What is a "chatbot" and how does it work? In this workshop, we explored how to build a chatbot for the conversational interface, without having to write any code.
Business process outsourcing (BPO) is a subset of outsourcing that involves the contracting of the operations and responsibilities of specific business functions (or processes) to a third-party service provider. Originally, this was associated with manufacturing firms, such as Coca Cola that outsourced large segments of its supply chain. In the contemporary context, it is primarily used to refer to the outsourcing of business processing services to an outside firm, replacing in-house services with labour from an outside firm.
This Document is helpful in creating UML diagrams
Business process outsourcing (BPO) is a subset of outsourcing that involves the contracting of the operations and responsibilities of specific business functions (or processes) to a third-party service provider. Originally, this was associated with manufacturing firms, such as Coca Cola that outsourced large segments of its supply chain. In the contemporary context, it is primarily used to refer to the outsourcing of business processing services to an outside firm, replacing in-house services with labour from an outside firm.
This Document is helpful in creating UML diagrams
The slide was prepared on the purpose of presentation of our project face detection highlighting the basics of theory used and project details like goal, approach. Hope it's helpful.
Attendance Management System using Face RecognitionNanditaDutta4
The project ppt presentation is made for the academic session for the completion of the work from Bharati Vidyapeeth Deemed University(IMED) MCA department
Presented by Mr. Dinesh KS
Software Developer, Livares Technologies
Introduction
Object detection is a computer technology related to computer vision and image processing that
deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or
cars) in digital images and videos.
Face detection is a computer technology being used in a variety of applications that identifies
human faces in digital images.
The artificial intelligence solutions are the greatest invention of mankind that has taken the technology to a whole new level. Artificial intelligence is used by the IT sector in their systems, software, applications, websites etc.
Check it Out – https://bit.ly/2Cgmd7p
Sept 2010 Talks @ The Science Gallery
Speaker: Alan Kennedy
(Level: Intermediate/Advanced)
Abstract:
Cloud computing is a growing force in business, with the principal benefit being reduction of the costs of providing business functionality to users. Dynamic languages are very popular on cloud computing platforms, offering rapid development and deployment cycles, which further reduce costs and decrease time to market. Python is one of the most popular dynamic languages for cloud computing, as evidenced by the support it garners from large cloud computing players such as Google and Microsoft. The purpose of this talk is to give you an overview what cloud computing options exist if you want to use cpython, jython or ironpython for your next cloud computing project, be it on Google AppEngine, Microsoft Azure, or other platforms.
More info: http://www.python.ie/meetup/2010/sept_2010_talks__the_science_gallery/
CDS is the criminal face identification by capsule neural network.
Solving the common problems in image recognition such as illumination problem, scale variability, and to fight against a most common problem like pose problem, we are introducing Face Reconstruction System.
Do you use the internet? Do you use websites with customer support live chat? If you answered yes to any of the questions I asked above, then chances are you have the first-hand experience of interacting with a chatbot. With digital interaction reaching new heights, chatbots have become quite the new buzz. And over the time chatbots have evolved too. When chatbots were conceived, they sounded entirely robotic, but today with the advancements in machine learning, these chatbots have improved in analysing the legions of data provided to them. They almost feel human when talking to.
The slide was prepared on the purpose of presentation of our project face detection highlighting the basics of theory used and project details like goal, approach. Hope it's helpful.
Attendance Management System using Face RecognitionNanditaDutta4
The project ppt presentation is made for the academic session for the completion of the work from Bharati Vidyapeeth Deemed University(IMED) MCA department
Presented by Mr. Dinesh KS
Software Developer, Livares Technologies
Introduction
Object detection is a computer technology related to computer vision and image processing that
deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or
cars) in digital images and videos.
Face detection is a computer technology being used in a variety of applications that identifies
human faces in digital images.
The artificial intelligence solutions are the greatest invention of mankind that has taken the technology to a whole new level. Artificial intelligence is used by the IT sector in their systems, software, applications, websites etc.
Check it Out – https://bit.ly/2Cgmd7p
Sept 2010 Talks @ The Science Gallery
Speaker: Alan Kennedy
(Level: Intermediate/Advanced)
Abstract:
Cloud computing is a growing force in business, with the principal benefit being reduction of the costs of providing business functionality to users. Dynamic languages are very popular on cloud computing platforms, offering rapid development and deployment cycles, which further reduce costs and decrease time to market. Python is one of the most popular dynamic languages for cloud computing, as evidenced by the support it garners from large cloud computing players such as Google and Microsoft. The purpose of this talk is to give you an overview what cloud computing options exist if you want to use cpython, jython or ironpython for your next cloud computing project, be it on Google AppEngine, Microsoft Azure, or other platforms.
More info: http://www.python.ie/meetup/2010/sept_2010_talks__the_science_gallery/
CDS is the criminal face identification by capsule neural network.
Solving the common problems in image recognition such as illumination problem, scale variability, and to fight against a most common problem like pose problem, we are introducing Face Reconstruction System.
Do you use the internet? Do you use websites with customer support live chat? If you answered yes to any of the questions I asked above, then chances are you have the first-hand experience of interacting with a chatbot. With digital interaction reaching new heights, chatbots have become quite the new buzz. And over the time chatbots have evolved too. When chatbots were conceived, they sounded entirely robotic, but today with the advancements in machine learning, these chatbots have improved in analysing the legions of data provided to them. They almost feel human when talking to.
Explore the world of AI-powered chatbots and their powerful benefits. Streamline your business communication with cutting-edge technology for enhanced customer satisfaction. Read now! https://www.syscraftonline.com/blog/what-are-ai-powered-chatbots-and-their-benefits
UXPA2019 Not Your Average Chatbot: Using Cognitive Intercept to Improve Infor...UXPA International
This presentation from UXPA 2019 will review cognitive intercept as pertains to search, and how it extends to an additional domain (live agent chat). Evidence that it helps users and lowers help desk volumes will be discussed.
Chatbot Service Providers | Chatbot Solution Providers | Ai Chatbot PlatformsElfo Digital Solutions
Elfo offers you 24/7 chat robot service platform. You can deploy your existing web application through our Chatbot Builder and get more leads and sales. We offer a free 14-day trial hosting on our platform to ensure the configuration, installation, and proper operation of your chatbot. To know more just visit this link: https://www.elfo.com/bot
chat bots are the future of communication.pptxJIMSVKII
Gaurav Gogia student of
BVJMM 2nd Semester of #JIMSVKII has shared about the chat bots are the future of communication.
For More Query Call us on 09990474829, 011 61199191
Visit us at https://www.jimssouthdelhi.com/
Follow us on:
Facebook: https://www.facebook.com/JIMSVASANTKUNJII/
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Blog: https://jimssouthdelhi.com/blog/
Linked In: https://www.linkedin.com/in/jims-vasant-kunj-38785a85/
Artificial Intelligence Improving the Candidate Experience AppVault
Curious where and how Artificial Intelligence (AI) plays in the Candidate Experience? Look no further than chat bots and automated recruitment marketing.
Check my presentation about challenges we're facing with voice and how to successfully getting started. Also viewable online: https://pasteapp.com/p/ANdFfwH2si9
How to Build a Chatbot with Tom Martin, Founder of LawDroidThomas G. Martin
Thinking a chatbot can help your clients? Learn how the basics to building your own chatbot that can screen clients or complete documents, all while syncing with your Clio account. Tom Martin, creator of LawDroid corporate filings, shares his expertise in building your own chatbot in this hands-on session.
Conversation UIs & Chatbots an introductionMarion Mulder
What are conversational User Interfaces (chatbots, voice assistants), how do they relate to AI, AR, and IoT. What can they be used for. Where are they today and where could this potentially go in the (near) future. And how and where do you start.
This presentation was used for a guest lecture to 3rd year students Media, Information and Communication (Creative Business) of the Hogeschool van Amsterdam (HvA) 26 september 2018.
Images used in the presentation have source reference where available
AI chatbot are frequently called menial helpers. Chatbots are normal in showcasing, presently taking spots in numerous angles to make speedy and shrewd help.
Artificial Intelligence Virtual Assistants & ChatbotsaNumak & Company
Artificial Intelligence transforms different interfaces into interactive systems that can be interacted with using Natural Language Processing technology. Thus, businesses can offer voice-integrated smart self-service solutions to their customers with Natural Dialogue Solutions, which can be positioned in different areas ranging from IVR systems to virtual assistants, from chatbots to smart systems.
A chatbot is an Artificial Intelligence (AI) program that simulates human conversation by interacting with people via text or speech. Chatbots use Natural Language Processing (NLP) and machine learning algorithms to comprehend user input and deliver pertinent responses. Chatbots can be integrated into various platforms, including messaging programs, websites, and mobile applications, to provide immediate responses to user queries, automate tedious processes, and increase user engagement.
Similar to Build a Chatbot with IBM Watson - No Coding Required (20)
How Will the Rise of AI and Robotics Change the Way We Work and Live Charlotte Han
In the face of a possible robot apocalypse where many of us could be replaced by AI and robots that don’t have to be perfect but merely better than us, maybe not all hopes for humans are lost. Humans may still be able to thrive and live a fulfilled life, as long as we have the agile principles in mind.
The machines are coming! RankBrain is an AI Google uses to serve better search results based on search intent. How is AI going to change SEO as we know it, and what can marketers do to stay ahead?
Beyond Wordpress - How to Launch a Website in One DayCharlotte Han
Weebly, Squarespace, Jimdo and Wix and some great choices other than Wordpress that will help you quickly build a site and easily manage yourself. I'll compare them side by side with the pros and cons to help you make smart decisions, whether you're launching a blog, ecommerce store or a portfolio site.
Mobile Commerce in Messaging Apps - WeChat: What One Billion People Know and ...Charlotte Han
Overview of WeChat that is more than just a messaging app. It's a huge ecosystem that currently has 1.1 billion users and 60 million active users. 60% of its users log on 10x a day. How are brands utilizing WeChat in campaigns?
Establish Your Digital Marketing Strategy in 5 Simple StepsCharlotte Han
In order to implement effective marketing plans and campaigns, we need to set a realistic goal, find our target audience, listen for valuable insight, and provide the best help. To bring it together, measuring, monitoring and optimizing are key.
Social media etiquette, social media campaigns, social media do's and don'ts, using social media for non-profit, how to share on social media, why do things go viral, #social, #socialmedia #socialmarketing
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
2. Hello! I’m Charlotte Han.
● I processes data and computes digital
strategies for a living
● Taiwan -> U.S. -> Germany
● Passionate about helping people
understand how technologies can
advance human lives
● Currently working as “Deep Learning
Marketing Manager” at NVIDIA
@sunsiren
3. Agenda
● What Is Artificial Intelligence, Machine Learning and Deep
Learning
● AI in Our Personal Lives and in the Workplace
● Underlying technology of chatbots
● Let’s build a chatbot for a flower shop using IBM Watson
4. Source: Gartner, “Architecting the On-Demand Digital Business”; Drue Reeves, Kyle Hilgendorf, Kirk Knoernschild, August 16, 2016
By 2020, the average person will have
more conversations with bots than with their spouse.
Source: Gartner’s Top 10 Strategic Predictions for 2017 and Beyond
7. Artificial Intelligence Is
Sweeping Across Industries
MEDICINE
MEDIA &
ENTERTAINMENT
SECURITY & DEFENSE
AUTONOMOUS
MACHINES
Cancer cell detection
Diabetic grading
Drug discovery
Pedestrian detection
Lane tracking
Recognize traffic signs
Face recognition
Video surveillance
Cyber security
Video captioning
Content based search
Real time translation
Image/Video classification
Speech recognition
Natural language processing
INTERNET SERVICES
8. Source: Gartner, “Architecting the On-Demand Digital Business”; Drue Reeves, Kyle Hilgendorf, Kirk Knoernschild, August 16, 2016
9. By Better Analyzing Data, Companies Can Have:
Improved
Operations
Increased
Productivity
Customers
Satisfaction
10. Structured Data:
Unstructure
d Data
80% of Business-
Related Data is
Excel, CRM, HR
systems,
Financial systems, SQL
Emails, images,
requisitions, purchase
orders, sensor data,
server or web logs, audio
files, video files, social
media data, text files and
documents
13. This Is Why There Are Free
Communication Apps
• Treasure trove of different types of
human communications
• They can use machine learning to see
patterns in how humans use their
natural language
21. Faster Processing, Happier Customers
● Faster claims
processing
● Increased
customer
satisfaction
● Maintain high
levels of customer
service
● Cost savings from
automation
22. AI Chatbot That Speaks Emoji
● Chatbots and virtual
assistants have risen in
popularity in banking and
other industries because
advancements in AI have
made them better at
interacting and
interpreting human
language.
● The banking industry can
offer advice on a larger
scale and with better
impact by using AI
chatbots that can learn
about user habits.
23. AI Tool Boosts
Customer Service
KLM’s 350+ social media
service agents handle 15K
requests/week. To support
the volume of incoming
messages, KLM uses GPU-
accelerated deep learning to
predict the best response.
Service agents review and
either approve or personalize
each response. The resulting
time savings allows agents to
focus on customers with more
pressing
needs and handle more
questions
while maintaining high
levels of customer
satisfaction.
24. Roll up Your Sleeves!
Chatbot 101 with IBM Watson Assistant
Source: https://courses.competencies.ibm.com/courses/course-v1:CognitiveClass+CB0103EN+v1/
25. Step One
Sign up for IBM Cloud:
https://cloud.ibm.com/registration
29. Intents
An intent is the goal of the
purpose of the user’s input.
Adding examples to intents
helps your virtual
assistants understand
different ways in which
people would say them.
Start with “#”
30. Entities
An entity is a portion of
user’s input you can use to
provide a different
response to a particular
intent. Adding values and
synonyms to entities helps
your virtual assistants
learn and understand
important details that your
users mention.
Start with “@”
31. Dialog
Creating a dialog defines
how your bot will respond
to what the user is asking.
Dialogues in Watson are
defined through nodes.
Each node has a name, a
condition and one or more
responses.
Execution
Order
42. Distinguish Intents with Entities
● I want flower recommendations
● Flower suggestions for boyfriend (@relationship)
● Recommend flowers for a birthday (@occasion)
49. What’s in the Welcome Node?
Name of the node
Condition
Response Block
50. What’s in the “Anything Else” Node?
If the conditions in the blocks above this one
were false / not met, this node will be
executed.
Randomize order
to make it more
“human”
51. Test it!
- Enter something irrelevant, such as “What!?”
- What is the intent or entity identified?
- What is Watson’s response?
Since the condition in “welcome” was not met, Watson
responded with Anything Else block. The order is
randomized.
52. Back to Welcome Node. Change Response
Hello. My name is Florence and I’m a chatbot. How can I help you?
You can ask me about flower suggestions or delivery info.
Personality
Setting up expectations to
get users back on track.
64. Test it!
- flower suggestions for my boyfriend
Did Watson give you a suggestion?
65. To Be Continued...
Follow the rest of this course about handling complex dialogue flows and deploying
the chatbot to WordPress here:
https://courses.competencies.ibm.com/courses/course-
v1:CognitiveClass+CB0103EN+v1/
66. If you want to learn more about AI:
Meetup.com/what-is-artificial-intelligence
It’s an honor to be here with you. Thank you.
I currently work at NVIDIA as “Deep Learning Marketing Manager”; still trying to figure out what it means. I’m learning deep.
Because of NVIDIA I get to see first hand how AI is changing the world. So fast. There is so much amazing research being published every year. It blows my mind.
I know you’re here for the same reason: you want to see the future. So let’s get on the journey together.
By 2020, the average person will have more conversations with bots than with their spouse. With the rise of Artificial Intelligence (AI) and conversational user interfaces, we are increasingly likely to interact with a bot (and not know it) than ever before. The digital experience has become addictive by entering our lives through smartphones, tablets, virtual personal assistants (VPAs) or the entertainment systems in our homes and cars.
I totally believe that because I don’t even have a spouse! Of course I’ll be talking more with the bots. It’s not like we’re talking to R2D2 or C-3PO, though.
First, let’s start with some definitions…
AI is a broad field of study focused on using computers to do things that require human-level intelligence. It’s been around since the 50’s, playing games like tic-tac-toe and checkers, and inspiring scary sci-fi movies. But it was limited in practical applications…
ML is an approach to AI that uses statistics techniques to construct a model from observed data. It generally relies on human-defined classifiers or “feature extractors” that can be as simple as a linear regression, or the slightly more complicated “Bag of Words” analysis technique that made email SPAM filters possible.
This was really handy in the late 1980’s when lots of email started showing up in your inbox
But then we invented smartphones, webcams, social media services, and all kinds of sensors that generate huge mountains of data and the new challenge of understanding and extracting insights from all this “big data”.
DL is a ML technique that automates the creation of feature extractors using large amounts of data to train complex “deep neural networks”
DNNs are capable of achieving human-level accuracy for many tasks, but require tremendous computational power to train
Several years ago, researchers started applying DNNs in a variety of areas and reporting amazing results…
==============
Ref. https://en.wikipedia.org/wiki/Naive_Bayes_spam_filtering
I was going to try to persuade you that AI is everywhere, touching our lives, but actually I’m going to try something different: raise your hand if you believe that AI is not touching your life? It must be a tough life. And you may be Amish.
Typical AI tasks include classification, pattern detection and prediction. It turns out that AI effective across many domains, and it’s transforming the way computers achieve perceptual tasks such as computer vision, pattern detection, speech recognition and behavior prediction. Some people, including Bloomberg and the World Economic Forum, have referred to it as the 4th industrial revolution. And Andrew Ng (a widely-respected Stanford University professor, founder of the Google Brain project, and co-founder of the Coursera online education platform) believes that this new deep learning approach to AI is “the new electricity.” and “Just as 100 years ago electricity transformed industry after industry, AI will now do the same.”
References:
https://www.bloomberg.com/news/articles/2016-05-20/forward-thinking-robots-and-ai-spur-the-fourth-industrial-revolution
https://www.weforum.org/agenda/2016/01/the-fourth-industrial-revolution-what-it-means-and-how-to-respond/
Ng on AI as the new electricity: http://www.fast.ai/2016/10/11/fortune/
A few examples:
Facebook’s “DeepFace” feature creates a 3D model of your face from online photos, adjusts for lighting and facial expressions, and identifies you in photos with 97% accuracy – all using deep learning. You may have experienced this when Facebook automatically alerts you that a new picture of you has been posted and gives you the option to blur out your image.
References:
http://www.inquisitr.com/1825367/facebook-deepface-ai-learning-your-face-in-every-uploaded-photo
http://news.sciencemag.org/social-sciences/2015/02/facebook-will-soon-be-able-id-you-any-photo
Microsoft’s Skype Translator performs instant translation of conversations to and from over 50 languages. If you haven’t tried this yet, it’s a really amazing way to connect and communicate with people across language barriers.
References:
http://www.technologyreview.com/news/534101/something-lost-in-skype-translation/
http://www.wired.com/2014/05/microsoft-skype-translate/
Other examples include medical researchers detecting genes associated with autism spectrum disorder, neuroscientists detecting and suppressing the brainwave patterns responsible for epileptic seizures, and others using deep learning to identify skin cancers, classify lung sounds, and accelerate computational drug design, saving millions in research.
Imagine a day in the not-too-distant future when a personal healthcare device, like a mirror in your bathroom, puts this all together and can automatically notify you when it detects that you may have early-stage skin cancer, so you can consult with your doctor and get life-saving treatment.
You can explore hundreds of deep learning use cases my team has collected at https://news.developer.nvidia.com
[next]
===========================
Story: Understanding Video
Clarifai offers a service that rapidly analyzes images and video clips to recognize 10,000 different objects or types of scenes
This capability can be used for extremely targeted advertising, for example:
Showing a Starbucks ad whenever coffee appears in a video
Rapidly scanning security footage
Searching through your personal video archive for your child’s first steps
References:
http://www.technologyreview.com/news/534631/a-startups-neural-network-can-understand-video/
Most enterprise businesses are on the path to AI already even though they might not know it. Companies are digitizing everything: supply chain, HR, finance, marketing, sales….
Digital creates data.
Data requires insight.
AI Deep Learning provides the tools to make the most use of that data.
It’s already taking off.
By 2020, 20% of companies will dedicate workers to monitor and guide neural networks.
Spending on AI Technologies by companies is expected to grow to $47b in 2020 from a projected 8 billion in 2016, according to IDC.
According to researcher Gartner, AI bots will power 85% of all customer service interactions by the year 2020 .
In a research report to its investors, Bank of America argued that the rise of AI will lead to cost reduction and new forms of growth that could amount to $14-$33 trillion annually, in what it calls "creative disruption impact," and that's just the tip of the iceberg in some expert's view.
“There are an estimated 3,000 AI startups worldwide, and many of them are building on Nvidia’s platform. They’re using Nvidia’s GPUs to put AI into apps for trading stocks, shopping online and navigating drones.” http://www.nextbigfuture.com/2016/12/nvidia-is-new-intel-and-its-chips-are.htm
Unstructured data, especially text, images and videos contain a wealth of information. However, due to the inherent complexity in processing and analyzing this data, people often refrain from spending extra time and effort in venturing out from structured datasets to analyze these unstructured sources of data, which can be a potential gold mine.
Natural language processing (NLP) is a subfield of computer science, information engineering, and artificial intelligence concerned with the interactions between computers and human (natural) languages, in particular how to program computers to process and analyze large amounts of natural language data.
Challenges in natural language processing frequently involve speech recognition, natural language understanding, and natural language generation.
An automated online assistant providing customer service on a web page, an example of an application where natural language processing is a major component.[1]
- Wikipedia
The ultimate goal of NLP is to the fill the gap how the people communicate (natural language) and what the computer understands (machine language).
Although, some people talk like robots. “We need to ETL the data from the warehouse so we can move it into the Hadoop Cluster!”.
AI teaches systems to do intelligent things
Machine Learning teaches systems to do intelligent things that can learn from experience
NLP teaches systems to be intelligent, learn from experience and can analyze, understand and generate human language.
Data scientists spend 90% of their time getting and cleaning data. Only when the data is prepped can they get to work with identifying patterns and making predictions. They can’t go straight into predicting the future without understanding the data. Your team has to better understand the past to be able to predict the future.
Knowledge Base - It contains the database of information that is used to equip chatbots with the information needed to respond to queries of customers request.
Data Store - It contains interaction history of chatbot with users.
NLP Layer - It translates users queries (free form) into information that can be used for appropriate responses.
Application Layer - It is the application interface that is used to interact with the user.
Chatbots learn each time they make interaction with the user trying to match the user queries with the information in the knowledge base using Machine Learning.
BNP Paribas Cardif
Industry(ies): FSI
Data: structured and un-structured
Products: 2 TITAN X for POC
Summary
The insurance industry hasn’t changed much in that it still relies largely on evidence-based, non-standardized documents (paper, scans, photos, etc) in its contract management processes. Processing this type of documentation is often manual, tedious, and time consuming for both the insurer and the insured.
‘Cardif Forward’ is BNP Paribas Cardif’s innovative digitization plan with AI being a key element of the plan. Thanks to artificial intelligence, the insurer will be able to automatically analyze documents and make monthly loan repayments without waiting for all supporting documents. This will allow a third of clients to receive immediate approval.
Problem
When facing unexpected events, customers expect their insurer to support them as quickly as possible. However, claims management may require different levels of checks and validations before a claim can be approved and a payment can be made. With the new practices and behaviors generated by the digital economy, this process needs adaptation thanks to data science to meet the new needs and expectations of customers.
The insurance industry still relies largely on evidence-based, non-standardized documents (paper, scans, photos, etc) in its management processes. E.g. medical reports for credit insurance; RIB to control operations; death certificate or work stoppage to validate a claim.
Solution
‘Cardif Forward’ is BNP Paribas Cardif’s development plan for 2017-2020 and marks the 3rd phase in the digitization of the company.
Cardif wants to remain a leading-edge company in term of customer experience and is using AI and DL to develop internal expertise to automatically recognize and process documents digitized by the insured.
Result(s)
The receipt, validation and processing of the contents of these documents are often manual and therefore long and tedious for the insured (numerous round trips) and costly for the company. The AI solution will save money and reduce the complexity of our contract management
Impact
Expected:
-Faster claims processing
-Increased customer satisfaction
-Maintain high levels of customer service
-Cost savings from automation
About the Customer
Protecting people and their property at every stage of their lives. As a global specialist in personal insurance, BNP Paribas Cardif serves 90 million clients in 36 countries across Europe, Asia and Latin America.
More Information
https://twitter.com/bnpp_cardif/status/847354298891517953?lang=en
https://www.forbes.com/sites/blakemorgan/2017/07/25/how-artificial-intelligence-will-impact-the-insurance-industry/#6b4bb5226531
https://www.theguardian.com/sustainable-business/2017/jan/28/insurance-company-lemonde-claims
Capital One
Industry(ies): Financial Services
Data: Text
Products: GPUs on AWS
Summary
Fintech analysts, Juniper Research, estimates the number of mobile banking users will reach 2b by the year 2021. So, it’s no surprise to see the rising popularity of Chatbots in the finance industry. Through convenience and ease-of-use, Chatbots optimize digital services at scale. Chatbots are convenient and easy for customers to use. And, with the ability to automate operations, to reach more customers chatbots are streamlining and optimizing digital services.
Capital One is piloting an SMS text-based intelligent assistant named Eno. Eno uses GPU-powered deep learning to respond to natural language text messages from customers inquiring about their accounts. Customers text Eno to track their balance, recent charges, or to pay their bill. Eno takes mobile banking to the next level, which is just a text message away.
Problem
Solution
In March 2017, Capital One launched a pilot of Eno (“One” spelled backwards), an SMS text-based intelligent assistant. Eno uses artificial intelligence to respond to natural language text messages and emojis from users about their money.
Result(s)
With Eno, customers can stay on top or their Capital One credit card and bank accounts, through text or emoji. You can text Eno things like, “What’s my balance?” or “How much credit do I have?” or “What are my recent charges?” and Eno will respond instantly with the information. Customers can also pay their credit card bill by simply texting “Eno, pay my bill.”
In a bid to make the experience more human, Eno has also been programmed to recognize certain "emojis”. For example, users can prompt Eno to show them their account balance by sending the "bag of money" emoji or they can confirm a payment through the "thumbs up" emoji.
Impact
-Eno helps customers stay on top of their accounts, anywhere, anytime.
-Right now, Eno is available to a small pilot of customers – Capital One is keeping a waitlist for customer who are interested in getting in the next wave.
-At this time, Eno cannot transfer funds. Capital One is working on developing new capabilities, and transferring money is one of them – but it’s not in the starting lineup of features.
-Overall:
---chatbots and virtual assistants have risen in popularity in banking and other industries because advancements in AI have made them better at interacting and interpreting human language.
---the banking industry can offer advice on a larger scale and with better impact by using AI chatbots that can learn about user habits.
About the Customer
Capital One Financial Corporation is a bank holding company specializing in credit cards, home loans, auto loans, banking and savings products headquartered in McLean, CA. Capital One is the eighth-largest commercial bank in the United States when ranked by assets and deposits and is ranked 9th on the list of largest banks in the United States by total assets. The bank has 755 branches and 2,000 ATMs. It is ranked #100 on the Fortune 500 #17 on Fortune's 100 Best Companies to work for list, and conducts business in the United States, Canada, and the United Kingdom. The company helped pioneer the mass marketing of credit cards in the 1990s, and it is one of the largest customers of the United States Postal Service due to its direct mail credit card solicitations. In 2015, it was the 5th largest credit card issuer by purchase volume, after American Express, JP Morgan Chase, Bank of America, and Citigroup.
More Information
https://www.capitalone.com/applications/eno/
https://www.abe.ai/blog/10-big-banks-using-chatbots-boost-business/
https://www.juniperresearch.com/press/press-releases/mobile-banking-users-to-reach-2-billion-by-2020
Oct. 2016: “New research from leading Fintech analysts, Juniper Research, finds that over 2bn mobile users will have used their devices for banking purposes by the end of 2021, compared to 1.2bn this year (2016) globally. Growth in mobile banking is being driven by consumer adoption of banking apps the changing way consumers manage their finances.”
DIGITALGENIUS – KLM
Industry: Transportation
Data: KLM’s historical data
Products: NVIDIA TITAN X GPUs for training. NVIDIA GPUs on AWS cloud with CUDA for production workloads and inference.
SUMMARY
KLM’s 350 social media service agents engage in 15K conversations each week on channels like Facebook Messenger, Twitter and Whatsapp, 24/7. To support the overwhelming volume of messages, KLM uses GPU-accelerated deep learning from DigitalGenius to predict the best response to an incoming message and shows it to a contact center agent for approval or personalization before sending it to the customer. The resulting time savings for KLM service agents means they can focus on customers with more pressing needs and handle a greater volume of questions while still maintaining a high degree of customer satisfaction.
Challenge
-KLM has >22 million social-media followers who engage with the airlines on various platforms >100,000 times a week.
-KLM’s team of 350 social media service agents engage in 15,000 conversations a week across all its social platforms, offering 24/7 service in 10 languages.
Solution
To contend with the overwhelming volume of messages, KLM turned to DigitalGenius and AI. DigitalGenius uses NVIDIA TITAN X GPUs DigitalGenius uses NVIDIA TITAN X GPUs to train its deep learning neural networks on the company’s historical data (>60,000 KLM questions and answers). Production workloads for enterprise customers run on NVIDIA GPUs in the AWS cloud, with the CUDA parallel computing platform providing acceleration.
When a new message comes in via a digital channel such as email, chat, social media or text, DigitalGenius’ deep learning model takes a couple of actions:
------It predicts and auto-fills metadata related to the incoming message.
------It predicts the best response to the incoming message and shows it to the contact center agent for approval or personalization before sending it to the customer
Result
Huge time savings for customer service agents, who can instead focus on customers with more pressing or complicated needs.
Impact
By applying AI, KLM can handle a greater volume of questions while still maintaining its personal approach and speed
The rapid increase in the collection of historical customer data and advances in NVIDIA hardware have combined to make AI-powered customer service practical for the first time.