Recently, the 2024 State of AI Report released by Appen has garnered significant attention. Based on a survey of over 500 IT decision-makers in the U.S., the report reveals that generative AI has grown by 17% in the past year. However, alongside this growth, companies are facing considerable challenges in data management. Si Chen, Appen's Head of Strategy, mentioned in an interview that as AI models are increasingly applied to more complex and specialized domains, the demands for data have risen significantly.

Relativity, a legal technology company in the United States, announced its integration with the ChatGPT Enterprise Compliance API from OpenAI, providing users with a seamless way to collect and process human-machine conversational data. This integration makes ChatGPT Enterprise part of the data sources for RelativityOne, allowing users to easily collect and process conversational data between humans and machines.Image source note: Image generated by AI, licensed service provider MidjourneyChatGP

Informatica's latest CDO Insights 2024 report indicates that data quality is the biggest barrier to implementing generative AI. The survey shows that 45% of companies have already implemented generative AI, while 53% plan to do so. The report highlights that data quality, data privacy, and AI ethics are major concerns for businesses when implementing generative AI. The use of data management tools also impacts generative AI projects, and attention to data quality is key to successful implementation.

The survey shows that data leaders in the Asia-Pacific region plan to incorporate generative artificial intelligence into business operations within the next 24 months, but face ethical and privacy challenges during adoption. Data leaders emphasize that successful implementation of generative AI requires comprehensive and integrated data management capabilities, and investment in this area is crucial to unlocking potential. Data leaders in the Asia-Pacific region are concerned about issues such as data ethics and privacy protection, with Australian and Singaporean data leaders facing major obstacles in generative AI implementation, including data bias and fragmentation. The survey results indicate that 64% of South Korean...

Canadian company Secoda successfully raised 14 million USD, planning to apply AI technology to enterprise data search and management, allowing users to easily search, understand, and utilize company data as if using Google. This round of funding was led by Craft Ventures, with participation from investors such as Abstract Ventures, YCombinator, and Garage Capital, aiming to address the challenges of data fragmentation and management in enterprises. Secoda has already achieved...