Chinese AI startup DeepSeek has announced two new AI models, DeepSeek-V3.2 and DeepSeek-V3.2-Speciale, which introduce a novel architectural innovation called DeepSeek Sparse Attention (DSA). DSA significantly reduces computational costs when processing long documents and complex tasks by identifying relevant context portions, leading to a 70% reduction in inference costs compared to previous models.
DeepSeek’s technical report highlights that the new models support context windows of 128,000 tokens, enabling efficient analysis of extensive documents, codebases, and research papers. Notably, DeepSeek-V3.2-Speciale has excelled in international competitions, showcasing its capabilities in mathematics, coding, and reasoning tasks.
Additionally, DeepSeek’s models incorporate ‘thinking in tool-use,’ allowing seamless problem-solving while utilizing external tools without losing reasoning context. By training on synthetic tasks and leveraging real-world tools, DeepSeek has expanded the boundaries of AI capabilities.
Departing from industry norms, DeepSeek has adopted an open-source approach, offering its cutting-edge models under the MIT license. This strategic move challenges the proprietary model ownership model, potentially disrupting the AI business landscape with free access to high-performance AI systems.
Despite facing regulatory challenges in Europe and America regarding data privacy and export controls, DeepSeek’s innovation and open-source strategy signal a new era in AI development and deployment.
Source: VentureBeat