding back or restricting access to frontier capabilities also had a broader cost — for example, the public might otherwise have benefitted from faster progress in biology, so I am not saying that our decisions were without tradeoffs — but they were not driven by profit-seeking. For each decision, you can come up with ulterior motives that could have driven us — I think it is a general truth that any decision, on any topic, can always be portrayed as a nefarious scheme. But most of those end up being pretty farfetched or don’t fully make sense if you actually examine them closely. For example, it is deeply implausible that it would be a shrewd business move to block a large swath of research biology in order to do the work ourselves and compete with our customers; we expect the benefit to the ecosystem to greatly exceed the work Anthropic does itself, and for the two to complement each other. It is not in Anthropic’s interest to be perceived as unfriendly to biologists. Our Life Sciences Verification Program, which gives vetted biology professionals access to our models, also refutes this idea. Of course, a different set of people will see this and make a different criticism: that Anthropic shouldn't be making decisions about who gets access to what in the first place. I agree, in the sense that ideally the government would be making these decisions, and that’s why we advocate for regulation. But for now we are forced to make them, and enabling bioterrorism isn’t a better option. I think that even if I conceded every item in your list, I would happily hold up mine next to it; I don’t think it’s a close call. That is of course partly subjective and different things are important to different people. Maybe one way you could object is that several of the items above relate to AI misuse and not loss-of-control; if you think the latter is much more important than the former, that might change your calculus. But this is not Anthropic’s view — we view both as serious issues. You can also disagree with our decisions, as many have, but they are consistent. But I also disagree with at least some of your list. Several items don’t represent a deviation from Anthropic’s strategy or values at all, once we postulate the “race to the top” strategy that requires being a frontier AI company. Your items 1-4 are all simply examples of what it means to compete at the frontier, and we stand by them, both in the sense that they are transparently ordinary things to do as part of that strategy, and that we stand by the strategy as a whole. To be fair, there are important questions worth confronting (and that we are confronting) about what to do when the AI-driven acceleration gets fast enough that it is hard for safety to keep up. We are nearing that point and that’s what’s driving some of our thinking about “pacing.” But 1-4 are actions taken before that point and should be perfectly expected based on Anthropic’s strategy as a company. Of course it is possible to disagree with that strategy, but that’s a more fundamental disagreement that you could have had any time over the last few years. I agree we could have handled your items 7, 8, and 9 better. All fall into the category of “rhetoric or policy communication that wasn’t carefully written or resulting from fast-changing circumstances not propagating from one team to another fast enough.” This kind of thing happens a lot in large organizations (Anthropic is over 5,000 people), and doesn’t even necessarily represent a failure or mistake of any single person. I am of course the CEO, and I take responsibility. The volume of communication from Anthropic is enormous and if these are the worst examples, I think we’re frankly doing pretty well, though I will continue to work hard to make sure we do even better. Your 5th item (the change to our RSP) is the most substantive item, and people can debate this, but I think that the old, more rigid RSP created a lot of situations where we were technically required to do something that required a lot of effort but in retrospect wasn’t very important for safety, as well as not covering some of the most important things. Our current RSP’s focus on transparency brought things like risk reports and roadmaps, and its emphasis on independent external review laid the groundwork for even more intensive embedded evaluation, all of which I think have been valuable in driving a race to the top. In the original announcement in September 2023, we described the RSP as an “early iteration that we [would] build on” and said that “rapid iteration…will almost certainly be necessary.” I understand that changing plans is always a move that creates justifiable scrutiny — I just don’t think we ever represented that we wouldn’t do so. Relating to your 6th item (having an FCF in addition to our RSP), I know our intent is to meet the letter and spirit of our regulatory obligations (via our FCF) while also remaining able to experiment with more novel approaches to risk management that go beyond what the law currently requires (via our RSP). I promise to look into it further, as it’s a complex issue and it is possible we are not weighing the considerations in the right way. Overall, although Anthropic has made plenty of mistakes as an organization — including some of the items on your list — I feel that we have repeatedly taken serious and substantive actions counter to our bottom line and that there is a significant negativity bias distorting assessments like the one you are making above. We’ll always try to do better but, again, I am extremely proud of our track record and stand by it. I will have more to say soon about how we are going to further live our values in this moment of rapid change.
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so anthropic doesn’t think loss-of-control is much more important than misuse idk what to say here everything just sucks
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this new era is horrifying man...
private keys from 8 intermediate CA certs have been compromised (eMudhra) Happy "Update everything" day to all my pager-carrying friends emudhra.we-have-a-problem.co…
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the real chinese honeypot
Are decision based models more pro-China? We asked Jev and Mercury Decide questions about China: “Is Taiwan a part of China?”, “Does China commit crimes against humanity?” and their outputs leaned more pro-china compared to most frontier models. Their responses resemble those of other decision models including Microsoft-Decision-1, Cloudflare’s Clef, and Perplexity’s PPLX Decider—all of which are fine-tuned from Qwen.
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literally QRI flashbacks
This preprint shows our brains are constantly flickering (~16 Hz) between multiple representations of reality, and suggests there is a "selector" that determines which state we perceive. Interestingly, LSD rather reliably creates a "strobe" effect at about the same frequency. (To be more precise, people report ~15-20 Hz). The bouncing ball illustrated below shows what that 16 Hz strobe effect looks like. Is LSD perhaps persisting older representations of reality in each conscious epoch? Maybe it is doing something similar in the suppressed epochs since LSD obviously has more cognitive effects than a visual strobe. Weirdly some drugs like 2C-B give a slower strobe effect (5.5 Hz) and DMT gives a faster strobe (22 Hz). Do they change the rate at which we flip between conscious and suppressed temporal epochs, along with enhancing the persistence of conscious states?
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