Integrating synthetic data, digital twins and LLMs: Building a future where AI capabilities are a click or prompt away

SAS Viya addresses the complexity of modern enterprise decision-making by integrating synthetic data, digital twins, and large language models into a unified platform. This approach shifts the focus from mere data availability to outcome-driven insights, leveraging advanced analytics to solve specific business problems. By providing a lightweight programming environment, the platform enables organizations to harness AI power without being hindered by technical infrastructure limitations. A key innovation is the removal of coding barriers through tools like Workbench, allowing users to operationalize AI models seamlessly. By handling the underlying computer science, the platform empowers non-experts to focus on solving business challenges, as demonstrated by its application in matching kidney donations at Cambridge University. This democratization of technology ensures that innovation is accessible to a broader range of stakeholders, accelerating the adoption of AI-driven solutions across diverse industries. The article highlights the growing necessity for robust model management amid the explosion of available AI models. As organizations struggle to track model relevance and performance, effective management becomes critical for maintaining actionable intelligence. This is highly relevant to open data discussions, as it underscores the importance of accessible, transparent, and manageable data ecosystems. Open data principles facilitate the sharing of synthetic data and models, fostering collaboration and ensuring that AI-driven insights remain reliable, ethical, and widely applicable across communities.

Source: siliconangle.com
Published on 2023-09-14

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