Meanwhile, building artificial intelligence (AI) models and implementing them in your business is extremely time-consuming and complex. With Kubernetes as a Service from Netstream, you leave all the computations you need to the Kubernetes cluster, taking much of the work off your hands.
Machine learning techniques are increasingly being used to simplify problems in our daily lives. Various industries are using the technology and can already celebrate major successes in this regard: self-driving cars, image recognition, translations, speech recognition, games and also in medicine. It's no wonder that the business world has quickly warmed up to the technology, given the new possibilities.
Building effective AI models and deploying them in operations remains complex and time-consuming today. The technology requires large data sets to be uploaded and processed. The machine learning model must then classify the data to recognize images, for example. After that, the AI must be "trained," which takes a particularly long time. Once the model has learned enough, it is finally implemented in an app that can then be used directly.
Many companies simplify the life of the data scientist or machine learning engineer by introducing various tools such as Kubeflow or Neptunethat are capable of accelerating the process. This can already significantly reduce the number of necessary steps and accelerate app development.
Kubernetes can further improve, simplify and accelerate app development at this point: With Kubernetes as a Service, all the computations needed to train the machine learning model can be outsourced to a Kubernetes cluster. The Data Scientist or Machine-Learning Engineer only has to take care of the data cleaning and the actual code. The rest is done by a Kubernetes-based tool.
With Kubernetes as a Service from Netstream, you can develop such apps directly in the Netstream Cloud and also deploy them easily.
Advantages:
- Harnessing computing power from the cloud
- Kubernetes saves you time and complexity.
- Develop apps to market faster.
- Distribute and use resources better.
