Core Insights - Meta will resume using publicly available content from European users to train its AI models, a process that was previously halted due to data privacy concerns raised by activists [2][3][4] - The AI training will utilize public posts and comments from adult users in the European Union, as well as interactions with Meta AI [3][5] - Meta's AI training efforts faced challenges due to strict EU data privacy laws, but a panel of EU privacy regulators confirmed that Meta's approach complies with legal obligations [4][5] Company Actions - Meta has launched its Meta AI assistant for European users, following its earlier rollout in the United States and other major markets [3] - The company will notify EU users about the AI training and provide a form for users to object to their data being used [5][6] - Meta emphasized that it will not use private messages for AI training and is following practices established by competitors like Google and OpenAI [5]

Meta announced on Monday that it’s going to train its AI models on public content, such as posts and comments on Facebook and Instagram, in the EU after previously pausing its plans to do so in response to regulatory pressure due to to data privacy concerns. The company will start training its AI on users’ content in the EU this week, it said. Users’ interactions with Meta AI will also be used to train its models.The announcement comes after a limited version of Meta AI launched in the EU last month, well a ...

Core Insights - Cisco's 2025 Data Privacy Benchmark Study highlights the critical role of data privacy in establishing business value and trust, particularly in the context of AI readiness [2][3] - The study reveals a complex landscape where local data storage is perceived as safer, yet organizations still rely on global providers for their expertise in data protection [3][4] Data Privacy Trends - 90% of organizations view local data storage as inherently safer, while 91% trust global providers for better data protection, indicating a dual reliance on both local and global data strategies [3] - Privacy legislation positively impacts customer trust, with 86% of respondents noting its benefits, an increase from 80% the previous year [4] Consumer Awareness - The 2024 Cisco Consumer Privacy Survey indicates that 53% of global consumers are aware of their country's privacy laws, with 81% of those feeling confident in their ability to protect their data [5] AI and Data Privacy - Familiarity with Generative AI (GenAI) is rising, with 63% of respondents being very familiar, yet concerns about data privacy risks remain significant [6] - 64% of respondents worry about inadvertently sharing sensitive information, highlighting the need for tools like Cisco's AI Defense to mitigate risks [6] Investment Shifts - 99% of respondents anticipate reallocating resources from privacy budgets to AI initiatives, indicating a significant shift in focus towards AI governance [7] - IT budget allocations for AI are expected to nearly double in the coming year as companies aim to safely deploy AI technology [7] Strategic Importance - The study emphasizes the need for organizations to balance local data storage, global expertise, and privacy as essential strategic investments for sustainable growth and consumer trust in an AI-driven world [9]

This article has been reviewed according to Science X's editorial process and policies . Editors have highlighted the following attributes while ensuring the content's credibility: Apple CEO Tim Cook in June 2024 announces plans to incorporate AI into Apple software and hardware. Has Apple, the biggest company in the world, bungled its generative artificial intelligence strategy? Doubts blew out into the open when one of the company's closest observers, tech analyst John Gruber, earlier this month gave a bl ...

Core Insights - The discussion revolves around how value will be created and sustained in the AI-driven era, emphasizing the importance of unique market entry strategies, specialized knowledge, and access to unique data sources [3][4][5] - Companies in sectors like finance, law, and healthcare are highlighted as potential areas for creating lasting value due to their complexity and the foundational work required [3][4] - The balance between showcasing future capabilities and current model limitations is crucial for both startups and established vertical SaaS companies [5][6] Group 1: Value Creation in AI - Unique market entry strategies and specialized knowledge are essential for creating value in the AI landscape [3][4] - Companies that can leverage foundational models while maintaining a deep understanding of their specific industries will thrive [4][5] - Startups may benefit from over-promising during early adoption phases, while established companies face challenges in managing customer expectations [5][6] Group 2: Product Development Challenges - Startups must decide whether to build products based on current technology or anticipated future advancements, as model quality significantly impacts product outcomes [6][7] - The rapid evolution of AI models necessitates a careful approach to product design, balancing speed of release with quality and user experience [19][20] - Companies must develop robust evaluation frameworks to adapt to changing models and user needs, ensuring their products remain relevant [20][21] Group 3: Competitive Landscape - The AI market is becoming increasingly competitive, with numerous companies releasing products simultaneously, complicating product marketing strategies [24][25] - Companies must navigate the complexities of product releases and user expectations, balancing innovation with stability [22][23] - The importance of brand loyalty is emphasized, as users tend to identify with specific models, impacting their long-term engagement [27][28] Group 4: Data and Model Quality - The future of AI models may rely on a combination of human and synthetic data, with the best models emerging from this integration [15][16] - The quality of models is closely tied to the data used for training, highlighting the significance of having strong foundational data sources [30][31] - Companies must focus on the practical application of models in real-world scenarios to demonstrate their value [31][32] Group 5: Global AI Capabilities - There is a recognition that the capabilities of AI in China are often underestimated, with significant advancements being made in the field [32][33] - The emergence of parallel entrepreneurial ecosystems in regions with restricted access to Western platforms has led to innovative solutions [32][33] - Companies must be aware of the global competitive landscape and the potential for new entrants to disrupt established markets [37][38]

Microsoft says that it has completed a multi-year project to allow Europe-based customers using its cloud services to store and process data in the EU.The project, the EU Data Boundary for the Microsoft Cloud, began in January 2023, went on for two more years, and finally wrapped up this February, Microsoft said. With its completion, European customers can store and process data for Microsoft core cloud services, including Microsoft 365, Dynamics 365, Power Platform, and most Azure services, within the EU a ...