Integration of voice control in smart devices is buzzing, and adoption continues to grow. Voice control provides a more natural way of interacting with connected apps and devices ranging from news feeds, traffic information to acting as personal assistants in the home. These intelligent devices respond to commands spoken in our own voice and act immediately.
The nature of money has evolved for a millennia and has now become fully digitized. Thousands of years ago, a bank account -- if you can call it that - likely consisted of a bag of coins or shells that were stashed away safely. During the Middle Ages, the double-entry accounting system was established, signaling the emergence of payments and the double-entry ledger then became the norm. This supported the movement of money across great distances. It also enabled money to be stored safely with a central party who could track and access those funds at different locations. This also facilitated the concept of credit, effectively paving the way for modern-day banking.
Many organizations have started to explore the value that machine learning can bring—from illuminating previously “dark data” such as images and videos, to creating models that help to guide or even automate business decision-making. However, very few companies have gone beyond pilots and prototypes, or made the transition from one-off projects to a scalable, repeatable workflow. Too often, machine learning exists in a bubble of its own, instead of being understood in the context of the broader data science workflow.
On Nov 1st, 2017, both Watson Speech to Text and Watson Text to Speech released Lite Plans, as part of IBM Cloud Platform’s initiative to roll out Lite Plans across public cloud services.
Machine learning is one of the most exciting areas of data science, with enormous potential to transform data into the pure gold of competitive advantage. Data scientists can seem like wizards when their models first accurately predict customer or market behavior, or reveal valuable insight from previously untapped data sources.
Over the past few years, we’ve seen a significant rise in popularity for intelligent personal assistants, such as Apple’s Siri, Amazon Alexa, and Google Assistant. Though they initially appeared to be little more than a novelty, they’ve evolved to become rather useful as a convenient interface to interact with service APIs and IoT connected devices.
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Imagine, you are in a conversation with a chatbot and you feel that the human angle is completely missing because the bot starts it's dialog with a usual "Hi" or "Hello". You may want to personify the conversation by adding the name of the person (who's logged in) to the boring "Hi" or "Hello". Ever thought of this? It's not just personification, How about wishing appropriately based on the time of the day someone invokes your chat application? Also, how about passing values back and forth during a conversation between the nodes or from application to a node?
Thank you for using IBM IoT for Automotive Experimental Bluemix service. We’d like to inform you that we are retiring the IBM IoT for Automotive Experimental Bluemix service on 10/18/2017.