How AI Really Works: Algorithms, Big Data, Neural Networks & Ethics Explained скачать в хорошем качестве

How AI Really Works: Algorithms, Big Data, Neural Networks & Ethics Explained

This presentation explores the evolution of artificial intelligence, focusing on the three pillars that power modern AI: algorithms, data, and computational power, as well as the ethical questions surrounding its future. The video explains how AI has evolved from early symbolic rule-based systems (expert systems) to modern machine learning, deep learning, and transformer models used in today’s large language models and generative AI systems. Topics covered include: • Early symbolic AI and expert systems based on explicit rules • The limitations of rule-based AI and lack of adaptability • The shift toward machine learning and data-driven models • Types of learning algorithms: supervised, unsupervised, and reinforcement learning • Neural networks and deep learning inspired by the human brain • The role of transformers and self-attention in modern AI systems • The explosion of big data and global connectivity • The importance of computing power, GPUs, and cloud infrastructure • The relationship between algorithms, data, and compute in AI performance • Challenges such as energy consumption, supply chains, and hardware limits The presentation also discusses key ethical challenges of artificial intelligence, including: • AI bias and transparency • Surveillance concerns • Economic concentration of AI power • Job displacement and automation • Military uses of AI • Governance and control of advanced AI systems This video provides a comprehensive overview of how modern AI systems work and the societal questions they raise.