What Can You Do with Continuous Intelligence? – RTInsights

By integrating continuous intelligence systems into business processes using real time and historical data, organizations can respond in near real time.

Oh, the many questions to ponder when it comes to extracting value from data.

What if you could analyze data as its created?

What if you could visualize your business?

What if you could better predict your customers needs?

What if you could gain insights from unstructured data like audio, text, or video?

What if you could automate immediate actions?

What if you always knew where your assets were, and where they would be?

What if you could update machine learning models continuously?

And what if you could do it all in real time?

Streaming analytics engines have the power and sophistication to answer the questions above in real time. As computing and networking costs have continued dropping year after year, sensors are monitoring nearly everything. Bluetooth, Wi-Fi, and 5G networks have enabled near-instantaneous delivery of huge volumes of data.

Deep learninguses artificial neural networks to recognize patterns in data. A human brainhas about 200 billion neurons, with about 32 trillion connections between them.Its these connections that enable people to recognize the pattern in speech,facial expressions, and so much more. Artificial neural networks have far fewerconnections, but as they continue to grow, they continue to improve inaccuracy.

These artificialneural networks have been applied to many areas, such as vision, speech,acoustics, natural language processing, medical image analysis, and board gamesranging from chess to go. In many of these situations, they have producedresults beyond top experts:

Whilethese high-profile grand challenges in computing were aimed at specific tasks,the experience gained has been applied to much broader areas.

Combiningall these forms of artificial intelligence with continuous intelligencedrawingfrom geospatial, real-time, and historical analyticscan further enhancebusiness ability to know where assets and people are at all times and helppredict what might occur next. One effort some years ago used anonymizedtelephone location data to predict with 95% accuracy where people would bebased on their past movements. Were all creatures of habit, going to work,school, synagogue, mosque, or church with great regularity, enabling thesekinds of predictions.

Addingrules engines and programmatic logic to AI, location data enables organizationsto automate many decisions that previously required human insights. Frompredictive maintenance based on actual driving conditions to decide the bestnext action to take with customers to improve loyalty, leading companies aredecreasing costs and improving revenues to become more successful.

Summary

By integrating continuousintelligence systems into business processes using real time and historicaldata, organizations can respond in near real time. Monitoring model drift andautomating model refresh and deployment enables the use of the most accurate AIto deliver on organizational improvements.

To learn more about these topics and get your questions answered, come hear me speak at IBMs Data and AI Forum on October 23, 2:15 pm3:00 pm. The Forum, which runs from October 21-24, 2019 in Miami, is the premier data and AI gathering of the year to learn how to drive smarter decisions, formulate more effective strategies and achieve better business outcomes with analytics.

I will discuss the role thatcontinuous intelligence plays in both AI and business and walk you through the benefits of using analytics to not only predict what will happen,but what to do about it.

See you there.

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What Can You Do with Continuous Intelligence? - RTInsights