豆包大模型1.8正式发布,拥有更强多模态Agent能力,豆包日均使用量超过50万亿,推出成本节省计划降幅达47%
硬AI·2025-12-18 14:05

Core Insights - The article highlights the launch of Doubao Model 1.8 by Volcano Engine, which features enhanced multimodal agent capabilities and a 256K ultra-long context for handling complex tasks [2][3][5] - Volcano Engine's "AI Savings Plan" aims to optimize user costs, offering savings of up to 47% on AI usage [3][17] - The company emphasizes the importance of expanding the AI market rather than competing for existing market share, predicting a potential market growth of tenfold in the coming year [4] Model Capabilities Upgrade - Doubao Model 1.8 shows significant improvements in multimodal understanding, particularly in long video comprehension and security monitoring scenarios [5] - The model's context management allows companies to tackle complex tasks and support decision-making processes [5] - New image generation model Doubao-Seedream-4.5 offers capabilities such as multi-image combinations, creative photography, and virtual try-ons [5] Video Generation Enhancements - The Seedance series includes two versions: Seedance-1.0-Lite focuses on cost and speed, while Seedance-1.0-Pro delivers cinematic quality and native sound effects [7] Application Scenarios - Doubao Model has been integrated into smart hardware and voice assistants, covering daily communication, professional services, and online searches [9] Ecosystem Development - Volcano Engine introduced "Volcano Ark" inference outsourcing service, supporting major open-source models for seamless deployment [11] - The Viking series products enhance user input quality and facilitate the rapid construction of knowledge and memory bases for models and agents [13] - The company launched an enterprise-level AI Agent platform, AgentKit, which has been adopted by leading clients [15] Cost Optimization Plan - The "AI Savings Plan" allows users to join once and benefit from cost reductions across various models, with flexible payment options [17] - The initiative is expected to enhance performance and reduce costs, particularly for video generation models, and is seen as a potential investment opportunity in the AI application landscape [17]