The post discusses the development of phi-3-mini in alignment with Microsoft’s responsible AI principles, focusing on safety measures such as post-training safety alignment and red-teaming. It highlights the importance of addressing AI harm categories through curated datasets and iterative improvements based on feedback from an independent red team.
Sovereign AI clouds provide essential control and compliance for manufacturers, ensuring that their proprietary data remains secure and localized. As the demand for AI-driven solutions grows, managed service providers are positioned to deliver customized AI platforms that meet regulatory requirements while enhancing competitive advantage.
The Trump administration is preparing to introduce new restrictions on AI chip exports to Malaysia and Thailand to prevent advanced processors from reaching China. These regulations could create volatility for cyclical tech stocks while allowing US data center operators to continue importing AI chips without significant disruption.
AI governance and data governance are critical for ensuring ethical and reliable AI solutions in modern enterprises. These frameworks help organizations manage data quality, transparency, and accountability, fostering trust in AI-driven initiatives.
In a significant move, BRICS nations have urged the United Nations to take the lead in establishing global regulations for artificial intelligence (AI). This initiative highlights the growing consensus on the need for structured governance to ensure that AI technologies benefit all countries equitably and responsibly.
Singapore is proactively addressing the challenges posed by data use in the age of artificial intelligence, emphasizing the need for robust data protection measures and the importance of adapting laws and social norms. Minister for Communications and Information Josephine Teo highlighted the role of data in the AI development lifecycle, while also stressing the necessity for independent testing to ensure generative AI applications function reliably.
The Asia-Pacific region is experiencing a rapid expansion of AI-powered surveillance technologies, especially from Chinese companies, yet lacks the governance frameworks to regulate their use effectively. This creates a significant risk as these technologies can be repurposed to consolidate political control and suppress dissent.
Generative AI is rapidly gaining attention in the financial sector, prompting firms to integrate this technology responsibly into their anti-financial crime frameworks. Experts emphasize the importance of strong governance, transparency, and human oversight to ensure that AI models are effective and compliant with evolving regulations.
Artificial intelligence (AI) is revolutionizing tax compliance by automating processes, improving accuracy, and enhancing efficiency in tax operations. With its ability to analyze large datasets, AI provides valuable insights that help businesses navigate the complexities of tax regulations and optimize their strategies.
The paper discusses the debate on whether frontier AI regulation should focus on the core technology (AI models) or its uses, highlighting the challenges of both model-based and use-based approaches. It proposes an alternative approach: entity-based regulation that targets the large business entities developing powerful AI systems, aiming to better address the unique risks posed by frontier AI.