High-level overview of AI attempting to answer three key questions: 1) Why are people so interested in AI? 2) What is it anyway? 3) What are some examples in eCommerce?
How artificial intelligence is transforming the e commerce industryCountants
Accounting for an impressive 35% of its overall revenues, product upselling and cross-selling on the Amazon E-commerce platform is among this retailer’s major success stories. Which technology is driving this mode of conversion? Amazon’s product recommendation technology that is primarily enabled by artificial intelligence or AI.
This document discusses how artificial intelligence is being applied in digital marketing. It outlines several ways AI can be used, including personalizing the user experience through smart content curation, chatbots, and predictive analytics. It also discusses how AI can help with lead generation through ad click prediction, ad personalization, and programmatic media buying. The document emphasizes that AI is already widely used in business and that companies should leverage their data through personalization rather than averaging to not miss opportunities with AI.
Adverity: The Impact of Artificial Intelligence in MarketingAdverity
Understand what AI in marketing is. Learn how artificial intelligence impacts digital marketing. And find out whether you should feel threatened by machine learning and intelligent artificial intelligence at all.
AI is the area that intends to comprehend the idea of human insight through the development of computer programs that emulate the intelligent behavior. AI strategies are effectively created and utilized as a part of most of the zones of science, designing, instruction, business, and so on. The momentum AI is so fast that it dynamically, intelligently rising quickly and influencing industries from banking through to healthcare.
E-commerce is the use of computing and communication advances in commerce between a few or all parts of a trade and its clients. AI strategies are broadly utilized in the improvement of e-commerce systems too. The field of e-commerce can be classified as B2C e-commerce and B2B e-commerce, in terms of AI strategies included in this field. In this slide, we show a few vital AI methods that are valuable in the plan and improvement of e-commerce frameworks
It has been said that Mobiles +Cloud + Social + Big Data = Better Run The World. IBM has invested over $20 billion since 2005 to grow its analytics business, many companies will invest more than $120 billion by 2015 on analytics, hardware, software and services critical in almost every industry like ; Healthcare, media, sports, finance, government, etc.
It has been estimated that there is a shortage of 140,000 – 190,000 people with deep analytical skills to fill the demand of jobs in the U.S. by 2018.
Decoding the human genome originally took 10 years to process; now it can be achieved in one week with the power of Analytic and BI (Business Intelligence). This lecture’s Key Messages is that Analytics provide a competitive edge to individuals , companies and institutions and that Analytics and BI are often critical to the success of any organization.
Methodology used is to teach analytic techniques through real world examples and real data with this goal to convince audience of the Analytics Edge and power of BI, and inspire them to use analytics and BI in their career and their life.
Do you know the business benefits of AI in the eCommerce as well as the retail Industry? In this article, we share some essential information about how you can increase your e-commerce & retail business sales with the help of AI.
Artificial intelligence (AI) is having a major impact on e-commerce. AI can mimic human intelligence through techniques like machine learning and deep neural networks. AI has the potential to significantly change businesses and the global economy. Retailers are increasingly investing in AI to improve marketing, sales, customer service, and supply chain management. By 2021, retailers that use AI for visual and voice search could increase digital commerce revenue by 30%. AI adoption is expected to boost global business revenue significantly between 2017-2021. SAP offers AI and machine learning capabilities across its software portfolio to help businesses gain insights from data.
AI marketing uses artificial intelligence technologies to make automated decisions based on data collection, data analysis, and additional observations of audience or economic trends that may impact marketing efforts. AI marketing tools use data and customer profiles to learn how to best communicate with customers, then serve them tailored messages at the right time without intervention from marketing team members, ensuring maximum efficiency.
This document discusses the use of artificial intelligence and chatbots in marketing. It outlines how chatbots can transform traditional sales and marketing funnels by allowing direct two-way conversations with customers. Examples are given of clothing and automotive brands using chatbots for personalized customer assistance and targeted campaigns. Statistics show growing markets for chatbots and their benefits across industries like e-commerce, insurance, and healthcare. The future potential of major companies developing chatbot technologies is also mentioned.
AI will not steal your job, but those who know how to use it might. In this session, you will learn about artificial intelligence (AI), ChatGPT and more and their impact on content marketing. Where and how are we using AI without realizing and what more can we do to be more productive, creative and efficient with our content marketing efforts? The amount of content being produced is not decreasing. AI will help you scale your content production to remain competitive and drive engagement.
1. Machine learning is a set of techniques that use data to build models that can make predictions without being explicitly programmed.
2. There are two main types of machine learning: supervised learning, where the model is trained on labeled examples, and unsupervised learning, where the model finds patterns in unlabeled data.
3. Common machine learning algorithms include linear regression, logistic regression, decision trees, support vector machines, naive Bayes, k-nearest neighbors, k-means clustering, and random forests. These can be used for regression, classification, clustering, and dimensionality reduction.
This is a deck on the state of Artificial Intelligence applications in Marketing. It covers an overview of the AI types and algorithms being used for Marketing use cases, a brief of the near-term future of AI in marketing, and covers some Marketing startups focusing on AI technologies.
AI vs Machine Learning vs Deep Learning | Machine Learning Training with Pyth...Edureka!
Machine Learning Training with Python: https://www.edureka.co/python )
This Edureka Machine Learning tutorial (Machine Learning Tutorial with Python Blog: https://goo.gl/fe7ykh ) on "AI vs Machine Learning vs Deep Learning" talks about the differences and relationship between AL, Machine Learning and Deep Learning. Below are the topics covered in this tutorial:
1. AI vs Machine Learning vs Deep Learning
2. What is Artificial Intelligence?
3. Example of Artificial Intelligence
4. What is Machine Learning?
5. Example of Machine Learning
6. What is Deep Learning?
7. Example of Deep Learning
8. Machine Learning vs Deep Learning
Machine Learning Tutorial Playlist: https://goo.gl/UxjTxm
AI in Marketing: Guest lecture at Bournemouth university Zoodikers
Katie King is an expert on AI and its impact on marketing. She discusses how AI is advancing beyond just data analysis to generating data from sights and sounds through machine vision and speech recognition. AI will transform marketers by helping with segmentation, tracking, and keyword tagging to make planning and execution more efficient. While AI can aid content creation, human marketers are still needed for their creativity. New technologies like chatbots and autonomous retail robots powered by AI are also discussed. King emphasizes that to prepare for the future of work with AI, organizations need to focus on retraining, culture, and experimentation.
KSIT Tech Form - Introduction to artificial intelligence (AI)Santosh Kumar
The document provides an introduction to artificial intelligence (AI) with the following key points:
1. It defines intelligence as the capacity for logic, understanding, learning, problem solving, and more. AI is defined as computer systems that can perform tasks requiring human intelligence like visual perception and decision-making.
2. There are different types of AI like machine learning, deep learning, supervised learning, unsupervised learning, and reinforcement learning. Machine learning allows systems to learn from data rather than through explicit programming.
3. Deep learning is a type of machine learning inspired by the brain that uses neural networks to learn representations of data. Supervised learning uses labeled input-output data to learn general rules while unsupervised learning
Explore how different industries are embracing the utility of AI to create and deliver new value for their customers and organisation
* Discuss the state of maturity of AI across industries
* Get an appreciation of business posture to AI projects
We also review the utility of AI across several industries including:
* Healthcare
* Newsroom & Journalism
* Travel
* Finance
* Supply Chain / eCommerce / Retail
* Streaming & Gaming
* Transportation
* Logistics
* Manufacturing
* Agriculture
* Defense & Cybersecurity
Part of the What Matters in AI series as published on www.andremuscat.com
AI Basic, AI vs Machine Learning vs Deep Learning, AI Applications, Top 50 AI Game Changer Solutions, Advanced Analytics, Conversational Bots, Financial Services, Healthcare, Insurance, Manufacturing, Quality & Security, Retail, Social Impact, and Transportation & Logistics
The document discusses the use of artificial intelligence and machine learning in the financial industry. It covers emerging trends like increased regulations, growth of digital technologies, and the emergence of AI/ML. It also discusses key concepts like big data, different types of machine learning (supervised, unsupervised, reinforcement, deep learning), and applications in areas like portfolio management, algorithmic trading, fraud detection, and chatbots. The future of AI in finance is seen as promising with potential for more widespread use of these technologies across various business problems in finance and other industries.
Impact of Artificial Intelligence on Marketing.pptxSadiahAhmad
This document discusses the impact of artificial intelligence on marketing. It begins with an introduction and definitions of key terms like AI and its applications. It then explores how AI has been implemented in various marketing functions at companies like Netflix, Amazon, Levis, Disney and Spotify. The findings are that AI has made marketing more effective and impacted areas like user experience, ROI, decision making and sales forecasting. Applications of AI in marketing discussed include product recommendations, chatbots, email marketing and digital advertising. The document also outlines major challenges of adopting AI in marketing as well as recommendations for overcoming challenges and effectively integrating AI technologies.
BBS-248 Artificial Intelligence (AI) for Financial ServicesOzgur Karakaya
• Artificial Intelligence (AI) general info and the AI world market
• AI in financial sector: services that AI can be applied (Investing, Management, Market Research, Blockchain, Fraud Detection, AI Assistants/Bots, etc.)
• AI firms, products and the tech behind.
This document discusses the uses of artificial intelligence in fintech. It defines AI as computer systems imitating human thinking, and describes three types: weak AI which completes simple tasks based on programming, strong AI which can learn and adapt to complete tasks more efficiently, and human reasoning AI which can anticipate human responses through machine learning. It explains that fintech industries use AI to enhance customer service by processing large amounts of data quickly to better understand customers, detect fraud, and provide faster, more personalized financial services and guidance. Overall, AI benefits fintech customers by accelerating and improving the convenience, ease of use, and delivery of financial services.
Almost every company can benefit from Artificial Intelligence, including sales and marketing. It allows marketers to become more proficient by gathering data and allowing people to personalize it. Know some of the specific benefits by Call Sumo like Score Leads Automatically, Customer Segmentation & Advanced Personalization, A Game-Changer for Sales Representatives, Shorten the Sales Cycle by Automating Lead Qualification and more, that your panel can expect when using AI.
Top 10 Applications Of Artificial Intelligence | EdurekaEdureka!
YouTube Link: https://youtu.be/Y46zXHvUB1s
** Machine Learning Masters Program: https://www.edureka.co/masters-progra... **
This Edureka session on Applications Of Artificial Intelligence will help you understand how AI is impacting various domains such as banking, marketing, healthcare and so on.
Following are the topics covered in this PPT:
AI In Artificial Creativity
AI In Social Media
AI In Chatbots
AI In Autonomous Vehicles
AI In Space Exploration
AI In Gaming
AI In Banking & Finance
AI In Agriculture
AI In Healthcare
AI In Marketing
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
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Why Social Media Chat Bots Are the Future of Communication - DeckJan Rezab
Social media chat bots are the future of communication, if its WhatsApp, Facebook Messenger, Kik, Skype, or Telegram - you can use their bots and bot stores to easily access new services - easier you could ever do it with apps.
The 7 Biggest Artificial Intelligence (AI) Trends In 2022Bernard Marr
The document discusses 8 major artificial intelligence trends for 2022:
1. The augmented workforce, where AI tools will help boost workers' abilities and make jobs more efficient.
2. Bigger and better language models that can generate more human-like text.
3. Increased use of AI in cybersecurity to detect network threats.
4. Role of AI in developing virtual worlds known as the "metaverse."
5. Growth of low-code and no-code tools that make AI development simpler.
6. Advancements in autonomous vehicles like cars and ships.
7. AI that can generate more complex creative works like art and music.
8. Continued pushing of boundaries in what AI systems
How is Artificial Intelligence transforming the way of digital marketing?MakeWebBetter
Hey, guys, we have come up with the idea of introducing the concept of artificial intelligence in digital marketing strategies.
Here is what we have covered in our presentation :
>> What is Digital Marketing?
>> What is Artificial Intelligence?
>> Why do we need to think about digital marketing using AI?
>> How is AI changing the way of digital marketing strategies?
>> Why do businesses need to combined their marketing strategies with AI?
>> Some popular case studies on AI and its tools being used by companies.
>> What are the latest statistics on artificial intelligence and the related trends?
>> Conclusion with the advantages
So guys, if you think you are in the developing phase of your business then you really need to see an eye to eye with right marketing strategies to stand in front of the curve in a long run.
For this, we feel blessed to provide you with necessary tutorials constantly, if you like our post, like and share it.
To know us to visit: www.makewebbetter.com
Follow us on:
Twitter - https://twitter.com/makewebbetter?lang=en
Instagram - https://www.instagram.com/makewebbetter/
Facebook - https://www.facebook.com/makewebbetter/
Stay connected to keep getting more updates.
Thanks For Watching
Team MakeWebBetter
AI in marketing - A detailed insight.pdfStephenAmell4
AI in marketing refers to the integration of artificial intelligence technologies, such as machine learning and natural language processing, into marketing operations to optimize strategies, enhance customer experiences and more.
This document discusses the application of parallel computing in artificial intelligence. It begins with an introduction to AI, including its definition and history. It then discusses how parallel computing is used in AI training through techniques like data parallelism and pipeline parallelism. This allows datasets to be distributed across multiple GPUs for faster training. The document also outlines several applications of AI in fields like computer vision, autonomous vehicles, natural language processing and audio processing. Finally, it concludes that GPU parallel computing has driven growth in the AI industry by enabling complex deep learning models to be trained on large datasets. Parallel computing was key to advances in AI.
This document discusses the use of artificial intelligence and chatbots in marketing. It outlines how chatbots can transform traditional sales and marketing funnels by allowing direct two-way conversations with customers. Examples are given of clothing and automotive brands using chatbots for personalized customer assistance and targeted campaigns. Statistics show growing markets for chatbots and their benefits across industries like e-commerce, insurance, and healthcare. The future potential of major companies developing chatbot technologies is also mentioned.
AI will not steal your job, but those who know how to use it might. In this session, you will learn about artificial intelligence (AI), ChatGPT and more and their impact on content marketing. Where and how are we using AI without realizing and what more can we do to be more productive, creative and efficient with our content marketing efforts? The amount of content being produced is not decreasing. AI will help you scale your content production to remain competitive and drive engagement.
1. Machine learning is a set of techniques that use data to build models that can make predictions without being explicitly programmed.
2. There are two main types of machine learning: supervised learning, where the model is trained on labeled examples, and unsupervised learning, where the model finds patterns in unlabeled data.
3. Common machine learning algorithms include linear regression, logistic regression, decision trees, support vector machines, naive Bayes, k-nearest neighbors, k-means clustering, and random forests. These can be used for regression, classification, clustering, and dimensionality reduction.
This is a deck on the state of Artificial Intelligence applications in Marketing. It covers an overview of the AI types and algorithms being used for Marketing use cases, a brief of the near-term future of AI in marketing, and covers some Marketing startups focusing on AI technologies.
AI vs Machine Learning vs Deep Learning | Machine Learning Training with Pyth...Edureka!
Machine Learning Training with Python: https://www.edureka.co/python )
This Edureka Machine Learning tutorial (Machine Learning Tutorial with Python Blog: https://goo.gl/fe7ykh ) on "AI vs Machine Learning vs Deep Learning" talks about the differences and relationship between AL, Machine Learning and Deep Learning. Below are the topics covered in this tutorial:
1. AI vs Machine Learning vs Deep Learning
2. What is Artificial Intelligence?
3. Example of Artificial Intelligence
4. What is Machine Learning?
5. Example of Machine Learning
6. What is Deep Learning?
7. Example of Deep Learning
8. Machine Learning vs Deep Learning
Machine Learning Tutorial Playlist: https://goo.gl/UxjTxm
AI in Marketing: Guest lecture at Bournemouth university Zoodikers
Katie King is an expert on AI and its impact on marketing. She discusses how AI is advancing beyond just data analysis to generating data from sights and sounds through machine vision and speech recognition. AI will transform marketers by helping with segmentation, tracking, and keyword tagging to make planning and execution more efficient. While AI can aid content creation, human marketers are still needed for their creativity. New technologies like chatbots and autonomous retail robots powered by AI are also discussed. King emphasizes that to prepare for the future of work with AI, organizations need to focus on retraining, culture, and experimentation.
KSIT Tech Form - Introduction to artificial intelligence (AI)Santosh Kumar
The document provides an introduction to artificial intelligence (AI) with the following key points:
1. It defines intelligence as the capacity for logic, understanding, learning, problem solving, and more. AI is defined as computer systems that can perform tasks requiring human intelligence like visual perception and decision-making.
2. There are different types of AI like machine learning, deep learning, supervised learning, unsupervised learning, and reinforcement learning. Machine learning allows systems to learn from data rather than through explicit programming.
3. Deep learning is a type of machine learning inspired by the brain that uses neural networks to learn representations of data. Supervised learning uses labeled input-output data to learn general rules while unsupervised learning
Explore how different industries are embracing the utility of AI to create and deliver new value for their customers and organisation
* Discuss the state of maturity of AI across industries
* Get an appreciation of business posture to AI projects
We also review the utility of AI across several industries including:
* Healthcare
* Newsroom & Journalism
* Travel
* Finance
* Supply Chain / eCommerce / Retail
* Streaming & Gaming
* Transportation
* Logistics
* Manufacturing
* Agriculture
* Defense & Cybersecurity
Part of the What Matters in AI series as published on www.andremuscat.com
AI Basic, AI vs Machine Learning vs Deep Learning, AI Applications, Top 50 AI Game Changer Solutions, Advanced Analytics, Conversational Bots, Financial Services, Healthcare, Insurance, Manufacturing, Quality & Security, Retail, Social Impact, and Transportation & Logistics
The document discusses the use of artificial intelligence and machine learning in the financial industry. It covers emerging trends like increased regulations, growth of digital technologies, and the emergence of AI/ML. It also discusses key concepts like big data, different types of machine learning (supervised, unsupervised, reinforcement, deep learning), and applications in areas like portfolio management, algorithmic trading, fraud detection, and chatbots. The future of AI in finance is seen as promising with potential for more widespread use of these technologies across various business problems in finance and other industries.
Impact of Artificial Intelligence on Marketing.pptxSadiahAhmad
This document discusses the impact of artificial intelligence on marketing. It begins with an introduction and definitions of key terms like AI and its applications. It then explores how AI has been implemented in various marketing functions at companies like Netflix, Amazon, Levis, Disney and Spotify. The findings are that AI has made marketing more effective and impacted areas like user experience, ROI, decision making and sales forecasting. Applications of AI in marketing discussed include product recommendations, chatbots, email marketing and digital advertising. The document also outlines major challenges of adopting AI in marketing as well as recommendations for overcoming challenges and effectively integrating AI technologies.
BBS-248 Artificial Intelligence (AI) for Financial ServicesOzgur Karakaya
• Artificial Intelligence (AI) general info and the AI world market
• AI in financial sector: services that AI can be applied (Investing, Management, Market Research, Blockchain, Fraud Detection, AI Assistants/Bots, etc.)
• AI firms, products and the tech behind.
This document discusses the uses of artificial intelligence in fintech. It defines AI as computer systems imitating human thinking, and describes three types: weak AI which completes simple tasks based on programming, strong AI which can learn and adapt to complete tasks more efficiently, and human reasoning AI which can anticipate human responses through machine learning. It explains that fintech industries use AI to enhance customer service by processing large amounts of data quickly to better understand customers, detect fraud, and provide faster, more personalized financial services and guidance. Overall, AI benefits fintech customers by accelerating and improving the convenience, ease of use, and delivery of financial services.
Almost every company can benefit from Artificial Intelligence, including sales and marketing. It allows marketers to become more proficient by gathering data and allowing people to personalize it. Know some of the specific benefits by Call Sumo like Score Leads Automatically, Customer Segmentation & Advanced Personalization, A Game-Changer for Sales Representatives, Shorten the Sales Cycle by Automating Lead Qualification and more, that your panel can expect when using AI.
Top 10 Applications Of Artificial Intelligence | EdurekaEdureka!
YouTube Link: https://youtu.be/Y46zXHvUB1s
** Machine Learning Masters Program: https://www.edureka.co/masters-progra... **
This Edureka session on Applications Of Artificial Intelligence will help you understand how AI is impacting various domains such as banking, marketing, healthcare and so on.
Following are the topics covered in this PPT:
AI In Artificial Creativity
AI In Social Media
AI In Chatbots
AI In Autonomous Vehicles
AI In Space Exploration
AI In Gaming
AI In Banking & Finance
AI In Agriculture
AI In Healthcare
AI In Marketing
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Why Social Media Chat Bots Are the Future of Communication - DeckJan Rezab
Social media chat bots are the future of communication, if its WhatsApp, Facebook Messenger, Kik, Skype, or Telegram - you can use their bots and bot stores to easily access new services - easier you could ever do it with apps.
The 7 Biggest Artificial Intelligence (AI) Trends In 2022Bernard Marr
The document discusses 8 major artificial intelligence trends for 2022:
1. The augmented workforce, where AI tools will help boost workers' abilities and make jobs more efficient.
2. Bigger and better language models that can generate more human-like text.
3. Increased use of AI in cybersecurity to detect network threats.
4. Role of AI in developing virtual worlds known as the "metaverse."
5. Growth of low-code and no-code tools that make AI development simpler.
6. Advancements in autonomous vehicles like cars and ships.
7. AI that can generate more complex creative works like art and music.
8. Continued pushing of boundaries in what AI systems
How is Artificial Intelligence transforming the way of digital marketing?MakeWebBetter
Hey, guys, we have come up with the idea of introducing the concept of artificial intelligence in digital marketing strategies.
Here is what we have covered in our presentation :
>> What is Digital Marketing?
>> What is Artificial Intelligence?
>> Why do we need to think about digital marketing using AI?
>> How is AI changing the way of digital marketing strategies?
>> Why do businesses need to combined their marketing strategies with AI?
>> Some popular case studies on AI and its tools being used by companies.
>> What are the latest statistics on artificial intelligence and the related trends?
>> Conclusion with the advantages
So guys, if you think you are in the developing phase of your business then you really need to see an eye to eye with right marketing strategies to stand in front of the curve in a long run.
For this, we feel blessed to provide you with necessary tutorials constantly, if you like our post, like and share it.
To know us to visit: www.makewebbetter.com
Follow us on:
Twitter - https://twitter.com/makewebbetter?lang=en
Instagram - https://www.instagram.com/makewebbetter/
Facebook - https://www.facebook.com/makewebbetter/
Stay connected to keep getting more updates.
Thanks For Watching
Team MakeWebBetter
AI in marketing - A detailed insight.pdfStephenAmell4
AI in marketing refers to the integration of artificial intelligence technologies, such as machine learning and natural language processing, into marketing operations to optimize strategies, enhance customer experiences and more.
This document discusses the application of parallel computing in artificial intelligence. It begins with an introduction to AI, including its definition and history. It then discusses how parallel computing is used in AI training through techniques like data parallelism and pipeline parallelism. This allows datasets to be distributed across multiple GPUs for faster training. The document also outlines several applications of AI in fields like computer vision, autonomous vehicles, natural language processing and audio processing. Finally, it concludes that GPU parallel computing has driven growth in the AI industry by enabling complex deep learning models to be trained on large datasets. Parallel computing was key to advances in AI.
The Disadvantages Of Artificial IntelligenceAngela Hays
Artificial intelligence is becoming increasingly important in technology and transforming societies. While AI brings benefits like improved efficiency and productivity, it also poses risks like job disruption and increased inequality. Overall, whether AI improves or worsens societies will depend on how its development and application are guided.
Technology in Business Law by Ammar YounasAmmar Younas
This lecture has been prepared by Ammar Younas, Senior Lecturer in Commercial Law at Westminster International University in Tashkent for the Class of 2019-2020 Introduction to Business Law.
Mr. Koushal Kumar Has done his M.Tech degree in Computer Science and Engineering from Lovely Professional University, Jalandhar, India. He obtained his B.S.C and M.S.C in computer science from D.A.V College Amritsar Punjab. His area of research interests lies in Artificial Neural Networks, Soft computing, Computer Networks, Grid Computing, and data base management systems
just hvae a look, m sure u whould lyk it...............................................................................................................................................................................its all about artificial machines.....................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................
Revolution of Quantum Computing in AI EraPrinceBarpaga
What is a Quantum Computer?
How does a Quantum Computer Work?
How will Quantum Computing revolutionize AI?
Can a Computer think like a human?
These are all the questions that I seek to answer in my presentation which was delivered at York University on 22nd March at Lassonde School of Engineering.
Presentation done and delivered by Prince Barpaga
Work/Technology 2050: Scenarios and Actions (Dubai talk)Jerome Glenn
The Millennium Project conducted a three-year global study on the future of work and technology called the Work/Technology 2050 Global Study. The study involved over 1,300 pages and used 37 different futures methods. It developed three scenarios for how work and technology could evolve by 2050: a mixed scenario, a political/economic turmoil scenario, and a self-actualization scenario. National workshops were held to discuss long-term strategies. This resulted in 93 proposed actions that were assessed in the areas of education, government, business, culture, and science/technology. The study explored how emerging technologies could profoundly impact work and the need for new economic and social systems to address issues like unemployment.
Internet of things and nanothings workshop may 2014Marios Kyriazis
This document provides an overview of the Internet of Things (IoT). It begins with motivation for the IoT, discussing how physical objects are becoming connected to the internet through embedded sensors and the convergence of the physical and digital worlds. Examples of application domains for the IoT are then described, such as smart homes, cities, transportation and health. Challenges and future directions are also discussed, such as privacy concerns and the potential for the IoT to extend to nanotechnology and more intelligent systems.
What really is Artificial Intelligence about? Harmony Kwawu
AI systems are growing. But what is AI, where did the idea behind it come from, what is intelligence, how does expert level intelligence work, and perhaps most importantly, would AI systems eventually make human beings redundant?
This document provides a case study on Google DeepMind and artificial intelligence. It discusses DeepMind's work in machine learning, deep reinforcement learning, and its creation of AlphaGo which was able to defeat professional Go players. The document also briefly outlines DeepMind's work in healthcare by collaborating with hospitals to analyze medical scans and develop algorithms to differentiate healthy and cancerous tissues. However, DeepMind's data sharing agreement with the Royal Free London NHS Foundation Trust to access patient medical records without consent was controversial.
The document provides an introduction to artificial intelligence (AI) and its history. It defines key AI terms like artificial intelligence, machine learning, and deep learning. It explains how deep learning helps solve limitations of classic machine learning by determining representations of data. The summary highlights major developments in AI history including early algorithms, expert systems, neural networks, and breakthroughs with deep learning starting in 2006. It differentiates modern AI using deep learning from prior approaches and provides examples of AI applications.
The document provides an introduction to artificial intelligence, including what AI is, its history and development over different eras. It discusses the types and approaches of AI, including reactive machines, limited memory systems, theory of mind and self-awareness. It also outlines how AI systems map to human thinking processes and how factors like advances in computing, big data, cloud computing and data science have influenced AI's development. Finally, it gives examples of real-world AI applications in various fields such as transportation, healthcare, home services and public safety.
The document discusses the history of artificial intelligence from its origins in the 1940s to modern applications. It describes several key early developments, including the first artificial neuron model (1943), the proposal of the Turing Test (1950), and the coining of the term "artificial intelligence" at the Dartmouth Conference (1956). The document also notes periods of growth and funding declines ("AI winters") for the field throughout its development. Overall, the history shows steady progress in AI from its theoretical beginnings to impactful applications today.
The document provides an overview of artificial intelligence (AI), including its history, definition, examples, advantages, and disadvantages. It traces the origins of AI concepts back to ancient Greece and discusses early milestones like the Turing test. Examples of modern AI applications mentioned include Google Maps, facial recognition, chatbots, and automated payments. While AI can reduce human error and perform dangerous tasks, disadvantages include high costs and an inability to think creatively.
This document outlines GenAI's marketplace partnership strategy. It discusses anchor partners that provide widely used solutions, niche partners with specialized solutions, and strategic partnerships that align with long-term objectives. Various revenue share models are presented, including publishing, joint venture, and royalty models. Examples of partnership agreements are provided. Finally, the document recommends establishing a dedicated team to pursue, manage, and optimize marketplace partnerships.
DTW Asia 23 - Collaboration_Metaverse Presentation_Final - 230315.pdfMichael Lesniak
This document provides an overview of collaborating to build the metaverse. It discusses how the metaverse will be the successor to the mobile internet and outlines Meta's investments including acquiring companies and developing devices and platforms. Emerging metaverse use cases are explored like VR games, education, and spatial computing. The document advocates working with leaders, startups, and brands in areas like mixed reality, blockchain virtual worlds, and immersive experiences to help develop the market. It also suggests defining a role in presence-driven use cases and building something in mixed reality to understand how to enable presence.
Web3_Metaverse_Foundations - DTW Coppenhagen - FINAL - 230919Michael Lesniak
This document discusses opportunities in web3 and the metaverse. It begins with short biographies of Genya Smagin and Michael A. Lesniak who work in web3 business development, metaverse partnerships and investments. The document then discusses laying a foundation for monetization in web3 and the metaverse through services, closing with a question and answer session.
The metaverse hype-cycle is in full swing, what's really going on? VR is driving presence-driven use cases, led by Meta and Quest 2. The market is big and growing fast, without the promise of Trillions USD to be had.
Quest 2 and the future of metaverse v2.0 210908Michael Lesniak
Brief overview of the impact of the Quest 2 launch in S. Korea on the development of the metaverse here, and the near future of the metaverse worldwide.
Note:
Michael's Metaverse for Dummies by Michael A. Lesniak is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Based on a work at http://www.malesniak.com/2020/09/blog-post.html.
This document outlines a vision for 5G and immersive media experiences including augmented reality (AR), virtual reality (VR), and mixed reality. It discusses leveraging existing mobile assets to build next generation services allowing customers to experience concerts and events, play games, learn, shop, and more together in AR and VR. It also outlines strategic partnerships with content providers and an in-house technology platform to help creators build immersive virtual spaces and experiences using tools like telepresence, rendering, tracking, and more.
The V2X Secure Central Gateway monitors in-vehicle networks for intrusions or abnormalities in near real-time over 5G. It uses quantum random number generation to secure the 5G cellular connection. The gateway can detect remote attacks and address issues quickly via low-latency 5G. It also enables secure over-the-air updates and transmission of vehicle status and location for emergency response.
Brief description of 11st ("eleventh street") Shop-in-Shop opportunity for exclusive retail partners like Tesco Home Plus, or major consumer brands like Samsung.
The Blockchain: Introduction and ImplicationsMichael Lesniak
The document provides an introduction to blockchain technology, discussing its origins and implications. It describes how blockchain establishes trust without third parties by using cryptography and distributed networks. Blockchain originated from a 2008 white paper introducing Bitcoin and has since grown significantly. The document outlines several potential benefits of blockchain, such as enabling trust, financial inclusion, and protecting digital identities and rights. It also discusses how blockchain could improve how we exchange value and conduct business through features like smart contracts.
SK planet is a leading e-commerce and O2O commerce company in South Korea that is seeking to expand distribution of SCINIC, a popular Korean skin care brand. SCINIC focuses on using natural ingredients and technology to create affordable, high-quality skin care products. It has a complete portfolio of products and a track record of innovation. The global beauty market is growing, particularly in emerging markets and skin care categories. SCINIC is well positioned for further growth internationally as a niche Korean brand known for its natural ingredients. SK planet sees an opportunity to partner with new distributors to expand SCINIC's global footprint.
Enhanced Shopping: Delivering value with Hybrid ProximityMichael Lesniak
SK planet is South Korea's largest mobile operator and digital platform. It offers various offline-to-online services including Syrup Wallet (digital wallet), OK Cashbag (coalition loyalty program), Gifticon (digital gifting platform), and Syrup Pay (web-based payment service). SK planet enhances these services through hybrid proximity technology to deliver value to customers and merchants. It aims to close the customer journey loop to engage customers with favorite brands anywhere.
Investors and Companies should look to East Africa for scalable products, quality entrepreneurs, with a large market opportunity. Statistics and Companies based on 2015 data.
AI and Data Privacy in 2025: Global TrendsInData Labs
In this infographic, we explore how businesses can implement effective governance frameworks to address AI data privacy. Understanding it is crucial for developing effective strategies that ensure compliance, safeguard customer trust, and leverage AI responsibly. Equip yourself with insights that can drive informed decision-making and position your organization for success in the future of data privacy.
This infographic contains:
-AI and data privacy: Key findings
-Statistics on AI data privacy in the today’s world
-Tips on how to overcome data privacy challenges
-Benefits of AI data security investments.
Keep up-to-date on how AI is reshaping privacy standards and what this entails for both individuals and organizations.
TrustArc Webinar: Consumer Expectations vs Corporate Realities on Data Broker...TrustArc
Most consumers believe they’re making informed decisions about their personal data—adjusting privacy settings, blocking trackers, and opting out where they can. However, our new research reveals that while awareness is high, taking meaningful action is still lacking. On the corporate side, many organizations report strong policies for managing third-party data and consumer consent yet fall short when it comes to consistency, accountability and transparency.
This session will explore the research findings from TrustArc’s Privacy Pulse Survey, examining consumer attitudes toward personal data collection and practical suggestions for corporate practices around purchasing third-party data.
Attendees will learn:
- Consumer awareness around data brokers and what consumers are doing to limit data collection
- How businesses assess third-party vendors and their consent management operations
- Where business preparedness needs improvement
- What these trends mean for the future of privacy governance and public trust
This discussion is essential for privacy, risk, and compliance professionals who want to ground their strategies in current data and prepare for what’s next in the privacy landscape.
Hands On: Create a Lightning Aura Component with force:RecordDataLynda Kane
Slide Deck from the 3/26/2020 virtual meeting of the Cleveland Developer Group presentation on creating a Lightning Aura Component using force:RecordData.
How Can I use the AI Hype in my Business Context?Daniel Lehner
𝙄𝙨 𝘼𝙄 𝙟𝙪𝙨𝙩 𝙝𝙮𝙥𝙚? 𝙊𝙧 𝙞𝙨 𝙞𝙩 𝙩𝙝𝙚 𝙜𝙖𝙢𝙚 𝙘𝙝𝙖𝙣𝙜𝙚𝙧 𝙮𝙤𝙪𝙧 𝙗𝙪𝙨𝙞𝙣𝙚𝙨𝙨 𝙣𝙚𝙚𝙙𝙨?
Everyone’s talking about AI but is anyone really using it to create real value?
Most companies want to leverage AI. Few know 𝗵𝗼𝘄.
✅ What exactly should you ask to find real AI opportunities?
✅ Which AI techniques actually fit your business?
✅ Is your data even ready for AI?
If you’re not sure, you’re not alone. This is a condensed version of the slides I presented at a Linkedin webinar for Tecnovy on 28.04.2025.
Procurement Insights Cost To Value Guide.pptxJon Hansen
Procurement Insights integrated Historic Procurement Industry Archives, serves as a powerful complement — not a competitor — to other procurement industry firms. It fills critical gaps in depth, agility, and contextual insight that most traditional analyst and association models overlook.
Learn more about this value- driven proprietary service offering here.
Technology Trends in 2025: AI and Big Data AnalyticsInData Labs
At InData Labs, we have been keeping an ear to the ground, looking out for AI-enabled digital transformation trends coming our way in 2025. Our report will provide a look into the technology landscape of the future, including:
-Artificial Intelligence Market Overview
-Strategies for AI Adoption in 2025
-Anticipated drivers of AI adoption and transformative technologies
-Benefits of AI and Big data for your business
-Tips on how to prepare your business for innovation
-AI and data privacy: Strategies for securing data privacy in AI models, etc.
Download your free copy nowand implement the key findings to improve your business.
Semantic Cultivators : The Critical Future Role to Enable AIartmondano
By 2026, AI agents will consume 10x more enterprise data than humans, but with none of the contextual understanding that prevents catastrophic misinterpretations.
What is Model Context Protocol(MCP) - The new technology for communication bw...Vishnu Singh Chundawat
The MCP (Model Context Protocol) is a framework designed to manage context and interaction within complex systems. This SlideShare presentation will provide a detailed overview of the MCP Model, its applications, and how it plays a crucial role in improving communication and decision-making in distributed systems. We will explore the key concepts behind the protocol, including the importance of context, data management, and how this model enhances system adaptability and responsiveness. Ideal for software developers, system architects, and IT professionals, this presentation will offer valuable insights into how the MCP Model can streamline workflows, improve efficiency, and create more intuitive systems for a wide range of use cases.
The Evolution of Meme Coins A New Era for Digital Currency ppt.pdfAbi john
Analyze the growth of meme coins from mere online jokes to potential assets in the digital economy. Explore the community, culture, and utility as they elevate themselves to a new era in cryptocurrency.
Leading AI Innovation As A Product Manager - Michael JidaelMichael Jidael
Unlike traditional product management, AI product leadership requires new mental models, collaborative approaches, and new measurement frameworks. This presentation breaks down how Product Managers can successfully lead AI Innovation in today's rapidly evolving technology landscape. Drawing from practical experience and industry best practices, I shared frameworks, approaches, and mindset shifts essential for product leaders navigating the unique challenges of AI product development.
In this deck, you'll discover:
- What AI leadership means for product managers
- The fundamental paradigm shift required for AI product development.
- A framework for identifying high-value AI opportunities for your products.
- How to transition from user stories to AI learning loops and hypothesis-driven development.
- The essential AI product management framework for defining, developing, and deploying intelligence.
- Technical and business metrics that matter in AI product development.
- Strategies for effective collaboration with data science and engineering teams.
- Framework for handling AI's probabilistic nature and setting stakeholder expectations.
- A real-world case study demonstrating these principles in action.
- Practical next steps to begin your AI product leadership journey.
This presentation is essential for Product Managers, aspiring PMs, product leaders, innovators, and anyone interested in understanding how to successfully build and manage AI-powered products from idea to impact. The key takeaway is that leading AI products is about creating capabilities (intelligence) that continuously improve and deliver increasing value over time.
Big Data Analytics Quick Research Guide by Arthur MorganArthur Morgan
This is a Quick Research Guide (QRG).
QRGs include the following:
- A brief, high-level overview of the QRG topic.
- A milestone timeline for the QRG topic.
- Links to various free online resource materials to provide a deeper dive into the QRG topic.
- Conclusion and a recommendation for at least two books available in the SJPL system on the QRG topic.
QRGs planned for the series:
- Artificial Intelligence QRG
- Quantum Computing QRG
- Big Data Analytics QRG
- Spacecraft Guidance, Navigation & Control QRG (coming 2026)
- UK Home Computing & The Birth of ARM QRG (coming 2027)
Any questions or comments?
- Please contact Arthur Morgan at [email protected].
100% human made.
Enhancing ICU Intelligence: How Our Functional Testing Enabled a Healthcare I...Impelsys Inc.
Impelsys provided a robust testing solution, leveraging a risk-based and requirement-mapped approach to validate ICU Connect and CritiXpert. A well-defined test suite was developed to assess data communication, clinical data collection, transformation, and visualization across integrated devices.
"Rebranding for Growth", Anna VelykoivanenkoFwdays
Since there is no single formula for rebranding, this presentation will explore best practices for aligning business strategy and communication to achieve business goals.
"Rebranding for Growth", Anna VelykoivanenkoFwdays
Ai in e commerce (public)
1. Artificial Intelligence
in eCommerce
1. Why everyone is talking about Artificial Intelligence?
2. What is Artificial Intelligence?
3. What are some examples of Artificial Intelligence in eCommerce?
3. ??
1. Why is everyone talking about Artificial Intelligence?
Data Processing is driving a new Industrial Revolution
There are four generally recognized “industrial revolutions” in human history….
1760~1840
Third Industrial
Revolution
Fourth Industrial
Revolution
First Industrial
Revolution
Second Industrial
Revolution
Steam Engine
Railroads
Manufacturing
1870~1914 1961~2000 2011~….
Electrification
Assembly Line
Mass Production
Semiconductors
Computing
The Internet
Cloud Computing
Internet of Things
Artificial Intelligence
Blockchain
etc…
the first machine age the second machine age
4. These revolutions have changed civilization dramatically
Historically the primary concerns for human civilization
warfamine plague
France, 1692-1694
15% of population
dies of starvation
China, 1958-1962
36,000,000 people
die of starvation
Worldwide, 2010
1,000,000 people
die of famine and
malnutrition
3,000,000 people
die of obesity
Mexico, 1520-1580
Disease decimates
population from
22 to 2 million
Worldwide, 1918
50~100M people
die of “Spanish Flu”
Worldwide, 2015
70% of deaths
worldwide caused
by NCDs
Diseases related to
diet and old age
Agricultural Society
Est. 15% of deaths
caused by violence
WW2, 1939-1945
50~80M people die
during WW2
Worldwide, 2015
620,000 people die
from human violence
“Sugar is more
dangerous than
gunpowder.”
5%
1. Why is everyone talking about Artificial Intelligence?
5. Famine and Disease are becoming things of the past
Death by Noncommunicable DiseaseLife Expectancy Worldwide
In much of the world, diet or old age kills more people than starvation or sickness…
1. Why is everyone talking about Artificial Intelligence?
6. Fewer people are being killed due to wars
War between “Great Powers” Battle Deaths
With any luck, great powers will consistently avoid war in the future…
1. Why is everyone talking about Artificial Intelligence?
7. The Steam Engine initiated drastic improvements
Invention
of the
Steam Engine
1. Why is everyone talking about Artificial Intelligence?
8. Computing technologies are initiating a new paradigm shift
Many Dimension of Moore’s Law
1. Why is everyone talking about Artificial Intelligence?
9. This is what that looks like….
ASCI Red PS3
1.8 teraflops in 1997 1.8 teraflops in 2006
$55,000,000 $500
1. Why is everyone talking about Artificial Intelligence?
10. What a difference ten years can make….
1. Why is everyone talking about Artificial Intelligence?
11. Or put it another way…
0
15
30
45
60
75
90
ASCI Red IBM Roadrunner NRCPC Sunway
90
10.001
Petaflops
1997 2008 2016
Estimated Petaflops = 1000
Human Brain
1. Why is everyone talking about Artificial Intelligence?
13. Enable machines to perform similar cognitive tasks as people
Artificial Intelligence covers several areas…
2. What is Artificial Intelligence?
•Curated Knowledge
•Machine Learning
•Data Mining
John McCarthy Marvin Minsky Andrew Ng Yann LeCun Geoff Hinton
… of data science relevant to eCommerce.
14. Most people are interested in Machine Learning…
2. What is Artificial Intelligence?
Supervised Learning
Unsupervised Learning
Reinforcement Learning
Artificial Neural Networks a.k.a.
Deep Learning
Learning Technique Description
Machine should accomplish a discrete task based
on human observations (e.g historical data).
Machine should rely on clustering data and
modifying its algorithms without human feedback
Machine should rely on reinforcement algorithms
to achieve a high grade on a task
Process data through layers of analysis using
“shallow” algorithms
15. Machines can learn to make predictions or classifications
2. What is Artificial Intelligence?
Supervised Learning
Type of Learning Description
Machine should accomplish a discrete task based
on human observations (e.g historical data).
Example…
Linear Regression Logistic Regression Support Vector Machine
Predict Cost (or
Revenue) of Ad
Units
Identify fraud,
spam, other
binary classes
Minimize
impact of data
anomalies
16. Machines can learn to identify clusters within data
2. What is Artificial Intelligence?
Unsupervised Learning
Type of Learning Description
Example…
Common clustering algorithms are: k-Means, k-Nearest Neighbor
Machine should rely on clustering data and
modifying its algorithms without human feedback
17. Machines can learn to understand an environment
2. What is Artificial Intelligence?
Reinforcement Learning
Type of Learning Description
Machine should rely on reinforcement algorithms
to achieve a high grade on a task
•“Semi-Supervised” and value of the output is unknown
•Understand complex situations where outcomes depend on many variables
•No direct oversight:
✓ machine is programmed with reinforcement algorithms
✓ each performance is graded, machine repeats until it achieves high grade
Example…
18. Machines can learn to interpret and react like we do
2. What is Artificial Intelligence?
Artificial Neural Networks a.k.a.
Deep Learning
Type of Learning Description
Process data through layers of analysis using
“shallow” algorithms
Artificial Neural Network (ANN)
•Each neuron contains a “shallow” algorithm
•Each neuron has a weight which is updated as
data is input to the network multiple iterations
•As information ascends through the network is
becomes less abstract and more specific
19. 2. What is Artificial Intelligence?
Types of Neural Networks
20. 3. What are some examples of A.I. in eCommerce?
21. 3. What are some examples of A.I. in eCommerce?
Product Search
Pricing
Personalization
Recommendations
Customer Service
Automated Orders
Shopping Agents Operations
Inventory
Management
Zero UI
Marketing
PaymentFulfillment
Merchandizing
Storage
Sales
22. 3. What are some examples of A.I. in eCommerce?
23. 3. What are some examples of A.I. in eCommerce?
24. 3. What are some examples of A.I. in eCommerce?
25. 3. What are some examples of A.I. in eCommerce?