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Artificial Intelligence
Will Artificial Intelligence live up to the hype?
June 15, 2017
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© Copyright Publicis.Sapient | Confidential
Agenda
1. Introduction
2. Current State of AI
3. Applications
4. Business Value for Sapient
5. Pros and Cons
6. Future Predictions
7. Conclusion
01 Introduction
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What is Artificial Intelligence?
“The science and engineering of making intelligent
machines, especially intelligent computer programs”
John McCarthy, father of Artificial Intelligence
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Artificial Intelligence At a Glance
• Artificial Neural Networks
• Machine Learning
• Planning
• Knowledge Representation
• Perception
• Natural Language Processing (NLP)
• Cognitive Systems
• Robotics
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Impact of AI
• Automated transportation – the beginning of self-driving cars era.
• Reduction number of dangerous jobs – outsourcing jobs, like welding, to robots.
• Virtual assistants – over half of the Apple device users use Siri on daily basis.
• Assisting in solving climate change – analysis of historic patterns and predictions.
• Healthcare – IBM Watson has been able to draw same conclusion as human in 99% of cases.
Furthermore IBM Watson found something new in 30% of cases.
• Simplified recruitment process
• Financial fraud detection – a number of financial services technologies are utilizing machine
learning to detect financial fraud.
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Artificial Intelligence Enablers
• Cloud Computing
• Big Data Processing & Distributed
Computing
• Open Source
• Customer Decision Driven Markets
• Advancements in High Performance
Computing
• Internet of Things (IoT)
02 Current State
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"This is not hype. It's real and sustained progress,
which accelerates research”
- Roman Yampolskiy
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• 2017 - CB Insights suggests that 200 AI-focused
companies have raised nearly $1.5 billion in
equity funding.
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• Khosala Ventures - the most active AI investor
• Backed over 15 companies during that time
frame, including Atomwise and MetaMind
• Google DeepMind
• Collaborating with the UK’s NHS in a handful
of projects.
• Spotify, Microsoft, Uber, Facebook, Apple, IBM
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Companies Investing in Artificial Intelligence
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“There is no approach at the moment that has any hope
of being flexible and performing multiple tasks or going
beyond the basic tasks that it’s programmed to do“
Andrei Barbu, MIT Center for Brains, Minds and Machines
03 Applications of AI
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© Copyright Publicis.Sapient | Confidential
Machine Learning
Supervised learning:
• The algorithm seeks a function from inputs to the
respective targets. Generally the algorithm is presented
with data that is already classified.
• User provides labels that algorithm takes into
consideration. At the end of algorithm, decision model
is obtained.
• Recommendation on Amazon, Netflix and Google are
based on the supervised learning techniques.
Unsupervised learning:
• The algorithm groups data how similar it is to each
other. The goal is to discover similar features, thus
clustering.
• Image processing is a common application of this,
specifically image denoising. Natural language
processing is common too.
04 Business Value for Sapient
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© Copyright Publicis.Sapient | Confidential
Collaborating Razorfish, DigitasLBi, SapientNitro and Sapient Consulting.
Luminoso:
• Partnership between Publicis.Sapient and Luminoso Technologies, Inc., a
leading global player in AI-based deep analytics
• Government Service Luminoso:
Redistribute Luminoso’s products into government agencies.
Help U.S. federal clients transform data into actionable insights
• Retail
Hyper-personalized Virtual Assistant for the retail industry, created
in partnership with SapientNitro.
• Automating manual processes
• Analysing unstructured data –analyse data to obtain patterns that
allow to obtain “hidden” information.
AI in Sapient
05 Pros and Cons
Pros
• Greater accuracy - somewhat elimination of “human” error
• Utilised to carry out repetitive tasks – increased automation that
will increase productivity.
• Continuously function without needing to rest - With AI, data
can be processed no matter how big the dataset might be.
• Cost efficient
• Fraud detection – financial institution are already utilizing
machine learning to recognize the behaviour of users and
detecting discrepancies.
Cons
• Cost incurred in the maintenance and repair – increased
dependency will lead to higher investment in technology.
• Lack of “human touch”
• Lack of creativity
• Automation of jobs – low skilled jobs will be eliminated, thus
increase in unemployment.
• Unexpected error – in recent past, there was a pound fall caused by
algorithmic trading.
• Lack of judgement call – In 2014, during the shooting in Sydney,
Uber algorithm rather than helping people get out of area, surged
the pricing.
06 Future Predictions
• AI tools for risk management and compliance
purposes.
• Machine learning to enhance their investment
research.
• Algorithmic trading.
• Reducing fraud and crime.
• Automated financial advisors.
• By 2025 half of investment assets will be traded via
AI according to Tractica market research report.
AI in Financial Services
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© Copyright Publicis.Sapient | Confidential
Industries at risk
• Taxi drivers – The effect of Uber, Lyft and likes.
• Factory Workers
• The first robot-only factory is being built in
China's Dongguan factory city.
• Journalists
• Doctors – diagnosis & analysis of patients.
• Lawyers – Smart, volume based analysis.
• Education – the rise of self learning and AI robots
specializing in education.
Every Industry will be affected by the Artificial Intelligence. Some reports
suggest up to 47% of all jobs will be taken over by AI!
28
© Copyright Publicis.Sapient | Confidential
Summary
• Development of IT infrastructure and the penetration
of smartphones and smart wearables main contributor
to growth.
• Elimination of low-skilled jobs, leading to increased
productivity.
• AI market is expected to grow from $1.25B to $36.82B
by 2025*.
• Massive opportunity for those betting big on AI,
especially for Sapient in FS sector.
• Manufacturing, media, transportation and advertising
industries as main drivers of growth.
* according to Statista 2017 report.
© Copyright Publicis.Sapient | Confidential

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Artificial Intelligence and Current State of It

  • 1. Artificial Intelligence Will Artificial Intelligence live up to the hype? June 15, 2017
  • 2. 2 © Copyright Publicis.Sapient | Confidential Agenda 1. Introduction 2. Current State of AI 3. Applications 4. Business Value for Sapient 5. Pros and Cons 6. Future Predictions 7. Conclusion
  • 4. 4 © Copyright Publicis.Sapient | Confidential What is Artificial Intelligence? “The science and engineering of making intelligent machines, especially intelligent computer programs” John McCarthy, father of Artificial Intelligence
  • 5. 5 © Copyright Publicis.Sapient | Confidential Artificial Intelligence At a Glance • Artificial Neural Networks • Machine Learning • Planning • Knowledge Representation • Perception • Natural Language Processing (NLP) • Cognitive Systems • Robotics
  • 6. 6 © Copyright Publicis.Sapient | Confidential Impact of AI • Automated transportation – the beginning of self-driving cars era. • Reduction number of dangerous jobs – outsourcing jobs, like welding, to robots. • Virtual assistants – over half of the Apple device users use Siri on daily basis. • Assisting in solving climate change – analysis of historic patterns and predictions. • Healthcare – IBM Watson has been able to draw same conclusion as human in 99% of cases. Furthermore IBM Watson found something new in 30% of cases. • Simplified recruitment process • Financial fraud detection – a number of financial services technologies are utilizing machine learning to detect financial fraud.
  • 7. 7 © Copyright Publicis.Sapient | Confidential Artificial Intelligence Enablers • Cloud Computing • Big Data Processing & Distributed Computing • Open Source • Customer Decision Driven Markets • Advancements in High Performance Computing • Internet of Things (IoT)
  • 9. 9 © Copyright Publicis.Sapient | Confidential "This is not hype. It's real and sustained progress, which accelerates research” - Roman Yampolskiy
  • 11. 11 © Copyright Publicis.Sapient | Confidential • 2017 - CB Insights suggests that 200 AI-focused companies have raised nearly $1.5 billion in equity funding.
  • 12. 12 © Copyright Publicis.Sapient | Confidential • Khosala Ventures - the most active AI investor • Backed over 15 companies during that time frame, including Atomwise and MetaMind • Google DeepMind • Collaborating with the UK’s NHS in a handful of projects. • Spotify, Microsoft, Uber, Facebook, Apple, IBM
  • 13. 13 © Copyright Publicis.Sapient | Confidential Companies Investing in Artificial Intelligence
  • 15. 15 © Copyright Publicis.Sapient | Confidential “There is no approach at the moment that has any hope of being flexible and performing multiple tasks or going beyond the basic tasks that it’s programmed to do“ Andrei Barbu, MIT Center for Brains, Minds and Machines
  • 19. 19 © Copyright Publicis.Sapient | Confidential Machine Learning Supervised learning: • The algorithm seeks a function from inputs to the respective targets. Generally the algorithm is presented with data that is already classified. • User provides labels that algorithm takes into consideration. At the end of algorithm, decision model is obtained. • Recommendation on Amazon, Netflix and Google are based on the supervised learning techniques. Unsupervised learning: • The algorithm groups data how similar it is to each other. The goal is to discover similar features, thus clustering. • Image processing is a common application of this, specifically image denoising. Natural language processing is common too.
  • 20. 04 Business Value for Sapient
  • 21. 21 © Copyright Publicis.Sapient | Confidential Collaborating Razorfish, DigitasLBi, SapientNitro and Sapient Consulting. Luminoso: • Partnership between Publicis.Sapient and Luminoso Technologies, Inc., a leading global player in AI-based deep analytics • Government Service Luminoso: Redistribute Luminoso’s products into government agencies. Help U.S. federal clients transform data into actionable insights • Retail Hyper-personalized Virtual Assistant for the retail industry, created in partnership with SapientNitro. • Automating manual processes • Analysing unstructured data –analyse data to obtain patterns that allow to obtain “hidden” information. AI in Sapient
  • 22. 05 Pros and Cons
  • 23. Pros • Greater accuracy - somewhat elimination of “human” error • Utilised to carry out repetitive tasks – increased automation that will increase productivity. • Continuously function without needing to rest - With AI, data can be processed no matter how big the dataset might be. • Cost efficient • Fraud detection – financial institution are already utilizing machine learning to recognize the behaviour of users and detecting discrepancies.
  • 24. Cons • Cost incurred in the maintenance and repair – increased dependency will lead to higher investment in technology. • Lack of “human touch” • Lack of creativity • Automation of jobs – low skilled jobs will be eliminated, thus increase in unemployment. • Unexpected error – in recent past, there was a pound fall caused by algorithmic trading. • Lack of judgement call – In 2014, during the shooting in Sydney, Uber algorithm rather than helping people get out of area, surged the pricing.
  • 26. • AI tools for risk management and compliance purposes. • Machine learning to enhance their investment research. • Algorithmic trading. • Reducing fraud and crime. • Automated financial advisors. • By 2025 half of investment assets will be traded via AI according to Tractica market research report. AI in Financial Services
  • 27. 27 © Copyright Publicis.Sapient | Confidential Industries at risk • Taxi drivers – The effect of Uber, Lyft and likes. • Factory Workers • The first robot-only factory is being built in China's Dongguan factory city. • Journalists • Doctors – diagnosis & analysis of patients. • Lawyers – Smart, volume based analysis. • Education – the rise of self learning and AI robots specializing in education. Every Industry will be affected by the Artificial Intelligence. Some reports suggest up to 47% of all jobs will be taken over by AI!
  • 28. 28 © Copyright Publicis.Sapient | Confidential Summary • Development of IT infrastructure and the penetration of smartphones and smart wearables main contributor to growth. • Elimination of low-skilled jobs, leading to increased productivity. • AI market is expected to grow from $1.25B to $36.82B by 2025*. • Massive opportunity for those betting big on AI, especially for Sapient in FS sector. • Manufacturing, media, transportation and advertising industries as main drivers of growth. * according to Statista 2017 report.

Editor's Notes

  1.  director of the cybersecurity lab at the University of Louisville
  2. As of June 2016, artificial intelligence received $974m of funding. This year’s funding is set to surpass 2015’s total and CB Insights suggests that 200 AI-focused companies have raised nearly $1.5 billion in equity funding. Fujitsu holds the most Artificial Intelligence patents, its human-centric AI Zinrai incorporates sensory-media technologies that can process people’s feelings, knowledge processing that can provide medical decision-making support and mathematic technology that is able to assist in mitigating air traffic.
  3. Google DeepMind - created an AI project that uses reasoning to conquer the London Underground. collaborating with the UK’s NHS in a handful of projects, including ones in which their software is being taught to diagnose cancer and eye disease from patient scans. Others are using machine learning to catch early signs of conditions such as heart disease and Alzheimers Facebook is helping blind people 'see' photos by using artificial intelligence to narrate them via its iOS app.
  4. Spun out of the Massachusetts Institute of Technology (MIT) Media Lab, Luminoso’s software is unique for its ability to process the intended meanings behind social content, blog posts, articles, news and other information sources that less sophisticated technology often cannot interpret. Luminoso’s products understand not just the words consumers are using, but also their underlying sentiment and intent. By rapidly analyzing large amounts of written feedback and providing real-time reporting, it can enable organizations to more quickly respond to the demands of their users.  This conversational commerce platform leveraged multiple technologies including tools from Facebook, Nuance and Luminoso. It demonstrated something fundamentally new in the world of virtual assistants: being able to listen to answers to open ended questions and extract insights about the consumers from their answers. Based on a person’s answers to questions such as “Where would you go on your ideal vacation? Please explain why”, the platform was able to recommend specific products curated based on the personality of the individual.
  5. https://www.theguardian.com/business/2016/oct/07/what-caused-pound-flash-crash-brexit-fallen-sterling
  6. https://www.theguardian.com/business/2016/oct/07/what-caused-pound-flash-crash-brexit-fallen-sterling
  7. For example, a leading financial institution is proactively assessing risk by using AI to review all of the activities undertaken by traders that have made suspicious trades. . For example, firms can analyse foot traffic at an individual set of retail stores or compare the current number of hours worked at a manufacturing company to the last week or quarter in real time to identify what a company’s performance might look like before it’s announced.
  8. Later this year, automated taxi pods will start running on the streets of England's Milton Keynes, offering rides around the town. Factory owner aims to reduce the current workforce of 1,800 by 90% Since September last year, a total of 505 factories across Dongguan have invested 4.2bn yuan (£430m) in robots, aiming to replace more than 30,000 workers according to the Dongguan Economy and Information Technology Bureau.