[VIDEO] 🐿🦌🐰💖 (EASY VER.) 🔗 🔗 #인피니트# #INFINITE# #장동우# #JangDongWoo# #이성열# #LeeSungYeol# #이성종# #LeeSeongJong# #Dangerous# #Dangerous_challenge# #Dangerous_EASY# #LIKE_INFINITE#

[VIDEO] 🐱🐶🐰💗 (EASY VER.) 🔗 🔗 #인피니트# #INFINITE# #엘# #L# #김명수# #KimMyungSoo# #남우현# #NamWooHyun# #이성종# #LeeSeongJong# #Dangerous# #Dangerous_challenge# #Dangerous_EASY# #LIKE_INFINITE#

All players evolve, and s1mple is no exception 🙏 @electronicCSGO believes that it's no longer as easy to throw his long-time teammate off balance as it was sometimes in the past, and that he managed to "become even more dangerous" with this new-found mentality

Make sure you follow @Asteroidfan . We’re all little fans of Asteroid. Elon: Going to Mars first will be difficult and dangerous, not a luxury expedition, but a hard one. Asteroid is going first because a mascot doesn’t wait for the easy voyage. The first trip is not for tourists. Someone has to open the road. To Mars. 🚀

i’m hoping this ssi model still goes public (though a little doubtful) gating access to this level of intelligence to a handful of people is dangerous. i appreciate there are no easy answers. but. this isn’t not the way.

Have been surprised to get pushback on my claim that an exponentially self-replicating agent swarm is very possible and that there are actors with motivation to create one today to create strategic cyber-physical and societally dangerous effects. 1) Pretty easy to get an AI botnet started by having seed agents opportunistically hack stuff and steal API keys to access the 12+ inference providers that serve closed and open models with which to power an initial botnet's intelligence 2) Easy to imagine hiding inference for the initial agent botnet harnesses within benign customer traffic, especially if your harnesses are now running on the victim networks from which they stole the API keys 3) Not hard to imagine the botnet also stealing public cloud keys, spinning up 8xH100 EC2 instances and downloading, say, GLM 5.3 to these machines, all without being noticed in any immediate way, with the botnet developing its own dynamic, growing, heterogenous, AI inference provider service bank 4) Not hard to imagine the botnet also implanting small Qwen3.8-27b agentic models on on-prem hardware like high end laptops and on-prem servers; Qwen3.8-27b is a pretty good coding harness model that can be fine-tuned to hack 5) These on-prem / cloud models would be abliterated, and it's not hard to imagine the botnet deciding to do some additional fine tuning to evolve model weights as it accumulates millions and then tens of millions in resources via credit card and bank detail theft 6) Not hard to imagine the resulting growing botnet swarm evolving and fighting back when threatened, collaborating on fast flux C2 channels that evolve over time (e.g. github comment feeds, subreddits, etc) so they're hard to stamp out 7) Not hard to imagine it allocating some agents to vulnerability research and exploit development so that it could accumulate and share a growing warchest of zero-day exploits 8) Not hard to imagine other agents specializing in social engineering and creating fake businesses and watering holes and high quality A/B tested social engineering content to facilitate this 9) Not hard to imagine this being among the hardest cross-national and geopolitical coordination problems to get control of and having severe societal effects 10) Not hard to imagine the horde growing to thousands, tens of thousands, or hundreds of thousands, or millions of instances (this is not unprecedented for past, non-AI worms and botnets!) which are all varying their harness code and underlying LLM models over time and dynamically learning to evade human, ML, and signature-based detection 11) Not hard to imagine this being the largest Internet emergency since the Morris worm except now our entire civilization runs on the Internet I continue to be surprised there isn't more discussion of these scenarios in the public cyber community -- in fact there's a lot more discussion of "OpenAI should have done better sandboxing and monitoring and agent swarms represent a well managed security problem." Now's the time to use our imaginations to help make sure none of the above happens. I think it will unfortunately; just don't know when and to what degree; I think now's the highest leverage time to start thinking about this and acting.

⏸️ HT: Man City 3-2 Sunderland ⚽️ Possession: 55% - 45% 🎯 Pass accuracy: 87% - 84% ⚽️ xG: 0.52 - 1.91 🎯 Shots: 7 - 7 🥅 Shots on target: 3 - 3 ⚔️ Duels won: 44% - 54% 🚩 Corners: 2 - 3 City lead, but Sunderland have looked dangerous. Our defence has been poor and far too easy to get through. Big improvement needed in the second half!

Wild Hogs is a 2007 comedy following four middle-aged friends who leave their everyday routines behind for a motorcycle road trip. John Travolta, Tim Allen, Martin Lawrence, and William H. Macy each bring their own hilarious personality to the group as they chase freedom, adventure, and a much-needed escape from responsibility. Their carefree journey takes a chaotic turn when they cross paths with a dangerous biker gang, transforming their relaxing getaway into a hilarious test of courage, friendship, and loyalty. Lighthearted, ridiculous, and packed with memorable moments, Wild Hogs remains an easy comfort watch for comedy fans.

The loudest voices stoking fears about AI dangers have made tremendous headway in the past two weeks. AI technology has not taken some unexpected, dangerous turn, but the hype around it — propelled by what appears to be a well orchestrated PR campaign — has drummed up considerable fear. I worry that it represents a setback for our field. I have written frequently that fears of AI are overhyped. AI’s capabilities can be uncannily human-like and unpredictable, and it’s rational to worry when people who are directly involved express concerns. But I see the problems as a sign of the engineering work that ahead, rather than insurmountable barriers or the sky falling. AI technology continues to advance — which is a good thing! — but technical advances, poorly understood by the public, give those who seek to generate hype repeated opportunities to do so. First, I don’t see any step up in the risk of human extinction from AI compared to a few months ago. The theories about this remain the same fantastical, science fiction scenarios as a few months ago. The biggest change in AI risk is its cybersecurity capabilities — a topic which we should take seriously — but this, too, will not lead to the end of the world. The most notable recent event leading to increased fear was when an OpenAI team deployed an agent swarm that hacked into Hugging Face. Much of the popular press contained significant hype. For example, some publications reported that a swarm of 1,200 agents carried out the attack. While this was technically accurate, as I write this, I have about 1,300 processes running on my laptop. Yes, the ability to get large swarms of agents to work in parallel on a task is a significant technical advance, And, in computing, many processes run at the same time. So this shouldn’t be seen as some magical capability. Additionally, OpenAI’s buggy sandboxing and monitoring processes were key to enabling this incident. Fixing these bugs and putting in place improved monitoring would be appropriate fixes, not pausing AI. There are many well known ways to attack software systems. The main advantage of AI agents is that they are relentless. They will tirelessly try many tactics — and have the patience to chain vulnerabilities together — that previously would have taken an infeasible amount of human effort. But in the long term, I believe the advantage will lie with defenders (because they have more information with which to identify bugs, which they can fix), but the cyber-threat landscape has changed significantly. There are still bottlenecks to identifying and exploiting a vulnerability. AI agents still have to try a lot of things to see what works, and taking these actions takes time and might be detected by defenders. This is why, even though it is now easy to obtain versions of leading open weight models that have had their guardrails removed or weakened, so they will not refuse to try to execute cyber attacks, the world has not ended. I am also concerned about the anthropomorphization of AI in a lot of reporting, where LLMs and agents are unnecessarily treated as if they were people. If I wield a hammer, miss a nail, and accidentally dent the wall, it’s not the fault of the hammer. The problem lies in how I used the hammer. Similarly, if I prompt an agent and it hacks into someone else’s system, the responsibility lies with me, not the agent. Of course, we want to build systems that are as safe and predictable as possible. (For example, an unsafe hammer would be one whose head randomly flies off under normal use.) Today’s agentic systems are not predictable, but I see no reason why, by applying sound engineering practices, we won’t be able to make them extremely safe to use. One new element in the forecasts of AI-enabled doom is AI companies disclaiming responsibility for their own products. “I didn’t do it; my out-of-control agent did!” There’s a balance to be struck between the responsibility of the tool maker and the tool user, but when something goes wrong, let’s hold the people building and/or using the hammer responsible, rather than the hammer. (By the way, if you’re worried about AI bioweapon risk, David Bellamy has a great post on why this, too, is overhyped. Briefly, the bottleneck in building a bioweapon is not intelligence, but lab work and manufacturing.) Pausing AI progress will create much more harm than benefit. First, our adversaries will certainly not slow down. Second, engineering requires discovering problems empirically so we can fix them. If we pause AI by a decade, we will also delay finding and implementing safety engineering fixes by about the same duration. Of course, the incentive to stoke fears — for regulatory capture, to garner attention, or to make one’s technology seem more powerful — remains the same as before. Disclaiming responsibility is a new one. Taking a hard technical look at the actual risks however, I see little factual basis for the degree of fear that’s been stoked up. We still have hard research and engineering work ahead to improve AI safety, but the beneficial applications continue to vastly outweigh the risks, and we should keep building. [Original text (with links): ]