ML Collaboration and Management Platform
AI-Stack is a machine learning collaboration and management platform featuring machine learning in Kubernetes functionality to make complex deployments in AI and Big Data easier.
Accelerate AI adoption today.
How it Works
The platform enables data science teams, developers, and IT teams to simplify and streamline workloads through a single system.
AI/ML capabilities are already integrated into this cloud so that users can focus on AI/ML workloads and not on system maintenance, adjustment and deployment scheduling. The cloud reduces complexity and the learning curve for users to adopt and master Tensorflow, Caffe, and other deep learning tools.
Containers make it easier, more secure, and faster for developers to develop, scale, and deliver AI applications. They also make it easier for data scientists to work with AI. Both Docker + Kubernetes are containers that can be used in this system.
Kubernetes is fast becoming essential to AI work and is a key feature of this cloud platform. It is the most popular container in machine learning workloads, as most scenarios are set up to run in Kubernetes containers due to its interactive mode capability. Because Kubernetes containers can be scheduled and managed throughout the life cycle, it’s also a favorite among developers and DevOps practitioners working with continuous release or continuous delivery application development processes. Machine learning developers also heavily favor Kubernetes for those same reasons.
Open source tools are increasingly becoming available on the market and further add appeal to using Kubernetes for data science work. For example, the Kubeflow open source tool enables teams to easily attach existing machine learning jobs to a cluster without having to do much in the way of adaptations or integrations.