What is the difference between a conversational AI platform and a natural language processing system? A conversational AI platform is basically a software system that has been specifically designed to interact with various technologies, sites, and applications in a more human-like manner through spoken, text or touch input. The technology is based on deep learning techniques and is capable of learning from past conversations with humans in order to better understand their interactions.
In contrast, deep learning uses pre-programmed neural networks to process large volumes of data and is capable of creating sophisticated machine learning models. This allows it to identify relevant information and build relationships and suggestions. Deep learning can also be used for classification purposes by predicting what type of results a model will provide based on the previous results of similar models.
As you can see, there is a significant difference between a conversational AI platform and a deep learning model and using a natural language processing system can be a good choice when building a conversational artificial intelligence system. However, not all of the systems are able to process large volumes of data, which requires the use of specialized hardware and programming languages to train these models.
The ability to develop conversational artificial intelligence and develop applications that work with it is still in its early days, but with a little bit of effort you can be well on your way. As long as you learn from your mistakes, have a solid understanding of how your system works and use the right hardware and programming language, you can be sure to produce some impressive results with your new conversational AI platform.
If you want to build a conversational AI for business applications, start by choosing a deep learning model. You can even create an individual application that integrates with other programs if you so choose. However, if you are only going to use a conversational model for business applications, you need to consider several things. The primary consideration is the amount of time you have available to spend training the model, and how much memory it needs to be able to store enough data and make intelligent suggestions.
Once you have determined the amount of time and memory needed, you should choose a platform that has built in tools for conversational AI training so that your model can easily adapt to your training needs. This will help it learn from past conversations and create the best recommendations based on the information it learns from the conversations it encounters.