You must have heard this multiple times by now. Artificial Intelligence is not coming, it’s here. Cars are already driving themselves. Warehouses are working by themselves. Many of the support calls are now answered by bots. Virtual assistants are helping us in perhaps everything from finding the nearest chemist store to the best restaurants.
Major AI players like IBM Watson, Google API, AWS, Microsoft are all working towards providing usable intelligence to enterprises so that real-world problems can be solved easily. Common services they offer include intelligent search, a conversation that can be trained, speech to text and text to speech, and other than core ML libraries.
Let’s take an example. Organizations may need a Chatbot that can create PTO / vacation days for employees.
This kind of conversation can be configured in IBM Watson Conversation as below.
For more information on creating the dialog, please refer to this.
This is all based on UI-based configuration. Other than that, you can also train your bot for intents. For example, I may ask to apply for vacation in different ways.
Now the conversion is all prepared in IBM Bluemix.
To experience this conversation in applications is important. But, building a quality application with these services is still challenging. Delays due to the unavailability of resources or skills should not stop you from realizing AI benefits.
Low-code application delivery tools facilitate the ease of integration of these AI services. WaveMaker (a low-code platform) provides out-of-the-box components (aka “prefabs”) to have a Chatbot that can provide the front end for Watson Conversations.
Developers simply need to drag and drop the Watson Chatbot prefab and configure the conversation workspace and its related authentication.
If you need any help with building your AI applications, please email me at email@example.com.