【华西计算机|每日资讯（0223)】|1.69亿融资押注专用芯片：Taalas要靠"去GPU化"改写AI算力格局 【国内新闻】 #蚂蚁集团AI业务春节加速：支付宝"AI付"、蚂蚁阿福APP用户数双破亿 蚂蚁集团 CEO 韩歆毅提出以"有钱花""有命花"为核心的"两朵花"AI战略，旨在用AI守护用户财富与健康。 2026年春节的实战表现，印证了这一战略的加速落地：一侧深耕AI健康，切入数十万亿规模的大健康市场，强化 专业服务供给；另一侧打造AI支付，为Agent经济铺设"支付高速公路"，催生全新的商业生态。 （来源：TechWeb） 【华西计算机|每日资讯（0223)】|1.69亿融资押注专用芯片：Taalas要靠"去GPU化"改写AI算力格局 【国内新闻】 #蚂蚁集团AI业务春节加速：支付宝"AI付"、蚂蚁阿福APP用户数双破亿 蚂蚁集团 CEO 韩歆毅提出以"有钱花""有命花"为核心的"两朵花"AI战略，旨在用AI守护用户财富与健康。 2026年春节的实战表现，印证了这一战略的加速落地：一侧深耕AI健康，切入数十万亿规 #智平方完成B轮系列超10亿元人民币融资，公司估值正式超过百亿 通用智能机器人公司智平方 ...

Core Viewpoint - Taalas aims to revolutionize AI inference by hard-coding AI model weights directly into chip transistors, eliminating software redundancies and simplifying device architecture, which addresses the memory-computation barrier faced by traditional GPUs and AI XPUs [2][6][10]. Company Overview - Taalas, founded two and a half years ago, has raised over $200 million through three rounds of venture financing and is based in Toronto, a hub for AI research and chip talent [3][4]. - The founders, including CEO Ljubisa Bajic, have extensive backgrounds in chip design and AI, with previous experience at companies like AMD and Tenstorrent [3][5]. Technology and Architecture - Taalas combines ROM and SRAM to create a high-density architecture for AI inference, allowing for the storage of model weights and execution of computations at high speeds [6][10]. - The current generation of Taalas chips can support up to 8 billion parameters, with plans for the next generation to support up to 20 billion parameters, significantly reducing the number of chips needed for large models [10][11]. Production and Cost Efficiency - The cost of training a model is approximately 100 times higher than the cost of customizing a Taalas chip, making it economically viable for companies to order custom accelerators for their models [11]. - Taalas has developed a "foundry-optimized workflow" with TSMC, allowing customers to convert model weights into deployable PCI-Express cards within two months [12]. Performance Metrics - Initial performance tests indicate that Taalas's HC1 chips demonstrate lower costs and latency compared to traditional GPU systems, with the potential to disrupt the AI inference market [17][19]. - The HC1 chip integrates 53 billion transistors and operates at a power consumption of approximately 200 watts per card, with a dual-socket server consuming around 2500 watts [12][13]. Future Developments - Taalas plans to release a hard-coded 20 billion parameter model by summer and aims to support multiple models through clusters of HC cards by the end of the year [13][19].