Oracle’s Platform as a Service (PaaS) will now feature artificial intelligence (AI) capabilities. This platform provides fast and easy access to machine learning and data science capabilities from the cloud. As Oracle is embracing Open Source in this AI Cloud it brings together the power of the scientific and data science community and the strength of Oracle with all its integration capabilities.
This blog post is the first of a series in which we will look into different aspects of this upcoming Oracle AI Cloud. Although Oracle never provides promise dates, delivery will likely either be linked to a major event, or come as a surprise. Either way, we can already deduce quite a bit about the new offering from the short description on the Oracle PaaS Cloud website.
- Libraries and Tool, containing the Python libraries that are crucial for complex operations on large data sets
- Deep learning Frameworks, with Tensorflow / Keras originating from Google supporting neural networks for deep analysis of data
- Elastic AI and machine learning Infrastructure underpins the platform with a rich set of high performance components
Oracle rightly chose to reuse what is already available in the market with regards to AI and machine learning and combine that with its own strong integration capabilities. This platform delivers the capabilities to extend and improve existing cloud and on-premises applications based on data and usage figures. Three use cases demonstrate these capabilities:
Learn from usage of applications
Learn from API usage
Improve costs structures of cloud usage
The cloud economic model is different from the model most customers are used to in their on-premises data centers. When going toward the cloud, a different financial model is in place, where usage and interfacing determine the bills to be paid at the end of the month. Understanding the inter connectivity and impact on cloud usage and economics makes it possible to continuously measure and save costs. The upcoming Oracle AI platform combines the power of open source, data science and machine/deep-learning capabilities, with Oracle’s integration capabilities to improve the usage and costs of both on-premises and cloud applications with knowledge about application and API usage.
In the forthcoming blogs, we will prepare for the AI cloud by looking at the tooling and frameworks, machine learning and infrastructure.
This blog series was co-authored by Léon Smiers and Johan Louwers. Léon Smiers is an Oracle ACE and a thought leader on Oracle cloud within Capgemini. Johan Louwers is an Oracle ACE director and global chief architect for Oracle technology. Both can be contacted for more information about this, and other topics, via email; Leon.Smiers@capgemini.com and Johan.Louwers@capgemini.com