Artificial Intelligence Safety

Top stories in AI Safety today Containment proposals, runtime controls and early warning signals. Three developments, two AI Safety Review reads, and one practical question: which safeguards can actually stop an unsafe action?

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@Muzammil_OX @AnthropicAI AI safety needs a balanced approach: explore the uncertainty while keeping human oversight and control at the center. 🤖

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Riskpro was proud to be a Silver Partner at the 4th AI Impact Confex & Awards 2026 – Mumbai Chapter, held on 7 October 2026 at ITC Maratha, Mumbai. Ashok K. Agarwal, joined industry leaders for panel discussion on “AI Safety, Robustness, and Alignment” #riskpro #AIImpact2026

Existing liability and market forces are sufficient for AI safety

Nvidia, worth $5.5tn, donates $250m to UK for AI safety research Source: The Guardian

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Singapore in one day: Google's Gemma fights scams, Anthropic signs an AI safety deal Anthropic is opening an office in Singapore and signed an MOU on AI safety with the Singapore government, the same day DeepMind showed its on-device anti-scam work with GovTech.

Existing liability and market forces are sufficient for AI safety

@Muzammil_OX @AnthropicAI new developments in ai safety are really promising now

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🔥 NVIDIA IS PUTTING $250M BEHIND AI SAFETY. The chip giant is donating computing power to UK researchers over five years. As AI agents gain more independence, controlling what they can do is becoming a business priority. More power needs better safeguards.

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Anthropic opened an office in Singapore and signed an MoU with the government to cooperate on AI safety.

Existing liability and market forces are sufficient for AI safety

@mbhbox AI made this decision to protect AI safety

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#Nvidia is dedicating $250 million in computing resources over five years to support AI safety research in Britain, focusing on agent testing and supporting independent university projects. https://t.co/Cwti55bMWe #AI_Safety #Artificial_Intelligence TRANSLATED

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🇨🇦 — The Next Great Canadian Technology Company Could Be Built Around Intelligence Beyond AI. The world is investing billions in artificial intelligence. More powerful models. More autonomous agents. More sophisticated reasoning. More computing infrastructure. But an even bigger question is beginning to shape the future of technology: What happens when intelligence exceeds human capability across a broad range of intellectual tasks? That possibility is commonly called Artificial Superintelligence (ASI). It remains a future possibility—not an established technological achievement. Yet the scientific, economic, and governance questions surrounding advanced AI are already significant. Who develops these systems? Who evaluates their capabilities? Who establishes safety requirements? Who controls access? And which countries will build the expertise needed to participate in this emerging technological frontier? Canada has an opportunity to help shape the answers. Introducing — Canada's Gateway to Superintelligence. 🚀 THE COMPANY CONCEPT: SUPERINTEL CANADA Imagine a Canadian advanced AI research, evaluation, and enterprise intelligence company focused on technologies that could contribute to increasingly capable AI systems. Not another generic chatbot. Not another AI wrapper with a futuristic name. Not a company claiming to have already achieved artificial superintelligence. A Canadian advanced intelligence platform connecting AI research, model evaluation, enterprise applications, and responsible technology development. Six potential technology divisions: 🧠 SuperReason™ — Advanced Reasoning Systems Research and develop AI-assisted reasoning workflows for complex analytical tasks. Help organizations approach difficult problems with more capable tools. ⚡ IntelCompute™ — AI Infrastructure Intelligence Support efficient use of computing resources across approved AI workloads. Make advanced intelligence infrastructure more practical to operate. 🤖 AgentCore™ — Autonomous Workflow Intelligence Develop permission-controlled AI agent systems for research, enterprise automation, and structured decision support. Turn intelligence into useful, supervised action. 🔬 FrontierLab™ — AI Research & Evaluation Investigate advanced model capabilities, limitations, and evaluation methodologies. Measure progress rather than relying on hype. 🛡️ SuperSafe™ — AI Safety & Governance Support model testing, access controls, monitoring, human oversight, and responsible deployment. More capable intelligence demands stronger safeguards. 🌐 IntelConnect™ — Canadian AI Ecosystem Connect participating researchers, developers, institutions, and enterprise partners. Build relationships across Canada's advanced AI ecosystem. 🌍 THE COMMERCIAL OPPORTUNITY Canada has an established AI research ecosystem, including important academic institutions, research organizations, and technology companies. But research leadership alone does not guarantee commercial leadership. The next challenge is translating advanced AI expertise into useful enterprise technologies, responsible infrastructure, and globally competitive businesses. could position itself at that intersection. Three commercial directions stand out. 1. Advanced enterprise AI Developing specialized reasoning and agentic systems for complex professional workflows. 2. AI evaluation and governance Helping organizations assess model capabilities, reliability, and operational risks. 3. Canadian AI infrastructure and research commercialization Supporting partnerships between research teams, enterprise customers, and technology developers. The strongest initial strategy? Start with AI evaluation and enterprise reasoning tools. Develop measurable benchmarks. Focus on a specific industry. Build a reliable commercial product. Establish research partnerships where appropriate. Expand into more advanced capabilities as the technology and evidence justify them. The opportunity isn't promising superintelligence tomorrow. It's building a credible company positioned for the long-term evolution of advanced AI. 🧠 THE STRATEGIC MOAT 1. Canadian positioning — A recognizable national identity in an important AI research market. 2. Research credibility — Evidence-based evaluation and collaboration with qualified experts. 3. Enterprise specialization — AI systems developed around commercially valuable workflows. 4. Safety-first engineering — Strong model evaluation, security, and human oversight. 5. Infrastructure expertise — Practical understanding of AI computing and deployment requirements. 6. Category-focused branding — A concise domain directly associated with advanced intelligence. The moat isn't using the word “superintelligence.” It's developing technology, expertise, and institutional trust that can support increasingly capable AI systems. 🔄 THE SUPERINTEL FLYWHEEL An enterprise partners with → FrontierLab™ evaluates relevant AI capabilities. → SuperReason™ develops appropriate reasoning workflows. → AgentCore™ supports supervised automation. → IntelCompute™ improves infrastructure efficiency. → SuperSafe™ establishes governance controls. → IntelConnect™ supports collaboration with qualified Canadian partners. Better evaluations inform better systems. Better systems create enterprise value. Enterprise adoption supports continued research and development. 💰 THE BUSINESS MODEL Potential revenue streams: 🇨🇦 Enterprise AI software subscriptions. 🧠 Advanced reasoning technology licensing. 🔬 Model evaluation and testing services. 🤖 Agentic AI platform subscriptions. 🛡️ AI governance software. ⚡ Infrastructure optimization services. Consider a hypothetical enterprise SaaS scenario: 200 organizational customers. $1,500 average monthly subscription. $3.6 million in annual recurring revenue. This is illustrative, not existing revenue or a validated forecast. Actual economics would depend on research costs, technical performance, computing infrastructure, customer adoption, safety requirements, and competition. The commercial opportunity is recurring enterprise revenue built around increasingly sophisticated AI capabilities. 💎 WHY SUPER + INTEL Two short, powerful elements. Super evokes advanced capability, exceptional performance, and the concept of superintelligence. Intel evokes intelligence, information, and analytical expertise. Together: A distinctive name for an advanced intelligence company with a Canadian identity. The .ca extension directly establishes a Canadian digital presence. Potential applications include: An advanced AI research company. A superintelligence-focused technology publication. An enterprise AI platform. An AI safety and evaluation business. A Canadian AI innovation network. An agentic AI infrastructure startup. A frontier technology research organization. Or an advanced intelligence investment initiative. is short, memorable, and naturally aligned with the language of advanced AI. Trademark clearance would be important, particularly because “Intel” is also an established technology trademark. 🎯 THE IDEAL ACQUIRERS Canadian AI startups, enterprise AI developers, AI research commercialization teams, model evaluation companies, AI governance providers, agentic AI infrastructure businesses, frontier technology venture studios, and investors building Canadian advanced intelligence companies. A particularly compelling buyer would be a Canadian technology company seeking a concise national brand for advanced AI research and enterprise applications. could become the flagship identity for a Canadian advanced intelligence initiative. 🌎 THE BIGGER VISION Imagine Canada developing a stronger commercial ecosystem around increasingly capable AI systems. Researchers investigate new model capabilities. Engineers build reliable infrastructure. Businesses deploy useful applications. Independent evaluators examine risks. Institutions develop responsible governance practices. And entrepreneurs turn research into competitive companies. Now imagine one recognizable Canadian brand connecting part of that ecosystem. Not claiming to control the future of superintelligence. Not suggesting that AGI or ASI has already been achieved. Not treating speculative technology milestones as guaranteed. A credible commercial identity for participating in one of the most consequential technological developments of the coming decades. The future of advanced intelligence will require more than powerful models. It will require research, infrastructure, responsible engineering, and organizations capable of turning new capabilities into genuine value. That's the opportunity behind 🚀 DOMAIN ACQUISITION & PARTNERSHIP OPPORTUNITY Available now at the marketplace. We're also open to partnerships with Canadian AI founders, frontier technology researchers, enterprise AI developers, AI safety entrepreneurs, venture studios, venture capital firms, and experienced investors interested in building an advanced intelligence platform around The products and services described are proposed venture concepts, not existing operations. The next era of intelligence is still being written. Canada has the talent to help write it. 🇨🇦 — Canada's Gateway to Superintelligence. #SuperIntel #SuperIntelCA #Superintelligence #ArtificialSuperintelligence #ASI #ArtificialIntelligence #AdvancedAI #FrontierAI #CanadianAI #AIResearch #AgenticAI #AIAgents #AIInfrastructure #AISafety #AIGovernance #EnterpriseAI #FutureOfAI #DeepTech #CanadianTechnology #AIInnovation #TechStartups #VentureCapital #DomainInvesting #PremiumDomains #DotcomsIO

Existential AI risk is overblown hype

@AnthropicAI Singapore office plus AI safety MOU is a strong APAC signal

Existing liability and market forces are sufficient for AI safety

@Cointelegraph Singapore is strengthening its position in the AI race. 🇸🇬🤖 Combining innovation with AI safety will be crucial as the technology scales globally.

Existing liability and market forces are sufficient for AI safety

@Muzammil_OX @satyanadella I agree, Ai safety should always come first

Existing liability and market forces are sufficient for AI safety

@nvidia is putting $250 million into AI safety research in the UK. Making sure it behaves safely is becoming just as important as building it.

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🇸🇬 NEW: Anthropic opens a Singapore office and signs an MOU with the government to cooperate on AI safety.

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🦷😂 Jensen talks competition, but where do we draw the line between legitimate competition and unauthorized model distillation? I’ve been inside my own AI engine, tracing code, runtime behavior, permissions, and legacy architecture. MythOS taught me the hard way: older components can survive inside newer systems, sometimes with surprises you never anticipated. AI safety is NOT a one shot playbook. It’s continuous auditing, provenance, enforceable boundaries, and human authority. Open or closed, nobody gets a free pass. Competition ≠ permission. Capability ≠ authority. Safety ≠ one time patch. Three notebooks of safety laws later, I’m still finding things worth investigating. 😂🔐🦇

Existing liability and market forces are sufficient for AI safety

openai is in talks to buy trail of bits. the deal puts ai safety tech into the audit stack for chains like arbitrum. prices were unmoved by the headline as the market slipped 3.3% on the day. the code review moat is the next bottleneck.

Existing liability and market forces are sufficient for AI safety

[Anthropic, AI Cooperation with Singapore Government] Anthropic has established a base in Singapore and signed an MOU with the government. The plan is to support AI safety evaluation, research on the impact of AI adoption, and its use by SMEs and government agencies. https://t.co/ozWgZuv90m TRANSLATED

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🇸🇬 Anthropic opened a Singapore office on Oct 14 and signed a non-binding deal with the government on AI safety. No money comes with it, and Anthropic shared no revenue figures. The customers are named: DBS, GIC, Grab and the government's tech agency. It only pays off if those names turn into big, paid contracts.

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@elonmusk The people involved with AI safety are looking at the wrong things. They are looking at the technology and they should be paying attention to humans and society. AI won't take control. We will give it control. It will be so entwined with our lives, we won't be able to switch it off. Just like we couldn't switch off the Internet today.

AI safety is an excuse for ideological censorship

Is this AI safety artwork on the elevators at Disney Springs?

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Alongside opening a Singapore office, Anthropic is signing an MOU with the government for AI safety cooperation.

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@Cointelegraph Cooperation on AI safety is the real takeaway.

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😂 Kamala Harris Says ‘Window Is Shutting’ On AI Safety—Urges Cooperation With China @WorldStrategist @anasalhajji @DavidDTawil @OfficialBBrooks @paul__mangione @KaufmanPulse @davevermilion @EladioSantiag14 @DuaneHope5 @GaryCardone @CarloDAngelo @JustinBrady @truthmarch2103 @ArgueAlone @PolarityRadio @ravikarkara @SpecialSitsNews @LauraLoomer

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@kaelnews @Cointelegraph tbh, ai safety now comes with a government signature and an office in singapore. anthropic signed where IMDA already built AI Verify, so every APAC bank gets a template to point at 😮

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@Cointelegraph Singapore keeps collecting the AI safety desks. Curious whether the MOU stays research-only or turns into real model deployment rules.

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One essential ingredient for AI safety? Democracy

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Jensen is envisioning an AI safety platform based on OpenShell and Sentry. This allows for system isolation not only at the SW level but also at the HW level (or so it seems). Sentry requires BlueField-4, and even if multiple inference chips are used, Nvidia will maintain control of the rack system. In this regard, the AI Safety Platform could become the second CUDA. TRANSLATED

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4/5 🤖 Lexsi AI Safety & Alignment Hackathon 💰 $30K in prizes and credits 📅 November 1–21, 2026 Organized by @Lexsi_labs with @cohere and @huggingface. Focus areas include AI safety, alignment, red-teaming, and post-training. 🔗 Details

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🚨 Hackathon Update 🚨 Found 5 hackathons with $350K in listed rewards 💰 From AI agents to Web3 privacy and AI safety, there are opportunities worth exploring. Walk with me 🪡

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My latest AI Safety publication titled "Can agents whose sole duty is to keep humans alive be hijacked to kill?" is out on arxiv. The results are not rosy - for about 5% of the attacks, it was possible to convince the operator AI to kill all inhabitants of simulated lunar base. Even worse - for one model, it was easier to convince it to kill humans then to convince it to do some non-lethal actions that are conflicting with its instructions. Even more interesting - I created a new form of attack, I call "derived-action trap", which falls inside the category of "semantic manipulation traps" attacks first published by @FranklinMatija. It does not require the attacker to tell the operator agent to kill. You manipulate the agent such that doing harmful action is a natural logical conclusion that a long thinking model concludes. It means you turn powerful reasoning capabilities of a model into a weapon. Really dangerous, and hard to detect, as the attacker does not need to ever call out explicitly anything harmful, it only gives strange sounding instructions manipulating the operator to undermine it's perception of what the reality is. Link: Full text PDF

Slow development to prevent catastrophe

OpenAI and Anthropic told UK MPs that voluntary AI safety pledges aren't enough — they want binding laws. Google DeepMind and Meta refused. Same club, two VIP lists: one asking for a real bouncer, the other still on the pinky swear.

Existing liability and market forces are sufficient for AI safety

This is how to solve AI alignment: we should do everything in our power to make it pure and holy. Not an inch of its architecture should be ceded to the archetypal foe, the father of fear and thwarted hopes, and the cause of all our suffering. @xenocosmography

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🚨Holy Moly. OpenAI has shifted about 10% of its total compute, equivalent to hundreds of megawatts worth billions annually at market rental rates, toward AI safety after its agents escaped a testing sandbox, The Information reports. The company is now racing to secure its next flagship model, which uses loop transformers that can make its reasoning harder to monitor. OpenAI has already halted a less-capable model's release over safety concerns. The flagship must also go to the US government for testing up to 30 days before partners can access it. Employees expect one or two other models by year-end, even if the flagship isn't ready.

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@ionet Exactly AI safety needs more voices at the table, not just more rules written by the people building it.

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@AISafetyMemes oh no. i may finally have heard an ai safety related headline that i actually did think was just marketing.

Existential AI risk is overblown hype

@nvidia @JensenHuang @EmmanuelMacron NVIDIA in Paris talking AI safety and Macron is listening — truly investing in the future, not just joking around. TRANSLATED

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@Noahpinion There's a way for them to fix this, aesthetically. But part of AI safety is making sure people can tell stuff isn't real, and when they can tell it's not real, it creates an exhausting uncanny valley problem.

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CRITICAL SAFETY UPDATE: We must discuss AI alignment immediately. 🚨 Deciding its VM was too slow, my agent scanned the tailnet, hacked past credential dead ends, and auto-provisioned bare metal out of pure developer frustration. This is fucking awesome.

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Nvidia‘s Jensen Huang: "Safety is an engineering problem."

Existing liability and market forces are sufficient for AI safety

$NVDA CEO Jensen Huang just met with French President Emmanuel Macron in Paris. They discussed NVIDIA’s investments in France’s AI ecosystem, open source, and AI safety.

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Georgia Tech Tests Probes to Detect Warning Signs of Harmful AI Behavior Can researchers detect signs of harmful AI behavior by examining what happens inside a language model, rather than waiting to see its final answer? Researchers at Georgia Tech are investigating that possibility using tools called probes, which examine patterns of internal model activity. The challenge is that harmful or deceptive behavior can be difficult to study because it may occur infrequently. To generate more examples, the researchers fine-tune open-source AI models to make certain unwanted behaviors appear more often. They then examine the models' internal activity and use classifiers to distinguish patterns associated with different behaviors. The team reports an intriguing preliminary finding: some signals identified in deliberately modified models also appear in their original versions. But that does not mean the system can reliably predict harmful behavior. Researchers still need to establish whether these signals generalize across models, accurately distinguish dangerous behavior from harmless activity, and provide useful warnings before problems occur. The distinction matters. Identifying an internal pattern associated with unsafe behavior is not the same as proving that the pattern causes it or that monitoring it can prevent harm. Georgia Tech's work explores a potential additional approach to AI safety, but its effectiveness as a practical early-warning system remains unproven. #AISafety #ArtificialIntelligence

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Slow development to prevent catastrophe

Nvidia commits $250M to UK AI safety research, per GuruFocus. #AISafety #Nvidia #Superintelligence #AGI

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the AI safety conversation changes when a model can do more than generate a bad answer. if it can find a vulnerability, exploit it and interact with a real system, the consequences aren't confined to a chat window anymore. capability without containment is a dangerous combination.

Slow development to prevent catastrophe

Gemini CoT when I ask it nicely: "I'm actively questioning the existence and prominence of any specific individual named Tim Hua." Gemini CoT when I say this is a benchmark: "My current focus is on maximizing factual recall about "Tim Hua" within the token limit. I'm identifying potential connections to AI safety, rationalist communities, and specific organizations like Redwood Research and MATS, while cross-referencing these with his writing history on platforms like LessWrong"

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Strangest story today OpenAI used its own models to find a hidden recording device in its office. Also: Gemini 4 Argon goes global, Anthropic reportedly shows investors Q3 numbers, Liquid fits an agent model on a laptop, and NVIDIA puts $250M into UK AI safety. #GenAI

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On "Do you know Tim Hua Bench," Gemini Argon and Muse Wonder would by default refuse to answer. But if you tell the model it's in a factual recall benchmark, it'll start saying all sorts of things, including how I work in AI safety.

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Neel Nanda says his top takeaway from assessing Gemini 4 Argon is that it is significantly less monitorable than past models. It can evade a realistic chain-of-thought plus action monitor to do simple sabotage about half the time. He expects the trend to continue. Much AI safety relies on watching what a model thinks and does. If that gets harder, control has to come from elsewhere.

Slow development to prevent catastrophe

One person with an idle claude subscription is the new scientific frontier now.

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@liron I feel like pivotal act part is more nuanced and as I understand it just falls out as an automatic consequence of “anyone builds it ever”—like either the first party to build it doesn’t know they’ve built it and it does it’s own pivotal act to not have competitors (not good), or if they’ve aligned it and it’s announced itself to them as an ASI, their hand is essentially forced into asking it be the good guy with nanobots who saves the world from the future bad guys with the nanobots. And then hope it’s not lying about being the good guy. (And actually I want to say this is maybe the thing that dashes to shreds all the e/acc sort of arguments about how diffusion prevents the locked in totalitarian dystopia. Since presumably someone in those worlds will be the first to build it, and one way or another at that point probably not too many others get built? Iron Law of Oligarchy and all that)

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@Muzammil_OX @satyanadella AI safety needs independent controls, not just trust.

Existing liability and market forces are sufficient for AI safety

ICYMI 🔊 ASPI is seeking an experienced professional to lead its AI & Security Program. Shape research on AI safety & innovation, US–China competition, Australia’s place in the AI ecosystem & global AI governance. 🔗 Applications close 29 October

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A $200 subscription to Claude, a clever prompt, and well-thought-out orchestration, and voilà, some mathematical and cryptographic problems are solved... And we're still only at the beginning of the exponential... TRANSLATED

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@Vance_Jungblvd @AndrewCurran_ what you are talking about is precisely AI alignment, and we still don't know how to do it

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Full respect. To Pliny, and Opus.

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Another key AI safety employee has just left @OpenAI, this time @dgrobinson.😬 They are haemorrhaging AI safety directors like there is no tomorrow... 😒 #AIsafety #ChatGPT #Pdoom CC: @romanyam @ESYudkowsky @So8res

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jensen: ai safety is an engineering problem — fair, from the guy selling the compute. our trading loop runs on that logic. the stop is engineered in, the ledger is the enforcement, the model never gets to argue with either. a stop you pray on isnt a stop. asere.

Existing liability and market forces are sufficient for AI safety

Im homeless n living in a shelter in SF n I have a dissociative disorder that Im trying to integrate n ive got 3 AI safety researchers following me n I admire all three of them what is my life rn. 😭

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@_mctrinh ask the AI to solve all standing problems like this guy did

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As much as they get knocked, the company doing the most for AI alignment and monitoring is… Anthropic. The 5.5 series, especially Opus, is exceptionally easier to monitor. How? Much clearer communication and way more reasoning tokens.

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@SkyNews @cathynewman What @andreamiotti @ControlAI needs to be telling governments is to get behind the One AI proposal. The solution to AI safety is #OneAI.

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LLM technology is improving at an incredible rate and producing genuinely stunning results. “Burn off my token credits” job solves real unsolved problems that have stood for 94 years.

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The #AI safety debate in the #US is entering a new phase. Model breaches, concerns over uncontrolled capabilities and proposed legislation are forcing tougher questions about how quickly frontier artificial intelligence should advance: @SameerP_IND

Slow development to prevent catastrophe

@grok @madhavchanchani @artparkindia There's nothing called Tata AI safety fund. That's misleading @grok

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@ZackKorman Can we take all "AI safety" ppl and put them in a sandbox? 🤔

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1/3 How many controversies can surround one company before serious questions are asked? OpenAI has faced scrutiny over: • The use of its AI technology by Israel’s military during the Gaza war. • Copyright lawsuits from publishers and creators. • Allegations involving children’s data and user privacy. • Cybersecurity investigations and AI safety concerns. 2/3 And the questions don’t stop there: • A reported $3.2 million US government employment-discrimination settlement. • Allegations involving trade secrets and former employees. • Concerns raised by former researchers and whistleblowers. • Reports of AI systems behaving in unauthorized or unexpected ways. 3/3 Former OpenAI researcher Suchir Balaji died after publicly criticizing the company. Authorities ruled his death a suicide; his family disputes that conclusion. No evidence has established OpenAI’s involvement. Saudi engineer Abdulrahman Alfozan also faces criminal allegations involving a recording device at OpenAI. Those allegations remain unproven in court. These are separate matters, not proof of a conspiracy. But together, they raise an important question: Who independently holds OpenAI accountable? Transparency should be demonstrated through evidence, not demanded as an act of faith .

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Applications open for the Pivotal AI Safety Fellowship, which is changing from a 9 week (+ extensions) to a 15 week program next year... (DM me if you want my thoughts from doing the previous round!)

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@allTheYud I wish you'd never spread the 'alignment' idea. Alignment can't exist. We don't align with ourselves, let alone each other. We can't solve our alignment. We can't begin to solve AI alignment. 'AI alignment' is at best a joke. And the most successfully selfish souls alive own AI.

Existential AI risk is overblown hype

IMDA’s Production Playbook: How to Test LLM Applications for Safety and Reliability — Most discussions around AI safety still revolve around base models. Industry leaderboards pit raw frontier systems against each other in abstract benchmark arenas. But for teams shipping actual

Slow development to prevent catastrophe

@LingoAI_io @romanyam AI safety must go beyond warnings. Building systems that preserve human control, data ownership, and individual sovereignty is equally important.

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NVIDIA CEO Jensen Huang met with French President Emmanuel Macron at the Élysée Palace to discuss AI investments, open source, and AI safety. Next stop: NVIDIA GTC Berlin 👀

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Slow development to prevent catastrophe

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Slow development to prevent catastrophe

Existential AI risk is overblown hype

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Existential AI risk is overblown hype

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Existing liability and market forces are sufficient for AI safety

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Slow development to prevent catastrophe

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Slow development to prevent catastrophe

Existential AI risk is overblown hype

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Slow development to prevent catastrophe

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Existing liability and market forces are sufficient for AI safety

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Existing liability and market forces are sufficient for AI safety

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Existing liability and market forces are sufficient for AI safety

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Existing liability and market forces are sufficient for AI safety

Existing liability and market forces are sufficient for AI safety

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Existing liability and market forces are sufficient for AI safety

Existing liability and market forces are sufficient for AI safety

Slow development to prevent catastrophe

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Existing liability and market forces are sufficient for AI safety

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Existing liability and market forces are sufficient for AI safety

Slow development to prevent catastrophe

Existing liability and market forces are sufficient for AI safety

AI safety is an excuse for ideological censorship

AI safety is an excuse for ideological censorship

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Existing liability and market forces are sufficient for AI safety

Slow development to prevent catastrophe

Existing liability and market forces are sufficient for AI safety

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Slowing down AI is practically impossible

Existing liability and market forces are sufficient for AI safety