Building and implementing artificial intelligence (AI) models in your business is currently extremely time-consuming and complex. With Kubernetes as a Service from Netstream , you delegate all the necessary calculations to the Kubernetes cluster, thus relieving you of a significant portion of the workload.
Machine learning techniques are increasingly being used to simplify problems in our daily lives. Various industries are utilizing the technology and have already achieved significant success: self-driving cars, image recognition, translations, speech recognition, games, and even medicine. Given these new possibilities, it's no wonder the Businessworld quickly embraced the technology.
Building effective AI models and deploying them in practice remains complex and time-consuming. The technology requires uploading and processing large datasets. The machine learning model then has to classify the data to, for example, recognize images. Afterward, the AI needs to be "trained," which is particularly time-consuming. Once the model has learned enough, it is finally implemented in an app that can then be used directly.
Many companies simplify the lives of data scientists and machine learning engineers by introducing various tools such as Kubeflow or Neptune, which can accelerate the process. This can significantly reduce the number of necessary steps and speed up app development.
Kubernetes can further improve, simplify, and accelerate app development at this point: With Kubernetes as a Service all the computations required to train the machine learning model can beagto a Kubernetes cluster. The data scientist or machine learning engineer only needs to focus on data cleansing and the actual code. The rest is handled by a Kubernetes-based tool.
With Kubernetes as a Service from Netstream , you can develop such apps directly in the Netstream Cloud and easily deploy them.
Advantages:
- Utilizing computing power from the Cloud
- Kubernetes saves you time and complexity.
- Develop apps for market faster.
- Distribute and utilize resources more effectively.
