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In the Industrial AI Podcast he discusses the adoption of generative AI, the importance of an ecosystem in its success, and using foundation models with company data. Peter Seeberg and Xiaopeng Li explore use cases of large language models in machine learning and techniques for mitigating hallucinations. They also explore the history of AI and the current status of AI development, highlighting the role of European organizations in industry-specific AI solutions.

Our main take aways:

  • Large language models are replacing traditional chatbots in contact centers to provide more natural language conversations with customers and assist human agents with analyzing call transcriptions for insights.
  • Industry-specific co-pilots powered by large language models are being developed in various industries, combining industry expertise with AI capabilities to enhance efficiency and decision-making in specific contexts.
  • Europe, with its accumulated industry-specific knowledge and expertise, is well-positioned to apply generative AI in various sectors, leveraging its deep industrial heritage.
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    The Global Landscape of Gen AI Adoption

    The adoption of generative AI varies across different regions, with the US and China leading in AI development, while Europe is catching up. However, Europe's accumulated industry-specific knowledge and expertise make it well-positioned to apply generative AI in various sectors. We can expect to see more industry-specific co-pilots and AI solutions coming out of Europe, leveraging its deep industrial heritage.