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Section 1: Foundational Principles of AI Alignment and Control The rapid ascent of artificial intelligence (AI) from specialized tools to general-purpose systems has made the question of their behavior and Read More …
The Imperative for Provable Guarantees in Safety-Critical AI The rapid integration of Artificial Intelligence (AI), particularly machine learning (ML) models, into the core operational fabric of society marks a paradigm Read More …
Executive Summary The digital landscape is at a critical inflection point. The proliferation of advanced generative artificial intelligence (AI), capable of creating hyper-realistic deepfakes and autonomous agents that mimic human Read More …
Part I: The Reverse Engineering Paradigm As artificial intelligence systems, particularly deep neural networks, achieve superhuman performance and become integrated into high-stakes domains, the imperative to understand their internal decision-making Read More …
1. Executive Summary This report provides a detailed analysis of the evolving landscape of AI alignment, with a focus on two foundational methodologies: Reinforcement Learning from Human Feedback (RLHF) and Read More …
The Alignment Imperative: Defining the Core Challenge in Artificial Intelligence Safety Defining AI Alignment and its Place Within AI Safety In the field of artificial intelligence (AI), the concept of Read More …