DeepSeek

Opinion: DeepSeek's low-cost AI development approach may become an important catalyst for blockchain development

ChainCatcher news, according to IBTimes, the founder of game studio Dizzaract, Ilman Shazhaev, stated in an interview that DeepSeek's low-cost AI development approach is "encouraging" and could become an important catalyst for blockchain development. He pointed out, "If high-performance AI models can be obtained at low cost, more decentralized systems will be able to utilize them at various levels."Shazhaev believes that DeepSeek's open weight design and two-stage reinforcement learning training method signify a true shift in AI development philosophy. He predicts that this model will have a significant impact on blockchain gaming, particularly in promoting smarter in-game economies.Although OpenAI CEO Sam Altman has accused DeepSeek of secretly using data from American AI giants to train its AI assistant, Shazhaev believes that a shift is occurring, especially among developers in the field of cryptocurrency and AI integration. He stated that budget constraints have always been a barrier in blockchain development, making models like the DeepSeek chatbot an attractive option.The AI model launched by DeepSeek in January of this year caused a stir in the tech industry, leading to a decline in related tech stocks and AI token prices. U.S. President Trump subsequently issued a statement calling for American tech companies to "wake up" and learn from this AI technology that does not require billions of dollars in development costs.

Sun Yuchen: Huobi HTX will lay out the cryptocurrency market in the CIS region

ChainCatcher news, the "2025 HTX DAO Victoria Harbour Night - Confidence Journey Hong Kong Station" hosted by HTX DAO was grandly held. Sun Yuchen, Global Advisor of Huobi HTX and Founder of TRON, revealed on-site that Huobi HTX has made significant progress over the past three years relying on the community, especially excelling in trading volume and new asset listings. Additionally, Huobi HTX is experiencing a surge in traffic in the CIS region in 2024 and will strongly focus on laying out the crypto market in the CIS region, emphasizing the resolution of user needs in that area to solidify its market position.Moreover, during the "Hong Kong TRON & HTX DAO Exchange Meeting," Sun Yuchen discussed the decentralized stablecoin USDD, stating that various methods have been tried to enhance user returns and improve user experience. USDD focuses on long-term development, with the key being to find the right team and leaders, possessing solid underlying technology and a sound community governance mechanism. During the construction process, it is essential to ensure substantial progress and prevent sudden project collapses due to issues like asset security, as only in this way can sustainable and healthy growth be achieved.Sun Yuchen also revealed that the application potential of AI in the crypto field is enormous, especially in building expert models. Currently, there is an exploration of an AI application based on DeepSeek with a certain level of anonymity, tailored to the characteristics of the crypto field.

Opinion: Decentralized AI is changing due to Deepseek, and AI models developed based on a complete Web3 AI stack are expected to emerge one after another

ChainCatcher news, the Pando Fund released a research report titled "Decentralized AI Changed by Deepseek," which points out that the narrative of decentralized AI is continuously reshaping. Web3 AI companies can focus on replicating DeepSeek's success while offering new advantages such as multimodality, user ownership, censorship resistance, and privacy. It is expected that the number of projects on the supply side will continue to grow, while consumer-facing projects will begin to compete with Web2 counterparts by building community-participated networks. In the coming year, AI models developed based on a complete Web3 AI stack will emerge one after another.In addition, companies combining AI and crypto are gradually adjusting their strategies to focus on infrastructure building rather than model development. For example, companies in the GPU market like Akash, Render, IoNet, and Exabits have developed sustainable revenue models. Meanwhile, businesses like Grass and Gradient, which allow users to share network bandwidth, have found their market positioning by providing distributed network services to Web2 clients. In inference tasks, the performance gap between small models and large models is narrowing, which means that Web3 does not need to rely on the massive computing power of traditional AI giants and can utilize these streamlined models for efficient inference operations. As this trend develops, we may see more inference endpoints driven by decentralized computing networks in the future.
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