Part 2: Google, Apple, and Microsoft in Crisis; The Birth of SearchGPT; What Is OpenAI Aiming For? — Link - There's an evolution away from exclusive cloud-centric systems toward additional embedding algorithms within edge device, which enhances personal data protection, security, and resource efficiency. Federated learning allows AI models to be trained on individual devices, sharing only updated parameters. Tesla's 'Dojo' is a prime example, where vehicles collect real-time data to continuously update AI models. - Companies like Google, Microsoft, Apple, and Amazon are adjusting their strategies in line with this shift to distributed models. Despite possessing massive data, they face privacy constraints; federated learning offers a solution to enhance AI competitiveness while addressing privacy concerns. - AI supplements real data by generating synthetic data, filling learning gaps especially in areas where data collection is difficult. The competition for AI dominance hinges on effectively handling federated learning and synthetic data. Companies leading in these fields, such as OpenAI with its recent "SearchGPT" release, are poised to shape the future AI ecosystem. - Ultimately, future dominance in AI is likely to be determined by data access methods and learning efficiency.