Core Viewpoint - The article discusses the current state of the Japanese AI industry, highlighting the challenges faced by companies like Preferred Networks in achieving internationalization and the tendency towards a closed-loop system within Japan, which limits global competitiveness [3][6][36]. Group 1: Characteristics of AI Companies - True AI companies possess self-developed models and frameworks, while false AI companies primarily enhance information efficiency without genuine AI capabilities [5]. - Preferred Networks is identified as a true AI company due to its strong technology and product versatility across various industries [5][10]. Group 2: Preferred Networks Overview - Preferred Networks was established in 2014 and developed the deep learning framework Chainer, which initially garnered high expectations within the industry [7]. - The company has a strong patent portfolio with 435 patents globally, indicating its technological strength [9]. - Despite its capabilities, Preferred Networks has shifted towards a more localized approach, focusing on serving major Japanese corporations rather than pursuing international expansion [12][13]. Group 3: Financial Performance of PKSHA Technology - PKSHA Technology, founded in 2012, has shown strong profitability, with revenues increasing from 15 billion yen in 2018 to 169 billion yen in 2024 [21]. - The company has a diverse client base across various sectors, including retail and finance, indicating its robust market presence [21][22]. Group 4: Role of Major Corporations and Government - Major Japanese corporations like NEC and NTT have established AI departments primarily serving government and B2B sectors, contributing to a self-sufficient ecosystem [31][32]. - The Japanese government plays a significant role in AI development through organizations like NEDO, which focuses on funding technology research but often overlooks the growth of individual companies [25][26]. Group 5: Cultural and Structural Challenges - The Japanese AI industry is characterized by a conservative culture that limits open sharing of technology and collaboration, impacting innovation [11][23]. - The reliance on corporate venture capital (CVC) rather than traditional venture capital (VC) restricts the growth potential of startups, as they remain tied to the interests of large corporations [38].

Group 1 - Preferred Networks is recognized as a "true AI" company due to its reliance on deep learning, NLP, and generative models, along with its self-developed models and AI frameworks [1][3][4] - The company has a strong product versatility, offering solutions across various sectors including industrial automation, healthcare, and education, with over 435 global patents [5][6] - Despite its initial ambitions for international expansion, Preferred Networks has reverted to a domestic focus, raising concerns for other Japanese tech firms considering overseas ventures [2][10] Group 2 - Preferred Networks was founded in 2014 and developed the deep learning framework Chainer, which was once positioned alongside TensorFlow and PyTorch [3][11] - The company has shifted its strategy to collaborate with major Japanese corporations like Toyota and Nissan, focusing on customized AI systems rather than pursuing a broader international presence [13][18] - The company has established a new subsidiary, Preferred Elements, aimed at foundational technology development, indicating a potential shift towards a more open approach [14][16] Group 3 - PKSHA Technology, another prominent Japanese AI firm, has shown strong profitability with significant revenue growth, serving various industries including retail and finance [24][25][26] - Unlike Preferred Networks, PKSHA retains ambitions for international collaboration, partnering with companies like Microsoft and Tencent [26] - The early establishment of AI companies in Japan, such as PKSHA and Preferred Networks, was driven by a combination of engineering talent and industry demand for automation [28][30] Group 4 - The Japanese AI industry is characterized by a closed-loop system where startups primarily serve large domestic corporations, limiting their growth potential and innovation [44][45] - The government and large companies emphasize project-based AI solutions, which diminishes the drive for exploratory or innovative AI developments [44][45] - Cultural factors contribute to the lack of ambition for developing universal AI platforms, contrasting with the more aggressive approaches seen in other countries [30][43]