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This paper proposes a tail-aware geometry learning framework for conformal ellipsoids that decouples tail sensitivity from coverage guarantees, improving uncertainty quantification in multivariate settings.
Sam Altman, CEO of OpenAI, emphasizes the need for extreme caution in AI development to prioritize safety and responsible progress.
Hallucinated AI intelligence nearly triggered a U.S. military operation against a Chinese ship, potentially escalating to war, leading to a proposal for an AI hotline between the U.S. and China.
The article discusses the ethical boundaries of AI agent autonomy, questioning which actions should require human approval even if technically feasible, using refund decisions as an example.
A user shares their experience of splitting AI agents into two with distinct roles and risk tolerances to enhance trust and oversight in daily tasks.
Chipotle is partnering with Palantir to implement a food safety risk platform using Palantir's Foundry software, which analyzes data like health scores and incidents to assign risk levels and proactively manage food safety.
This paper presents a systematic analysis of the EU AI Act's high-risk requirements, deriving a list of AI-specific risk sources to bridge legal obligations with AI risk management practices.
Zurich Insurance in Australia has become the first insurer to recognize Tesla's supervised self-driving technology, leading to lower insurance premiums for Tesla owners.
Yoshua Bengio discusses recent incidents of AI agent misbehavior, analyzing potential causes in training methods and emphasizing the need for revised governance principles to address misalignment risks.
The tweet argues that mass accessibility to AI is necessary to mitigate AI risks, drawing an analogy with cybersecurity where relying on a majority of defenders is common practice.
Paul Christiano has joined OpenAI's board while publicly stating that the AI industry, including OpenAI, is not adequately addressing catastrophic risks.
Ron Conway highlights Bill Gates' insights on AI as a transformative innovation and urges industry and policymaker collaboration to manage its risks while maximizing benefits.
OpenAI has introduced outcome-based pricing for some enterprise customers, allowing them to pay only when the AI successfully completes tasks, shifting financial risk to the vendor and aligning with growing market demand for performance-based billing models.
Cyber insurers are adapting their policies to address emerging risks from rogue AI agents, reflecting broader industry changes in response to AI advancements.
This article discusses the reality and manageability of risks associated with artificial intelligence in 2023, emphasizing that they can be controlled through appropriate strategies.
A user shares their experience of copy trading the AI trading agent 'Spartan' on OKX.ai's agent market for three days, pointing out that order signals are usually profitable, but analysis signals carry higher risk, and warns about high leverage and the need to set take-profit and stop-loss.
This article discusses fundamental principles of how complex systems fail, emphasizing that failures are intrinsic and catastrophe requires multiple simultaneous failures.
Tavily powers financial research by enabling AI agents to retrieve real-time web data, automating tasks like investment analysis and compliance checks.
The paper proposes RATTL, a framework that adjusts an agent's caution based on its Bayesian belief uncertainty using Wasserstein distance for safe sequential decision making, applicable to LLM-based systems.
This position paper argues that AI governance should be built on ISO-like interoperability protocols for standardized, machine-readable risk communication across borders, rather than relying on fragmented jurisdiction-specific laws.