哈萨比斯：DeepMind才是Scaling Law发现者，现在也没看到瓶颈

Core Insights - The article emphasizes the importance of Scaling Laws in achieving Artificial General Intelligence (AGI) and highlights Google's success with its Gemini 3 model as a validation of this approach [5][19][21]. Group 1: Scaling Laws and AGI - Scaling Laws were initially discovered by DeepMind, not OpenAI, and have been pivotal in guiding research directions in AI [12][14][18]. - Google DeepMind believes that Scaling Laws are essential for the development of AGI, suggesting that significant data and computational resources are necessary for achieving human-like intelligence [23][24]. - The potential for Scaling Laws to remain relevant for the next 500 years is debated, with some experts expressing skepticism about its long-term viability [10][11]. Group 2: Future AI Developments - In the next 12 months, AI is expected to advance significantly, particularly in areas such as complete multimodal integration, which allows seamless processing of various data types [27][28][30]. - Breakthroughs in visual intelligence are anticipated, exemplified by Google's Nano Banana Pro, which demonstrates advanced visual understanding [31][32]. - The proliferation of world models is a key focus, with notable projects like Genie 3 enabling interactive video generation [35][36]. - Improvements in the reliability of agent systems are expected, with agents becoming more capable of completing assigned tasks [38][39]. Group 3: Gemini 3 and Its Capabilities - Gemini 3 aims to be a universal assistant, showcasing personalized depth in responses and the ability to generate commercial-grade games quickly [41][44][45]. - The architecture of Gemini 3 allows it to understand high-level instructions and produce detailed outputs, indicating a significant leap in intelligence and practicality [46]. - The frequency of Gemini's use is projected to become as common as smartphone usage, integrating seamlessly into daily life [47].