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Designing Customer Centered AI experiences - Dialogkonferansen 2018Samantha Starmer
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Sudha Jamthe shares her vision for a futuristic connected world which she calls as "Driverless World" where the roads are smart, homes and cars have voice assistants and healthcare is predictive and preventive. She guides us on what is AI and how the convergence of AI and AV leads us to the Driverless World.
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Alternative download link: https://dl.dropboxusercontent.com/u/6757026/slideShare/creativeAI.pdf
Microsoft provides several technologies in and around SQL Server which can be used for casual to serious data science. This presentation provides an authoritative overview of five major options: SQL Server Analysis Services, Excel Add-in for SSAS, Semantic Search, Microsoft Azure Machine Learning, and F#. Also included are tips on working with Python and R. These technologies have been used by the presenter in various companies and industries. This deck includes a sneak preview for SQL Server 2016.
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– Insight: Understand AI’s impact on the insight industry
– Foresight: Learn how to transform yourself and your company with AI
Listen to the full presentation at NewMR.org/Play-Again
Machine Learning and AI: An Intuitive Introduction - CFA Institute MasterclassQuantUniversity
Learn how artificial intelligence (AI) and machine learning are revolutionizing financial services — this course will introduce key concepts and illustrate the role of machine learning, data science techniques, and AI through examples and case studies from the investment industry. The presentation uses simple mathematics and basic statistics to provide an intuitive understanding of machine learning, as used by financial firms, to augment traditional investment decision making.
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The recent release of the ChatGPT “chatbot” has reinvigorated interest in artificial intelligence. This should bring up the question, how can you invest in AI?
https://youtu.be/70dLgVjlJH8
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Marketing automation platforms save time, improve efficiency and increase productivity. They give companies an unprecedented ability to understand buyers, identify opportunities, track campaign performance and link marketing activities to business outcomes.
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AI 101 for km washington november 2018 km world workshop
1. AI 101 for KM
KM World Workshop
Gordon Vala-Webb
November 2018
Washington, D.C.
Gordon@BuildingSmarterOrganizations.com
@BuildSmarterOrg www.BuildingSmarterOrganizations.com
2. What I think KM should be . . .
• Predictions & Bets
• Flows of info, ideas
decisions
• Designing / Nurturing
@BuildSmarterOrg www.BuildingSmarterOrganizations.com 2
3. Why does AI
matter?
Workforce
Healthcare
Fourth industrial
revolution
@BuildSmarterorg www.BuildingSmarterOrganizations.com 3
World Economic Forum
Mapping Global Transformation
https://www.weforum.org/about/transformation-maps
3
4. Annual value estimated $3.5 – $6.8 trillion
@BuildSmarterorg www.BuildingSmarterOrganizations.com 4
NOTES FROM THE AI FRONTIER INSIGHTS FROM HUNDREDS OF USE CASES McKinsey Global Institute
https://www.mckinsey.com/~/media/mckinsey/featured%20insights/artificial%20intelligence/notes%20from%20the
%20ai%20frontier%20applications%20and%20value%20of%20deep%20learning/mgi_notes-from-ai-
frontier_discussion-paper.ashx
5. Is AI magic?
@BuildSmarterorg www.BuildingSmarterOrganizations.com
“Any sufficiently advanced technology is indistinguishable from magic.”
Arthur C. Clarke
5
6. Is it a flying car?
@BuildSmarterorg www.BuildingSmarterOrganizations.com 6
By Eslivb [CC BY-SA 4.0 (https://creativecommons.org/licenses/by-
sa/4.0)] , from Wikimedia Commons
By Thesupermat - Own work, CC BY-SA 3.0,
https://commons.wikimedia.org/w/index.php?curid=23885520
Or is it just a car?
7. Where is Machine Learning on the Gartner Hype Cycle?
@BuildSmarterorg www.BuildingSmarterOrganizations.com 7
https://www.gartner.com/en/research/methodologies/gartner-hype-cycle
?
?
?
8. What is Machine Learning?
Creating algorithms
that can recognize patterns in large,
evolving data sets, and
drawing conclusions from past
experience by using that data
@BuildSmarterorg www.BuildingSmarterOrganizations.com 8
Machine Learning and Predictive Systems; World Economic Forum
https://toplink.weforum.org/knowledge/insight/a1Gb0000000pTDREA2/explore/dimension/a1Gb00000017L8jEAE/summary
10. Components of custom-built AI solution
•Technologies
•Tools /methodologies
•Business knowledge and experience
•AI expertise
•Focus on specific business opportunity
@BuildSmarterorg www.BuildingSmarterOrganizations.com 10
11. What is Machine Learning?
Creating algorithms
that can recognize patterns in large,
evolving data sets, and
drawing conclusions from past
experience by using that data
@BuildSmarterorg www.BuildingSmarterOrganizations.com 11
Machine Learning and Predictive Systems; World Economic Forum
https://toplink.weforum.org/knowledge/insight/a1Gb0000000pTDREA2/explore/dimension/a1Gb00000017L8jEAE/summary
12. IF this THEN that ELSE: Employee or Contactor?
@BuildSmarterorg www.BuildingSmarterOrganizations.com 12
Will the service be provided
from home?
Or will the services be provided in a determined
place (offices or facilities of the hiring company)?
Will the service be subject to a work shift or schedule?
If yes – is employee If yes – is employee
If no - is independent contractor If no:
Will the person be using uniform of the hiring
company?
If yes – is employee
If no:
Will the person be using the tools of the hiring
company?
If yes – is employee
14. What is Machine Learning?
Creating algorithms
that can recognize patterns in large,
evolving data sets, and
drawing conclusions from past
experience by using that data
@BuildSmarterorg www.BuildingSmarterOrganizations.com 14
Machine Learning and Predictive Systems; World Economic Forum
https://toplink.weforum.org/knowledge/insight/a1Gb0000000pTDREA2/explore/dimension/a1Gb00000017L8jEAE/summary
15. “Recognize patterns in data sets”
@BuildSmarterorg www.BuildingSmarterOrganizations.com 15
Principal Component Analysis (PCA)/SVD
Least Squares and Polynomial Fitting
Constrained Linear Regression
K-Means Clustering
https://dzone.com/articles/ten-machine-learning-algorithms-you-should-know-to
17. Training systems:
False positives
and negatives
A face is a face – isn’t it?
@BuildSmarterorg
www.BuildingSmarterOrganizations.com
17@BuildSmarterorg www.BuildingSmarterOrganizations.com
18. Is a roc a rock?
@BuildSmarterorg www.BuildingSmarterOrganizations.com 18
By Charles Maurice Detmold (1883-1908) - http://boards.collectors-
society.com/ubbthreads.php?ubb=showflat&Number=4741639, Public Domain,
https://commons.wikimedia.org/w/index.php?curid=20210405
26. Caveat – is AI fair?
•US sentencing guidelines – COMPASS – racially biased
•Siri giving inadequate instructions to women’s health
services
•Natural language models that associate ‘woman’ with
‘receptionist’
•US law enforcement crime prediction - PredPol –
racially biased
•Google image search for “CEO” – gender biased
@BuildSmarterorg www.BuildingSmarterOrganizations.com 26
27. Some KM use cases
• Customized / personalized search
• K (customer) support “bots”
• Text analytics and NLP
• Life sciences – diagnoses and finding cures
• Cybersecurity – attacks and effective responses
@BuildSmarterorg www.BuildingSmarterOrganizations.com 27
28. Customized / personalized search – e.g. Attivio
“A system . . . begins to
understand how Bob is great
at handling queries about a
problem with mobile while
Mary excels at database
issues . . . a support ticket
can be directed to the right
person in real time based . .
. on an intake call or email.”
@BuildSmarterorg www.BuildingSmarterOrganizations.com
28
https://www.attivio.com/blog/post/solving-customer-issues-
intelligent-answers-and-insights
29. @BuildSmarterorg www.BuildingSmarterOrganizations.com 29
10 Best Chatbots [services] of 2018 Consumers Advocate https://www.consumersadvocate.org/chatbots/a/best-chatbots
Knowledge support – e.g. Dialogflowhttps://cloud.google.com/blog/products/gcp/dialogflow-enterprise-edition-is-now-generally-available
https://medium.com/swlh/how-to-build-a-chatbot-with-dialog-
flow-chapter-1-introduction-ab880c3428b5
https://hackernoon.com/how-to-train-your-robot-ai-for-
everyone-69b96ad943e5
30. Build a bot
https://landbot.io/
@BuildSmarterorg www.BuildingSmarterOrganizations.com 30
More advanced!
Language Understanding (LUIS)
https://www.luis.ai/welcome
• Domain
• Intents
• Utterances
• Entities
32. Data is
everything!
• Structured
• Time series
• Text
• Audio
• Video
• Image
@BuildSmarterorg www.BuildingSmarterOrganizations.com
https://www.mckinsey.com/~/media/mckinsey/featured%20insights/artifi
cial%20intelligence/notes%20from%20the%20ai%20frontier%20applicatio
ns%20and%20value%20of%20deep%20learning/mgi_notes-from-ai-
frontier_discussion-paper.ashx
NOTES FROM THE AI FRONTIER
INSIGHTS FROM HUNDREDS OF USE
CASES McKinsey Global Institute
32
33. Some key challenges
•Massive data sets
• Labelling training data
• Large and comprehensive enough
• Organizational change
•Explaining results
•Focused – not generalizable learning
•Potential bias
@BuildSmarterorg www.BuildingSmarterOrganizations.com 33
NOTES FROM THE AI FRONTIER INSIGHTS FROM HUNDREDS OF USE CASES McKinsey Global Institute
https://www.mckinsey.com/~/media/mckinsey/featured%20insights/artificial%20intelligence/notes%20from%20the%20ai%20frontier%20applications%20and%20value%20of%20deep%20learning/mgi_notes-from-ai-
frontier_discussion-paper.ashx
36. VUCA-Digital world
cc: frogthroat - https://www.flickr.com/photos/22980078@N04
“The Specter of an Accidental China-U.S. War”
“Sears tanked because the company
failed to shift to digital.”
36
37. Our organizations optimized for “old” world
@BuildSmarterOrg www.BuildingSmarterOrganizations.com 37
Old world
Grow big
Reliably repetitive
Control
VUCA – Digital world
Grow adaptable
Radically responsive
Predict
39. Uncertainty / Ambiguity / Complexity =
What is happening?
@BuildSmarterOrg www.BuildingSmarterOrganizations.com 39
Classifying Experimental Designs
Source: https://www.socialresearchmethods.net/kb/expclass.php
40. “Try or try not. There is only do not with no try."
Gordon Vala-Webb – Building Smarter Organizations 2016 Slide 40
“Try or try not.
There is only
do not with no
try."
40
@BuildSmarterorg www.BuildingSmarterOrganizations.com