科大讯飞董事长：基于国产算力的新算法研发，会慢但不会矮

Core Insights - The chairman of iFlytek, Liu Qingfeng, emphasized the challenges of developing algorithms based on domestic computing power compared to using overseas solutions, noting a potential delay of three months in algorithm development [1] - iFlytek is committed to a self-controlled path in algorithm development, citing the need for independence to avoid being constrained by external factors [1] - The company has seen significant success in various sectors, including education and legal, with its AI models outperforming competitors in specific applications [3][4] Group 1: Business Development - iFlytek's business is thriving across C-end, B-end, and G-end sectors, with numerous benchmark cases emerging from state-owned enterprises [3] - The company has achieved comprehensive leadership in the financial and state-owned enterprise markets, focusing on solidifying its foundational models and standard products [4] - The star product, the X1 model, has shown impressive performance in medical and legal applications, with accuracy rates significantly surpassing competitors [3][4] Group 2: Consumer Market Performance - iFlytek's consumer products, including learning machines and translation devices, have dominated sales on major platforms, with a 25% year-on-year revenue growth [6] - The total user base for the SaaS product "Tingjian" has reached 90 million, reflecting a 54% year-on-year increase [6] - The overseas market has seen explosive growth, with the number of overseas developers increasing by 31.9% and AI marketing revenue growing 25 times year-on-year [6] Group 3: Future Outlook - Liu Qingfeng believes that a nation's global influence will be measured by the number of sovereign large models it can provide, positioning iFlytek to contribute significantly to this landscape [6] - The year 2025 is anticipated to mark the beginning of widespread AI adoption, with projections indicating that 17.7% of China's population will be users of generative AI by the end of 2024 [6] - iFlytek aims to capture the foundational benefits of the AI era by focusing on self-control, integration of software and hardware, and addressing industry-specific needs [6]