Everyone is now talking about this new way of using AI in an interactive form of communication. When we talk about free or open and AI, these three questions immediately came to my mind: “If you're not paying for the product, then you are the product.” That's a quote from Daniel Hövermann in The Social Dilemma. What will be the business model? "Will my Job be replaced?" "Can I trust, and what is my remaining responsibility?"
This blog post is about, how to customize a classification model for Watson NLP for Embed and use it on your local machine.
This blog post is about, how to create a custom dictionary model for Watson NLP. One capability of the Watson NLP is the "Entity extraction to find mentions of entities (like person, organization, or date)." We will adapt the Watson NLP model to extract entities from a given text to find single entities like names and locations which are identified by an entry and its label.
This blog post is about using the IBM Watson Natural Language Processing Library for Embed on IBM Cloud Code Engine and is related to my blog post Run Watson NLP for Embed on your local computer with Docker. IBM Cloud Code Engine is a fully managed, serverless platform where you can run container images or batch jobs.
This blog post is about using the IBM Watson Natural Language Processing Library for Embed on your local computer with Docker. The IBM Watson Libraries for Embed are made for IBM Business Partners. Partners can get additional details about embeddable AI on the IBM Partner World page. If you are an IBM Business Partner you can get a free access to the IBM Watson Natural Language Processing Library for Embed. To get started with the libraries you can use the link Watson Natural Language Processing Library for Embed home. It is an awesome documentation and it is public available.
This blog post is about a simple example to use the Watson Assistant API v2 with the Node.js SDK to get a Watson Assistant sessionID and send a message to Watson Assistant using this sessionID. Here is the GitHub project watson-assistant-simple-node-js-server-example.
This blog post is about IBM Cloud Watson Speech to Text (STT) language model customization. Currently I took a look at the IBM Cloud Watson Assistant service used to build conversational assistants. A conversation leads potentially to speech input of users, which needs to be converted to text to be processed using AI for example the NLU.
Thomas Suedbroecker's Blog 