火山引擎总裁谭待：谈论Agent与APP冲突还太早

Core Insights - ByteDance's cloud platform Volcano Engine has released the Doubao model 1.8 and the Seedance 1.5 pro audio-video creation model, with Doubao's daily token usage exceeding 50 trillion, up from 30 trillion in September [2] - The industry views the targeted restrictions on internet apps as a conflict between the "Agent era and the APP era," but the president of Volcano Engine, Tan Dai, believes that the core value for users lies in achieving goals more conveniently and at lower costs, regardless of the medium used [2] - Tan Dai emphasizes that AI's primary role should be to optimize the efficiency of unmet needs, suggesting a coexistence of Web, APP, and Agent rather than a replacement [2] Industry Readiness - The exploration of AI and Agents is still in a trial phase, with market demand present but models not yet fully developed, a situation expected to last for about three more years [3] - The core issue regarding the industry's readiness for Agent integration lies in the improvement of Agent tools, with Volcano Engine investing significant resources to make existing functions recognizable and callable by Agents [3] - Tan Dai notes that both Doubao AI assistants and APPs consist of complex Agent collections, facing challenges in foundational capabilities and real-world application requirements [3] Multi-Modal Models - By the end of 2025, leading domestic and international model manufacturers are intensifying efforts, with multi-modal models like Seedance 1.5 pro marking a shift towards deeper AI applications [4] - Multi-modal capabilities allow models to "see, hear, speak, and act," moving beyond text-based interactions to practical applications such as traffic recognition and quality inspection [4] - Tan Dai believes that while multi-modal models face data challenges, significant progress has been made compared to last year, and the pace of model advancement is rapid [4] Cloud Services in AI Era - Volcano Engine continues to highlight the value of cloud services in the AI era, with AWS aiming for its generative AI platform Bedrock to become the "largest reasoning engine globally," comparable to its core computing service EC2, which is currently valued at around $40 billion [4] - Tan Dai acknowledges this trend and compares the development of MaaS (Model as a Service) to the chip business, indicating a shift from GPU training to inference processes [4] Future of AI Hardware - Tan Dai cites the early 2025 AI wave as evidence of the importance of cloud business, noting that many users faced issues with fixed-capacity AI hardware due to rapid technological iterations [5] - The inability to privatize deploy technologies like Agents and the fixed capabilities of one-machine solutions hinder the successful implementation of diverse AI applications [5] - Consequently, the private one-machine model from the software era is expected to be phased out in the AI era [5]