Core Insights - The article discusses a significant paradigm shift in AI, indicating that the development of AI is not slowing down but rather transitioning to a new phase of growth [1][7][12]. Group 1: AI Development Trends - There are two contrasting views on AI development: one claims that AI growth is slowing down, while the other highlights continuous advancements with new models like GPT-5.1 and Gemini 3 being released [3][12]. - Łukasz Kaiser argues that the perception of slowing growth is incorrect, stating that AI's capability growth follows a smooth exponential curve, akin to Moore's Law [15][16]. - The shift from pre-training to reasoning models is a key factor in this transition, with pre-training being in a later stage of its S-curve while reasoning models are still in their early stages [18][19]. Group 2: Reasoning Models and Their Impact - The industry is focusing on smaller, cost-effective models that maintain quality, leading to the misconception that pre-training has stalled [21]. - Reasoning models, which allow for more complex thought processes and the use of tools during inference, are expected to progress rapidly due to their emerging nature [22][27]. - The evolution of models like ChatGPT demonstrates a qualitative leap in performance, with newer versions incorporating reasoning and external tool usage for more accurate responses [23][24]. Group 3: GPT-5.1 Insights - GPT-5.1 is not merely a minor update but represents a significant stability iteration, enhancing reasoning capabilities through reinforcement learning and synthetic data [34][35]. - The naming convention for versions has shifted to focus on user experience rather than technical details, allowing for greater flexibility in development [38]. - Despite improvements, GPT-5.1 still has limitations, particularly in multi-modal reasoning, as illustrated by its struggles with basic tasks that require contextual understanding [41][42]. Group 4: Future of AI and Robotics - AI is expected to change the nature of work without eliminating jobs, as human expertise will still be needed in high-stakes scenarios [62][66]. - Home robots are anticipated to be the next visible AI revolution, driven by advancements in multi-modal capabilities and general reinforcement learning [67][69]. - The integration of these technologies is expected to lead to a significant leap in the capabilities of home robots, making them more intuitive and perceptible compared to current AI models like ChatGPT [69].