Core Insights - Sequoia Capital defines the current AI wave as a profound "cognitive revolution," with transformative power comparable to or exceeding the Industrial Revolution, presenting a massive $10 trillion business opportunity [1][5][19] - The next battleground for AI is the vast service industry market, which will undergo disruptive transformation and expansion, similar to how SaaS reshaped the software market [1][5][19] - Sequoia is actively seeking and investing in startups that can "specialize" general AI technologies to address specific industry pain points, akin to historical figures like Rockefeller and Carnegie [1][4][5] Investment Trends - The company has identified five key investment trends currently unfolding in the AI landscape: 1. Work models are shifting from "low leverage, high certainty" to "high leverage, high uncertainty," allowing sales personnel to manage hundreds of clients through AI agents, achieving over 1000% leverage [10][21] 2. The standard for measuring AI capabilities has shifted from academic benchmarks to real-world performance, exemplified by companies like Expo proving their technology in competitive environments [13][22] 3. Reinforcement learning is transitioning from theory to practical application, becoming a competitive advantage for many startups [13][23] 4. AI is penetrating the physical world beyond robotics, optimizing processes and accelerating hardware manufacturing [13][24] 5. Computing power is becoming a new productivity metric, with expectations that the consumption of computing power per knowledge worker will increase by 10 to 1000 times [13][24] Investment Themes - Over the next 12 to 18 months, Sequoia will focus on five investment themes to address core bottlenecks in AI development: 1. Persistent memory, enabling AI to retain long-term context and maintain unique identities for complex productivity tasks [15][25] 2. Seamless communication protocols between AIs, which could lead to disruptive applications, such as fully automated shopping processes [15][26] 3. The explosion of AI voice applications, which are already viable for consumer and enterprise use [15][27] 4. Comprehensive AI security, covering the entire chain from development to end-users, ensuring safety against vulnerabilities [15][28] 5. The critical moment for open-source AI, emphasizing the importance of competition with proprietary models to maintain an open and free AI ecosystem [15][29]