According to Anthropic (@AnthropicAI), improving Chain of Thought (CoT) monitoring is essential for identifying safety issues in AI systems. The strategy requires making CoT more faithful and obtaining evidence of higher faithfulness in realistic scenarios. This could potentially lead to better trading decisions by enhancing AI troubleshooting, ensuring systems operate as intended. The paper suggests that other measures are also necessary to prevent misbehavior when CoT is unfaithful, which could impact AI-driven trading models. [Source: AnthropicAI Twitter]

According to Demis Hassabis, the Gemini 2.0 series models are now leading in cost efficiency and performance, providing powerful reasoning and multimodal capabilities essential for agentic applications in trading. These advancements can improve algorithmic trading models by reducing operational costs while enhancing decision-making accuracy. Source: @demishassabis.