The document provides a comprehensive overview of IBM Cloud AI, covering its various capabilities in machine learning, deep learning, and cognitive services. It discusses features such as visual recognition, language translation, natural language classification, and AI-assisted applications like Watson Assistant, with examples of case studies showing successful applications. Additionally, the document includes links to demos for each AI service and outlines the importance of transparency and bias detection in AI.

1. Satyajit Panda
IBM Cloud AI : A Comprehensive Overview

2. Agenda
2
3
4
Why IBM Cloud AI
IBM Cloud AI & Machine Learning
Case Studies
1 IBM Cloud AI : Overview

3. Why IBM Cloud AI
Comprehensive AI portfolio : Machine Learning | Deep Learning | Cognitive
Transparent AI: Bias Detection and Explainability
GDPR compliant
GPU and distributed training support
Integration with other IBM Cloud capabilities

4. IBM Cloud AI :Overview
Vision
Visual Recognition
Language
Language Translator
Natural Language Classifier
Speech
Speech to Text
Text to Speech
AI Assistant
Watson Assistant
Knowledge
Discovery
Natural Language Understanding
Knowledge Studio
Data
Watson Machine Learning
Watson Knowledge Catalog
Watson Studio
Empathy
Personality Insights
Tone Analyzer
Transparency
AI OpenScale

5. Visual Recognition
Visual Recognition helps analyzing images or video frames for objects, faces, and other content
It uses a default model, also supports creating own custom classifier
Model Types
General
Model
• Use your
own image
to classify
Food Model
• Classify
from around
2,000 foods
to identify
meals, food
items, and
dishes
Custom
Model
• Create
custom
visual
classifiers
Explicit
Model
• Assess
image for
objectionabl
e content
Face Model
• Detect
human
faces in the
image with
age range
and gender
Text Model
(Private Beta)
• Detect and
extract
recognized
words

6. Visual Recognition: Demo

7. Visual Recognition: Demo Continued …

8. Language Translator: Translates text from one language to another
Translate between different languages
High accuracy at faster speeds using deep learning models
Identify up to 62 languages
Build domain specific custom models by creating own corpus via a .tmx(Translation Memory
Exchange for CAT) file
Multilingual chabot
Translate contents of
documents,apps,web
sites
Translation of text
inside image
Voice to text language
translators
Use cases

9. Language Translator : Demo

10. Natural Language Classifier
It returns the best matching categories for a sentence or phrase with a probability
value
Spam Detection Product Classification
Question and answer
(Q&A) application
Classify news content
Use cases
Multiple language support | Multi-Category classification
Multi-Phrase classification | Watson Studio Integration

11. Natural Language Classifier: Demo

12. Speech to Text: Voice to Text
It converts the human voice into text
It combines information about grammar and language structure with knowledge of the
composition of the audio signal to generate an accurate transcription.
Voice control of
embedded systems
Transcription of
meetings and
conference calls
Dictation of email and
notes
Use cases

13. Speech to Text: Demo

14. Text to Speech: Text to synthesized audio
It processes text to generate synthesized audio output complete with appropriate cadence and
intonation
It is available in 13 voices across 7 languages
Things of Internet of
things
Navigation aids
Assistive technology
for differently abled
Use cases

15. Text to Speech: Demo

16. Watson Assistant
Conversational interface across a variety of channels
It provides a workspace to design the conversational interface
Use Cases
Customer care
• Improve customer relations
and reduce cost
Auto
• IBM® Watson™ Assistant for
Automotive is a digital
assistant designed to enhance
in-vehicle experiences
Hospitality
• IBM® Watson™ Assistant for
Hospitality offers a
customized digital assistant
for hotel guests

17. Watson Assistant : Chatbot of Autodesk

18. Watson Discovery

19. IBM Watson Discovery: Demo

20. Natural Language Understanding: Semantic understanding of text
Analyze semantic features of text input like categories, concepts, emotion, entities, keywords,
metadata, relations, semantic roles, and sentiment.
Extend Natural Language Understanding with custom models built on Watson Knowledge Studio.
Broad Language Support
Analyze Product review
Analyze social media
streams
Enhance chatbots with
better responses
Use cases

21. Natural Language Understanding: Demo

22. Knowledge Studio
Evaluate model
performance:
Measure and
evaluate the model
performance.
Integration : Use
models from Watson
Knowledge Studio
with Watson
Discovery, Watson
Natural Language
Understanding and
Watson Explorer.
End to end modelling
:Annotation, training,
and evaluation
Engage your SME’s:
SME’s can create
industry specific
custom models
without a single line
of code

23. Machine Learning: (Merged with Watson Studio)
Build, train, and deploy models using python client library, command line
interface, REST API
Deployment infrastructure for hosting your trained models
Hyperparameter
optimization
• Explore a search space of
potential Hyperparameters,
build a series of models and
compare the models using
metrics of interest
Distributed deep
learning
• TensorFlow with parameter
server and workers
• TensorFlow with IBM DDL
• TensorFlow with Horovod
GPUs for faster
training
• Specify GPU’s in
configuration file in
training manifest file
Machine Learning | Deep Learning

24. Knowledge Catalog(Merged with Watson Studio)
Govern Data
(Watson Knowledge
Catalog
Professional):Control
data access by
defining policies
Find Data: Discover
the data you need
and collaborate to
discover insights
Refine Data: Data
preparation and
cleansing
Catalog Data: Create
a 360-degree view of
your data

25. Watson Studio
Model Builder
• Build a model
using Spark ML
algorithms
Flow Editor
• Presents a
graphical view of
your
model(SPSS,
Spark ML)
Notebooks
• Collaborative
environment for
working with
data, rapid
prototyping and
testing of models
Experiment
Builder
• Automates
massive batch
training runs ,
tracking and
storing results
A graphical collaborative environment for designing, training, deploying, and
managing models with your machine learning services
Tensorflow, Keras, Caffee, Pytorch, Spark MLlib, scikit learn, xgboost and SPSS.

26. Personality Insights
Agreeableness is a
person's tendency to be
compassionate and
cooperative toward
others.
Conscientiousness is a
person's tendency to act
in an organized or
thoughtful way.
Extraversion is a
person's tendency to
seek stimulation in the
company of others.
Emotional range, Natural
reactions, is the extent to
which a person's emotions are
sensitive to the person's
environment.
Openness is the extent
to which a person is
open to experiencing
different activities.
Derive insights from transactional(email, text messages) and social media data(tweets, forum
posts).
Identify psychological traits which determine purchase decisions, intent and behavioral traits;
utilized to improve conversion rates.
It uses Big Five personality characteristics which describes how a person engages with the world.

27. Personality Insights : Demo

28. Tone Analyzer: Cognitive linguistic analysis
Tone Analyzer leverages cognitive linguistic analysis to identify a variety of tones
Three types of tones
Emotion
• Anger
• Disgust
• Fear
• Joy
• Sadness
Social propensities
• Openness
• Conscientiousness
• Extroversion
• Agreeableness
• Emotional range
Language styles
• Analytical
• Confident
• Tentative
Use cases: Trend analysis, opinion analysis | Predicting customer satisfaction in
public forums | Product feedback from social media

29. Tone Analyzer: Social Demo

30. AI OpenScale:Visibility,Bias detection
Observability : How AI affects business outcomes.
Payload logging and AI health monitoring
Bias detection and mitigation
Trust and Transparency in AI: AI is no more a black box.
Explainable AI recommendations: Trace and audit AI predictions
Monitoring: Fairness,Accuracy,Explainability

31. AI OpenScale:Visibility,Bias detection

32. IBM Cloud AI: Case Studies
Autodesk : Their chabot, Ava handles over 150,000
customer contacts per month and improved customer
response times by 99%. They are now
developing Autodesk Contract Explorer (ACE) which can
read and review arduous procurement contracts.
Fukoku Mutual Life Insurance: IBM Watson
actually replaced 34 human insurance brokers. Now it
calculates the insurance payouts to customers.
Staples: They created a 'smart' ordering button which
takes voice command like "order more red pens“ and
place an order. It reduces the ordering time and
complications of online ordering.

33. Demo links
Visual recognition: https://www.ibm.com/watson/services/visual-recognition/demo/
Language translator: https://language-translator-demo.ng.bluemix.net/
Natural-Language-Classifier : https://natural-language-classifier-demo.ng.bluemix.net/
Speech to text: https://speech-to-text-demo.ng.bluemix.net/
Text to speech:https://text-to-speech-demo.ng.bluemix.net/
Discovery Service: https://discovery-news-demo.ng.bluemix.net/
Natural Language Understanding: https://natural-language-understanding-demo.ng.bluemix.net/
Personality insights: https://personality-insights-demo.ng.bluemix.net/
Tone analyzer :https://customer-engagement-demo.ng.bluemix.net/
Tone analyzer social :https://tone-analyzer-demo.ng.bluemix.net/
AI Open Scale: https://www.ibm.com/cloud/garage/demo/try-ai-openscale
References and credits
IBM Cloud: https://console.bluemix.net
The AI behind Watson :http://www.aaai.org/Magazine/Watson/watson.php

34. Thank you
@p_satyajit
https://www.linkedin.com/in/satyajitpanda/
Satyajit Panda
Chief architect, New age Media and Education