Subject archive for "reproducibility"

Weaving Generative AI into your company’s core processes has the power to transform your business. There’s just one catch, and it’s a big one – it’s still a risky endeavor, so tread lightly.

For multinational enterprises, compliance with the AI Act is not just a legal requirement, but also an opportunity to drive business transformation by fostering safer, governed, and more responsible AI.

Domino Flows unlocks the power of AI and machine learning flows, transforming them into a critical element of your responsible AI strategy.

AI orchestration has become a game-changer in life sciences, enabling the integration and automation of complex data and analytical tasks.

True reproducibility means anyone can return to a point in time — anywhere in the AI/ML lifecycle — and see how a model was built and understand its purpose and KPIs. Yet, most AI models are built outside of controlled environments and systems of record. Enterprise AI platforms like Domino solve this by automatically unifying and capturing all model provenance and all artifacts across teams, users, tools, and environments without manual detective work, which can produce mixed results.

Reproducibility is a cornerstone of the scientific method and ensures that tests and experiments can be reproduced by different teams using the same method. In the context of data science, reproducibility means that everything needed to recreate the model and its results such as data, tools, libraries, frameworks, programming languages and operating systems, have been captured, so with little effort the identical results are produced regardless of how much time has passed since the original project.