Deep Learning Market to Surpass $296B
The global deep learning market is projected to surpass $296 billion by 2031, growing at a compound annual rate of 35.48% between 2026 and 2031, according to a Mordor Intelligence report. Key drivers include rising investment in generative AI, widespread AI adoption, and demand for automation in computer vision and natural language processing.
- The ISO/IEC JTC 1/SC 42 is the primary international committee for AI standardization, developing foundational standards for AI concepts, trustworthiness, and governance to ensure global compatibility. More than 60 countries, over a third of which are developing nations, participate in this committee's work. - Major economies are pursuing distinct AI governance strategies: the European Union has adopted the risk-based AI Act, the United States is implementing a more decentralized, sector-specific approach guided by the NIST AI Risk Management Framework, and China is using a state-led model with top-down directives aligned with national priorities. - China's Ministry of Industry and Information Technology (MIIT) is a key player in its national AI standardization efforts, with bodies like the China Electronics Standardization Institute (CESI) supporting both domestic framework development and participation in international bodies like ISO/IEC JTC 1/SC 42. - The geopolitical competition over AI standards is intensifying, with a strategic pivot from focusing on acquiring the fastest hardware to controlling the underlying software and development ecosystems, such as the competition between NVIDIA's CUDA and Huawei's CANN platforms. - The International Telecommunication Union (ITU) has addressed AI in specific sectors, with a notable focus group on AI for autonomous and assisted driving (FG-AI4AD) that worked on defining performance thresholds to build public trust in AI-enabled vehicles. - The IEEE Standards Association has numerous working groups developing standards related to AI ethics and governance, including projects on algorithmic bias, data literacy, AI risk management, and organizational ethics oversight.
