It is becoming clear that AI will be a critical competitive differentiator for organizations, industries, and even countries. It is also clear that many are looking for success stories to leverage into learning opportunities. As AI embeds its intelligence throughout organizations, the sophistication of the data usage will increase to a point where traditional data approaches will need to extend to include real-time data streams of images, videos, speech, events, and operational data. It means that new data approaches will be necessary. As AI gets more sophisticated at speed, its hunger for complex data becomes insatiable. As organizations learn to leverage AI, emergent problems can now be attempted. You can find strong case studies of emergent AI acting on data streams by clicking here.
Leveraging AI Starting with Machine Learning (ML)
Machine learning allows applications to learn from the data in order to make better decisions at speed. There is significant value in creating predictive applications that can smartly select smart actions that meet or intercept emergent data from multiple and intersecting contexts. This iterative learning and improvement cycles are driven by emergent data, shifting goals, and guardrails that are invaluable for organizations that want to stay in step or ahead of their market place and constituents.
Intermediate AI Applications Leverage Smart Streaming
As AI gets more sophisticated in its learning ability by applying deep learning and even cognitive thinking leveraging interpretation, recognition, scoring, intuition, reasoning, and judgment, the hunger for faster multiple data sources will grow. Streams of complex and evolving data will need to be utilized in solving both static and emerging problems.
Putting a Premium on Emergent, Fast and Agile Data Sources
Looking to the past is valuable, but today's demands require organizations to get in front of business events, constituents, and competitors. The data sources will include traditional and non-traditional data such as voice, video, and images. The speed and mixes of data types and sources will be dynamic and agile. Instant integration and transformation will be the norm to satisfy prediction and intelligence needs fueled by AI and analytics.
AI is gaining momentum and is taking on predictive applications that leverage fast and agile data sources. As AI migrates to the edge over time, the notion of fast streams of event and pattern data will grow along with traditional big and fast operational data. Organizations that want to thrive and capitalize on leveraging AI and smart streams will get ahead of the curve by learning from successful implementations. Please click here to access an E-book for some impressive case studies that leverage AI-enabled smart data streams.
Click here for the E-Book entitled "The Future Starts Now" subtitled "Achieving Successful Operations of ML & AI-Driven Applications."