Occasions v6 ML
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Occasions ML envisions feed data from the network edge processed for segmentation logic and machine based rationalization within a session while feed data from enterprise data stores, exchange environments and cloud APIs runs continually.
The data organization schema reduces latency from backhaul processes and provides up to the minute accuracy. Steadily processing big data in a feed forward architecture makes back office and cloud data readily available to IOT APs with reduced calculations per session.
IBM CEO Ginni Rometty identified thinaire as a cognitive IOT partner during her CES 2016 keynote.
The data organization schema reduces latency from backhaul processes and provides up to the minute accuracy. Steadily processing big data in a feed forward architecture makes back office and cloud data readily available to IOT APs with reduced calculations per session.
IBM CEO Ginni Rometty identified thinaire as a cognitive IOT partner during her CES 2016 keynote.
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