Google's DeepMind released the structure of 200 million proteins, solving the protein-folding problem, a significant achievement in AI.
Proteins' 3D structures determine their functions, and determining them computationally is laborious due to numerous configurations.
DeepMind's AlphaFold accurately predicted structures of 100 proteins, surpassing other solutions and revolutionizing drug discovery.
DeepMind made the research outcomes easily accessible, aiding initiatives like Drugs for Neglected Diseases and enabling faster drug discovery.
AI synthesizers and robotic synthesizers can revolutionize research and discovery processes in chemistry and other fields.
AI, like the UNEP's World Environment Situation Room (WESR), can collect and analyze real-time sensor data for predicting environmental conditions.
AI may raise concerns about authorship, knowledge ownership, biases, and challenges for publishers due to AI-generated content.
AI can aid in democratizing knowledge but requires infrastructure and resources for advanced science and medicine.
The AI-Chasm: The gap between those with access to advanced AI infrastructure and resources and those without may lead to wealth concentration and inequality.
Transformation of Workplaces: AI's capabilities in music, poetry, and manuscripts can create polymath 'beings' and transform workplaces and institutions.
Need for Governance: Governments must assess AI's impact, establish advisory groups, and formulate AI and data-governance policies to guide responsible AI development.
Interdisciplinary Approach: Responsible AI development requires interdisciplinary efforts in institutions and industry.
Early Movers' Advantage: Early adopters of AI governance will have a greater advantage in harnessing the benefits of AI.
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