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The article argues that increasing AI agent capability does not inherently improve reliability, emphasizing the need for robust control systems, audits, and human oversight similar to accounting standards to prevent convincing failures.
This paper introduces TradingAgents, a multi-agent LLM framework that simulates real-world trading firms to improve stock trading performance. It utilizes specialized agents for analysis and risk management, demonstrating superior results in cumulative returns and Sharpe ratio compared to baselines.
OpenAI proposes a regulatory framework for 'frontier AI' models that pose potential public safety risks, advocating for standard-setting processes, registration/reporting requirements, and compliance mechanisms including pre-deployment risk assessments and post-deployment monitoring.
OpenAI unveils Trove, a no-code agent that automates vendor due-diligence by screening for sanctions, financial and reputational risk and producing analyst-ready reports in minutes.