Machine Learning Operations

Reliable and scalable AI with MLOps

The biggest challenge in production-level AI is not finding the best ML model but building a reliable, scalable, and maintainable system for operating it in production and developing it continuously. Learn from Silo AI experts how to take the first steps to become AI-driven.

Episiode 14 Ville Tuulos

Ville Hulkko | 08.04.2021

Episode 14: Experimentation culture of Netflix – Ville Tuulos

Machine Learning is defined by a need for rapid experimentation. To achieve an environment of fast, iterative and low-risk experimentation, both hard aspects (tools and platforms) and soft aspects (culture, ways of working) of the ecosystem need to be aligned.

PODCAST

solutions-1000

Pauliina Alanen | 15.04.2021

Building operational AI/ML with MLOps

In this webinar, we dived into the infrastructure and organizational requirements of getting real-time machine learning-driven insights and analytics, that help run your operations smoothly. With our invited guest Unity, we showed an example of how solid machine learning operations (MLOps) helps scale several machine learning products at once.

WEBINAR

mlops-cv-product-blog

Hossein Yousefi | 21.04.2021

Implementing end-to-end scalable MLOps for a CV product

The overall goal of MLOps is to make the process of productizing ML models smoother. MLOps applies the DevOps techniques, concepts and practices to machine learning systems with an increased demand to take care of aspects around the activities, such as data versioning, data lineage and data quality. MLOps responses to an increased need for model observability and monitoring model performance.

ARTICLE

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Machine learning for predictive maintenance

Improve your production efficiency by ensuring reliable operations with machine learning and computer vision for predictive maintenance. As your trusted partner, Silo AI helps you build robust solutions permit you to be one step ahead.

Silo AI x NVIDIA webinar – Vessel and vehicle awareness

In this webinar, we’ll dive into using sensor fusion to improve situational awareness. Together with NVIDIA Inception, we’ll share key use cases enabled by NVIDIA components, and we’ll showcase invited guest Groke’s concrete use of sensor fusion to improve vessel awareness.

LATEST WEBINARS

How to scale AI – learnings from H&M and Silo AI

We welcome Errol Koolmeister, a former Head of AI at H&M, to talk about his learnings in building scalable AI at one of the world’s largest retailers, H&M. Errol is joined by Niko Vuokko, Head of Technology at Silo AI, who’ll share his experience in building scalable AI products together with industry leaders.

Sensor fusion for situational awareness

Learn how to benefit from sensor fusion to improve situational awareness. Together with NVIDIA Inception, we shared key use cases enabled by NVIDIA components, and we showcased invited guest Groke’s concrete use of sensor fusion to improve vessel awareness.

Building operational AI/ML with MLOps

In this webinar, we dived into the infrastructure and organizational requirements of getting real-time machine learning-driven insights and analytics, that help run your operations smoothly. With our invited guest Unity, we showed an example of how solid machine learning operations (MLOps) helps scale several machine learning products at once.

Machine learning for predictive maintenance

In this webinar, we focus on machine learning for predictive maintenance together with our invited guests, Hanna Grönqvist, Senior Data Scientist at Hiab, and Slawomir Nowaczyk, Professor in Machine Learning at the Halmstad University and a Lead AI Scientist at Silo AI.