Demis Hassabis, CEO and co-founder of Google DeepMind, forecasts the emergence of Artificial General Intelligence (AGI) by 2030, contingent on overcoming current research challenges. Hassabis emphasizes the necessity of active problem-solving systems and suggests that one or two major breakthroughs are still required to achieve AGI. He highlights the brain's ability to integrate new knowledge, such as through REM sleep, as a model for AI learning processes. Hassabis also points out inefficiencies in current AI systems, which rely on brute force methods for information processing. He advocates for more efficient memory systems and highlights model distillation as a method to create smaller, cost-effective AI models without sacrificing performance. Innovations from AlphaGo and AlphaZero are expected to drive future AI advancements, with engineers experiencing productivity increases of up to 1000 times due to recent AI developments. Despite these advancements, Hassabis notes that the lack of continual learning remains a significant barrier to full task automation in AI. Addressing this limitation is crucial for advancing AI capabilities and realizing the full potential of AI technologies in real-world applications.