Google DeepMind CEO Predicts AGI in 5–8 Years

Google DeepMind CEO Demis Hassabis stated at the AI Summit that Artificial Intelligence (AI) has the potential to revolutionize science and medicine.

He emphadata-sized that global collaboration and communication are crucial to address AI’s societal implications effectively.

Hassabis predicted that Artificial General Intelligence (AGI) could become a reality within the next five to eight years, marking a major turning point in technology.

AI Transforming Science and Medicine

AI tools and products are rapidly being developed, offering new possibilities in drug discovery, medicine, materials science, and climate technology.

Systems like AlphaFold demonstrate how AI can accelerate research and problem-solving at a global scale.

Hassabis highlighted that the benefits of AI can only be maximized through global cooperation and sharing knowledge across data-borders.

Societal Challenges and Global Cooperation

Despite technical advances, AI presents complex societal challenges that cannot be solved by technology alone.

Hassabis stressed the importance of international conferences—from the UK to Paris, Seoul, and India—to bring together technical experts and policymakers to discuss AI’s risks and benefits.

Cautious optimism is warranted: technical problems can be solved over time, but societal impacts require structured governance and collaboration.

AI vs. AGI

Current AI excels at specific tasks, such as translation, image recognition, and chatbots.

AGI, however, would possess human-like understanding, capable of learning, reasoning, problem-solving, and performing tasks across multiple domains.

In the future, AGI could take on roles such as doctors, teachers, or engineers, performing diverse tasks with general intelligence.

Limitations of Current AI

Hassabis highlighted that existing AI is limited: systems become static after training and cannot adapt to new experiences in real-time.

AI struggles with long-term planning, consistent strategies, and generalization beyond specific problems.

Current systems may solve Olympiad-level challenges but fail at simpler or slightly altered problems.

The next goal is to create AI that continuously learns, plans long-term, and maintains consistency, moving closer to true intelligence rather than task-specific performance.

Hassabis concluded that the possibilities for AI are limitless, but realizing AGI responsibly requires both technological innovation and careful societal planning.

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