Topic: LLM

We delve into the first completed three-year cycle of the AI wave, marked by the significant IPO milestones of Zhipu and MiniMax. By reflecting on early investment decisions with Zhang Jinjian, we examine the evolution of cognitive frameworks, shifting from pure belief to a nuanced understanding of large models and embodied AI as converging paths to AGI. We highlight the critical 'long action, short thinking' asset strategy and the rising importance of 'subjectivity' for founders in an increasingly noisy market. For the tech community, this discussion provides vital context on the three stages of embodied AI development and an optimistic outlook for the Chinese market in 2026. Today we focus on how individual agency and 'vitality' remain the core drivers of innovation as we transition into the next era of technological advancement.

Today we explore the transformative shift in algorithm development, moving from traditional manual tuning to autonomous evolution driven by Large Language Models. We delve into Google's AlphaEvolve, the evolutionary coding agent launched in May that recently assisted mathematician Terence Tao in solving the world-class Erdos#1026 problem. The discussion highlights how LLMs' reasoning capabilities allow algorithms to "reproduce" and optimize themselves, shifting industry focus from one-off optimizations to continuous, self-improving agent ecosystems. We also examine China's progress in this field, specifically Baidu's "Famou" platform, which targets industrial applications in energy, finance, and manufacturing. For developers and enterprises, this marks a significant transition from SaaS to "Result as a Service" (RaaS), where the human role shifts toward defining and evaluating AI rather than performing repetitive coding tasks.