Bluemix Overview
This document will give an overview of what Bluemix has to offer.
Building Apps
Cloud Foundry Applications
Bluemix includes runtimes for Java, Node.js, PHP, Python, Ruby, Go, and available Cloud Foundry community build-packs.
Most likely, you will be using cloud foundry applications. Our starter-app server is based on node-js
and Cloudant
. Feel free to check out the other build packs and boiler plate applications here.
-> more info
Containers
??? -> more info
Virtual Servers
Deploy virtual servers provisioned on OpenStack. If you would like to deploy your own virtual server, look into this option. -> more info
Watson APIs
- Alchemy API
- Description: Uses NLP and ML algorithms to extract meta-data from content, such as information on people, places, companies, topics, facts, relationships, authors, and languages.
- Input: Web pages, HTML content, or text content
- Output: Metadata based on the content that was passed
- Notes:
- Concept Insights
- Description: Allows users to find similar content and suggestions for new content
- Input: Text or a collection of documents
- Output: Related documents (based on the collection) and concepts mentioned in the input document
- Notes:
- Dialog
- Description: Enables applications to use natural language to respond to user's questions or comments.
- Input: Script conversations based on your expert knowledge of the domain.
- Output: End users can chat with your application using natural language and get the pre-written responses you created.
- Notes:
- Document Conversion
- Description: This service prepares documents so they can be used by other Watson APIs.
- Input: A Microsoft Word Document, A HTML Document, A PDF Document
- Output: An answer unit JSON document, a plain text document, or a HTML document
- Notes:
- Language Translation
- Description: Translate text into one of the supported languages.
- Input: Plain text in one of the supported input languages and domains.
- Output: Plain text in the target language selected.
- Notes:
- Natural Language Classifier
- Description: Handle common questions from users, classify SMS texts as personal, work, or promotional, classify tweets, and control outcome of user.
- Input: Text to a pre-trained model
- Output: Classes ordered by confidence
- Notes:
- Personality Insights
- Description: The service outputs personality characteristics that are divided into three dimensions: the Big 5, Values, and Needs.
- Input: JSON, or Text or HTML (such as social media, emails, blogs, or other communication) written by one individual
- Output: A tree of cognitive and social characteristics in JSON or CSV format
- Notes:
- Relationship Extraction
- Description: Analyze news articles and perform linguistic analysis of the input text.
- Input: Text news articles
- Output: XML document of the entities from the text and the relationships of said entities.
- Notes:
- Retrieve and Rank
- Description: Find the most relevant information for your query using machine learning algorithms.
- Input: Documents, Queries (Questions), and User Queries (Questions)
- Output: Indexed Documents, Rank (ML Model), List of relevant documents and metadata.
- Notes:
- Speech to Text
- Description: Converts speech into text.
- Input: Streamed or recorded audio
- Output: Text transcriptions of the audio
- Notes: The transcription of incoming audio is corrected as more speech is heard. Supported languages include US English, UK English, Japanese, Spanish, Brazilian Portuguese, Modern Standard Arabic, and Mandarin.
- Text to Speech
- Description: REST API to convert text to speech in many different voices.
- Input: Plain text in one of the supported languages.
- Output: Returns the audio in
ogg
,wav
, orflac
formats. - Notes: Developers can control the pronunciation of specific words. Supported languages include Brazilian Portuguese, English, French, German, Italian, Japanese, and Spanish.
- Tone Analyzer
- Description: Detects three types of tones from text: emotion, social tendencies, and language style
- Input: Text
- Output: JSON object that represents the analysis of the input message.
- Notes:
- Tradeoff Analytics
- Description: Helps people make decisions when balancing multiple objectives by using the
Pareto Optimization
filtering technique. - Input: A decision problem with objectives.
- Output: JSON object that represents optimal options and highlights the tradeoffs between them.
- Notes:
- Description: Helps people make decisions when balancing multiple objectives by using the
- Visual Recognition
- Description: Understand the content of images.
- Input: Image
- Output: Relevant classifiers related to objects, events, and settings.
- Notes: Can also train the API to detect custom content.
-> more info