DeepMind's Blueprint for Safe AGI Development: Navigating the Risks of 2030

As AI hype reaches fever pitch, the focus shifts to Artificial General Intelligence (AGI). DeepMind's new 108-page paper tackles the crucial question of safe AGI development, projecting a potential arrival by 2030. The paper outlines four key risk categories: misuse, misalignment, mistakes, and structural risks. To mitigate these, DeepMind proposes rigorous testing, robust post-training safety protocols, and even the possibility of 'unlearning' dangerous capabilities—a significant challenge. This proactive approach aims to prevent the severe harm a human-level AI could potentially inflict.