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Xebia emphasizes data foundation for AI agents
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Why it matters
- →A strong data foundation is crucial for AI agents to function correctly.
- →Proper data management can significantly accelerate digital transformation.
- →Integrating AI into the software lifecycle can enhance efficiency and reduce costs.
Xebia's CTO, Niels Zeilemaker, stresses the importance of a solid data foundation for AI agents to function effectively. He points out that without proper data cataloguing, AI agents might misinterpret data, leading to errors. Xebia's Agentic Data Foundation aims to make data AI-ready, facilitating quicker migrations to modern platforms. Additionally, Xebia ACE integrates AI into the software development lifecycle, promising up to 40% faster delivery and significant cost savings. This approach ensures that AI processes maintain quality and governance, addressing potential security issues in AI-generated code.
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Microsoft AI drafts Humanist AI Code of Conduct
Microsoft AI has unveiled a draft Humanist AI Code of Conduct, initiating a public consultation to refine operational constraints for AI model training and deployment. This draft aims to ensure AI systems prioritize human authority, setting clear boundaries to prevent autonomous capabilities from overstepping. The initiative responds to recent security incidents and emphasizes the importance of maintaining control over AI systems. By rejecting the pursuit of unconstrained superintelligence, Microsoft seeks to build AI that is both useful and safe, even if it means limiting generality and autonomy. This move marks a significant step in addressing the real-world risks associated with advanced AI systems.
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Enterprise AI Agent Pilots Rarely Reach Deployment
Despite widespread adoption of AI agent pilots, a staggering 89% fail to transition into full-scale deployment, according to Deloitte's research. The issue isn't the AI models themselves but the surrounding infrastructure, including data access, evaluation, and cost management. Companies like Crunch-IS are addressing these challenges by focusing on the operational layers often overlooked in pilot phases. The few enterprises that succeed in scaling AI agents prioritize evaluation infrastructure, operational staffing, and governance, demonstrating that the key to success lies in robust operational frameworks rather than increased spending.
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Perplexity Portable Computer Launches on Windows with NVIDIA RTX
Perplexity's Portable Computer is now available for Windows users with NVIDIA RTX GPUs, offering a powerful local AI agent that can handle multistep tasks directly on a PC. This release allows users to keep sensitive information on their devices while leveraging local models for data analysis and task management. The integration with NVIDIA RTX GPUs ensures accelerated performance, and the app can seamlessly transition tasks to cloud models when needed. This development brings advanced AI capabilities to more Windows users, simplifying the setup and use of local AI models without the need for complex configurations.
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