The document discusses IBM's strategy for artificial intelligence (AI) for business, called AI+. It outlines how AI can boost global GDP by 14% by 2030 by increasing productivity and consumer demand. IBM's strategy focuses on using AI to automate tasks, optimize workflows, and have AI orchestrate work. This involves collecting and organizing data, adding AI to applications, replacing workflows, automating tasks, and having AI orchestrate workflows. The strategy involves using traditional and generative AI models within an enterprise AI layer and intelligent process layer to dynamically optimize business processes. IBM's WatsonX platform is presented as an enterprise-ready solution for targeted generative AI and data services to help businesses implement this strategy.
The numbers tell the story: 84% of C-suite executives believe they must leverage artificial intelligence (AI) to achieve their growth objectives, yet 76% report they struggle with how to scale. With the stakes higher than ever, what can we learn from companies that are successfully scaling AI, achieving nearly 3X the return on investments and an average 32% premium on key financial valuation metrics?
To answer that question, Accenture conducted a landmark global study involving 1,500 C-suite executives from organizations across 16 industries. The aim: Help companies progress on their AI journey, from one-off AI experimentation to gaining a robust organization-wide capability that acts as a source of competitive agility and growth.
Read the full report:
http://www.accenture.com/AI-Built-to-Scale-Slideshare
The UAE AI Strategy: Building Intelligent EnterprisesSaeed Al Dhaheri
This presentation was presented at the CIOMajlis meeting and highlights the UAE AI strategy and how to build Intelligent AI-driven Enterprises. Examples of some AI applications in the UAE public sector were highlighted.
🔹How will AI-based content-generating tools change your mission and products?
🔹This complimentary webinar [ON-DEMAND] explores multiple use cases that drive adoption in their early adopter customer base to provide product leaders with insights into the future of generative AI-powered businesses, and the potential generative AI holds for driving innovation and improving business processes.
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
Solve for X with AI: a VC view of the Machine Learning & AI landscapeEd Fernandez
What you'll get from this deck
1. The M&A race for AI: by the numbers
2. Watch out! hype ahead: definitions & disclaimers
3. Machine Learning drivers: why is Machine Learning a ‘thing’ now (vs before)
4. Venture Capital: forming an industry, the AI/ML landscape
5. The One Hundred (+13) AI startups to watch in the Enterprise
6. The great Enterprise pivot: applying Machine Learning at scale
7. - where to go next -
This presentation discusses matters of AI and machine learning. This presentation was given during the ITU-T workshop on Machine Learning for 5G and beyond, held at ITU HQ in Geneva, Switzerland on 29 Jan 18. More information on the workshop can be found here: https://www.itu.int/en/ITU-T/Workshops-and-Seminars/20180129/Pages/default.aspx
Join our upcoming forums and workshops here: https://www.itu.int/en/ITU-T/Workshops-and-Seminars/Pages/default.aspx
The numbers tell the story: 84% of C-suite executives believe they must leverage artificial intelligence (AI) to achieve their growth objectives, yet 76% report they struggle with how to scale. With the stakes higher than ever, what can we learn from companies that are successfully scaling AI, achieving nearly 3X the return on investments and an average 32% premium on key financial valuation metrics?
To answer that question, Accenture conducted a landmark global study involving 1,500 C-suite executives from organizations across 16 industries. The aim: Help companies progress on their AI journey, from one-off AI experimentation to gaining a robust organization-wide capability that acts as a source of competitive agility and growth.
Read the full report:
http://www.accenture.com/AI-Built-to-Scale-Slideshare
The UAE AI Strategy: Building Intelligent EnterprisesSaeed Al Dhaheri
This presentation was presented at the CIOMajlis meeting and highlights the UAE AI strategy and how to build Intelligent AI-driven Enterprises. Examples of some AI applications in the UAE public sector were highlighted.
🔹How will AI-based content-generating tools change your mission and products?
🔹This complimentary webinar [ON-DEMAND] explores multiple use cases that drive adoption in their early adopter customer base to provide product leaders with insights into the future of generative AI-powered businesses, and the potential generative AI holds for driving innovation and improving business processes.
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
Solve for X with AI: a VC view of the Machine Learning & AI landscapeEd Fernandez
What you'll get from this deck
1. The M&A race for AI: by the numbers
2. Watch out! hype ahead: definitions & disclaimers
3. Machine Learning drivers: why is Machine Learning a ‘thing’ now (vs before)
4. Venture Capital: forming an industry, the AI/ML landscape
5. The One Hundred (+13) AI startups to watch in the Enterprise
6. The great Enterprise pivot: applying Machine Learning at scale
7. - where to go next -
This presentation discusses matters of AI and machine learning. This presentation was given during the ITU-T workshop on Machine Learning for 5G and beyond, held at ITU HQ in Geneva, Switzerland on 29 Jan 18. More information on the workshop can be found here: https://www.itu.int/en/ITU-T/Workshops-and-Seminars/20180129/Pages/default.aspx
Join our upcoming forums and workshops here: https://www.itu.int/en/ITU-T/Workshops-and-Seminars/Pages/default.aspx
Thabo Ndlela- Leveraging AI for enhanced Customer Service and Experienceitnewsafrica
Thabo Ndlela, from Accenture, delivered a keynote on Leveraging AI for enhanced Customer Service and Experience at Digital Finance Africa 2023 on the 2nd of August 2023.
How do OpenAI GPT Models Work - Misconceptions and Tips for DevelopersIvo Andreev
Have you ever wondered why GPT models work? Do you ask questions like:
◉ How does GPT work? Why does the same problem receive different answers for different users? Is there a way to improve explainability? ◉ Can GPT model provide its sources? Why does Bing chat work differently? What are my ways to have better performance and improve completions? ◉ How can I work with data in my enterprise? What practical business cases could a generative AI model fit solving?
If you are tired of sessions just scratching the surface of OpenAI GPT, this one will go deeper and answer questions like why, why not and how.
Key Terms; ChatGPT Enterprise; Top Questions; Enterprise Data; Azure Search; Functions; Embeddings; Context Encoding; General Intelligence; Emerging Abilities; Chain of Thought; Plugins; Multimodal with DALL-E; Project Florence
A Framework for Navigating Generative Artificial Intelligence for EnterpriseRocketSource
Generative AI has dominated the headlines recently, which has caused many enterprises to put a full stop to implementing this technology until they can understand what’s behind the glitz and glamour. What if we shifted the conversation? What if the focus became a fresh, incremental approach to embracing the opportunities with generative artificial intelligence to keep organizations moving upward on the S Curve of Growth?
Brands stay relevant and solve complex problems by testing the barometer for one thing — will a new strategy, tool, or piece of technology improve humanity?
Human connections are more vital than using shiny new tools or technology. As your teams work to steer clear of the temptation to do what everyone else is doing in uniform, this post will highlight how to stand out, compete, and do so with less risk in today’s world of generative AI overload.
Unlocking the Power of Generative AI An Executive's Guide.pdfPremNaraindas1
Generative AI is here, and it can revolutionize your business. With its powerful capabilities, this technology can help companies create more efficient processes, unlock new insights from data, and drive innovation. But how do you make the most of these opportunities?
This guide will provide you with the information and resources needed to understand the ins and outs of Generative AI, so you can make informed decisions and capitalize on the potential. It covers important topics such as strategies for leveraging large language models, optimizing MLOps processes, and best practices for building with Generative AI.
AI for an intelligent cloud and intelligent edge: Discover, deploy, and manag...James Serra
Discover, manage, deploy, monitor – rinse and repeat. In this session we show how Azure Machine Learning can be used to create the right AI model for your challenge and then easily customize it using your development tools while relying on Azure ML to optimize them to run in hardware accelerated environments for the cloud and the edge using FPGAs and Neural Network accelerators. We then show you how to deploy the model to highly scalable web services and nimble edge applications that Azure can manage and monitor for you. Finally, we illustrate how you can leverage the model telemetry to retrain and improve your content.
A Glimpse Into the Future of Data Science - What's Next for AI, Big Data & Ma...Pangea.ai
We are living in the era of "the fourth industrial revolution". How did we get here? Read this presentation to explore current application trends in Artificial Intelligence (AI,) The Internet of Things (IoT), Big Data, and Machine Learning (ML) technology. Also, to discover the future implications of big data in our lives.
Read the original article here: https://www.pangea.ai/data-science-resources/future-of-data-science/
Work with a data science expert at Pangea: https://www.pangea.ai/
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
This talk overviews my background as a female data scientist, introduces many types of generative AI, discusses potential use cases, highlights the need for representation in generative AI, and showcases a few tools that currently exist.
GENERATIVE AI, THE FUTURE OF PRODUCTIVITYAndre Muscat
Discuss the impact and opportunity of using Generative AI to support your development and creative teams
* Explore business challenges in content creation
* Cost-per-unit of different types of content
* Use AI to reduce cost-per-unit
* New partnerships being formed that will have a material impact on the way we search and engage with content
Part 4 of a 9 Part Research Series named "What matters in AI" published on www.andremuscat.com
How Deloitte Uses AI to Simplify Reporting and Increase ValueAmazon Web Services
In this webinar, you’ll learn how Deloitte, a multinational consultancy, solves client pain points around employee efficiency, scale, regulatory compliance, and customer engagement using Quill, a NLG solution created by Narrative Science and deployed on AWS. You’ll learn how you can easily get started with artificial intelligence on AWS to derive deeper insights, improve operational efficiency, enhance customer experiences, and meet compliance requirements.
Join our webinar to learn:
- How NLG can solve problems around internal reporting, operational efficiency, and regulatory compliance
- How Deloitte delivered transformative solutions both internally and to clients on AWS while saving over $600K
- How to get started with NLG in your organization
Generative AI: Past, Present, and Future – A Practitioner's PerspectiveHuahai Yang
Generative AI: Past, Present, and Future – A Practitioner's Perspective
As the academic realm grapples with the profound implications of generative AI
and related applications like ChatGPT, I will present a grounded view from my
experience as a practitioner. Starting with the origins of neural networks in
the fields of logic, psychology, and computer science, I trace its history and
align it within the wider context of the pursuit of artificial intelligence.
This perspective will also draw parallels with historical developments in
psychology. Against this backdrop, I chart a proposed trajectory for the future.
Finally, I provide actionable insights for both academics and enterprising
individuals in the field.
In this session, you'll get all the answers about how ChatGPT and other GPT-X models can be applied to your current or future project. First, we'll put in order all the terms – OpenAI, GPT-3, ChatGPT, Codex, Dall-E, etc., and explain why Microsoft and Azure are often mentioned in this context. Then, we'll go through the main capabilities of the Azure OpenAI and respective usecases that might inspire you to either optimize your product or build a completely new one.
Artificial Intelligence for Product Managers by former Yahoo! PMProduct School
Jobs requiring artificial intelligence skills in the US has grown 450% in the last five years. Corporations are seeking relentlessly for product leaders who can utilize AI technologies on their products and services to improve the company’s bottom line or top line. It's called the Fourth Industrial Revolution, and it is happening right here, right now.
However, as a Product Manager, how do you gain the necessary knowledge to analyze, understand, plan, and design products based on artificial intelligence technologies? Since you cannot get a college degree in AI Product Management, how do you adapt to this rapid change? In this talk, Adnan helped to answer these questions.
Generative AI models, such as ChatGPT and Stable Diffusion, can create new and original content like text, images, video, audio, or other data from simple prompts, as well as handle complex dialogs and reason about problems with or without images. These models are disrupting traditional technologies, from search and content creation to automation and problem solving, and are fundamentally shaping the future user interface to computing devices. Generative AI can apply broadly across industries, providing significant enhancements for utility, productivity, and entertainment. As generative AI adoption grows at record-setting speeds and computing demands increase, on-device and hybrid processing are more important than ever. Just like traditional computing evolved from mainframes to today’s mix of cloud and edge devices, AI processing will be distributed between them for AI to scale and reach its full potential.
In this presentation you’ll learn about:
- Why on-device AI is key
- Full-stack AI optimizations to make on-device AI possible and efficient
- Advanced techniques like quantization, distillation, and speculative decoding
- How generative AI models can be run on device and examples of some running now
- Qualcomm Technologies’ role in scaling on-device generative AI
Transforming your business through data driven insights and action with AzureInovar Tech
A data-driven culture is critical for today’s businesses to thrive. Azure analytics services enable you to use the full breadth of your data assets to help build transformative and secure analytical solutions at enterprise scale.
Advanced Analytics and Artificial Intelligence - Transforming Your Business T...David J Rosenthal
Recent advances in AI have incredible potential and they are already fundamentally changing our lives in ways we couldn’t have imagined even five years ago. And yet, AI is also probably one of the least understood technological breakthroughs in modern times. Come to this event to learn about breakthrough advances in AI and the power of the cloud, and how Microsoft provides a flexible platform for you to infuse intelligence into your own products and services. Microsoft empowers you to transform your business, uniquely combining AI innovation with a proven Enterprise platform, deriving intelligence from a wide range of data relevant to your business no matter where it lives.
Thabo Ndlela- Leveraging AI for enhanced Customer Service and Experienceitnewsafrica
Thabo Ndlela, from Accenture, delivered a keynote on Leveraging AI for enhanced Customer Service and Experience at Digital Finance Africa 2023 on the 2nd of August 2023.
How do OpenAI GPT Models Work - Misconceptions and Tips for DevelopersIvo Andreev
Have you ever wondered why GPT models work? Do you ask questions like:
◉ How does GPT work? Why does the same problem receive different answers for different users? Is there a way to improve explainability? ◉ Can GPT model provide its sources? Why does Bing chat work differently? What are my ways to have better performance and improve completions? ◉ How can I work with data in my enterprise? What practical business cases could a generative AI model fit solving?
If you are tired of sessions just scratching the surface of OpenAI GPT, this one will go deeper and answer questions like why, why not and how.
Key Terms; ChatGPT Enterprise; Top Questions; Enterprise Data; Azure Search; Functions; Embeddings; Context Encoding; General Intelligence; Emerging Abilities; Chain of Thought; Plugins; Multimodal with DALL-E; Project Florence
A Framework for Navigating Generative Artificial Intelligence for EnterpriseRocketSource
Generative AI has dominated the headlines recently, which has caused many enterprises to put a full stop to implementing this technology until they can understand what’s behind the glitz and glamour. What if we shifted the conversation? What if the focus became a fresh, incremental approach to embracing the opportunities with generative artificial intelligence to keep organizations moving upward on the S Curve of Growth?
Brands stay relevant and solve complex problems by testing the barometer for one thing — will a new strategy, tool, or piece of technology improve humanity?
Human connections are more vital than using shiny new tools or technology. As your teams work to steer clear of the temptation to do what everyone else is doing in uniform, this post will highlight how to stand out, compete, and do so with less risk in today’s world of generative AI overload.
Unlocking the Power of Generative AI An Executive's Guide.pdfPremNaraindas1
Generative AI is here, and it can revolutionize your business. With its powerful capabilities, this technology can help companies create more efficient processes, unlock new insights from data, and drive innovation. But how do you make the most of these opportunities?
This guide will provide you with the information and resources needed to understand the ins and outs of Generative AI, so you can make informed decisions and capitalize on the potential. It covers important topics such as strategies for leveraging large language models, optimizing MLOps processes, and best practices for building with Generative AI.
AI for an intelligent cloud and intelligent edge: Discover, deploy, and manag...James Serra
Discover, manage, deploy, monitor – rinse and repeat. In this session we show how Azure Machine Learning can be used to create the right AI model for your challenge and then easily customize it using your development tools while relying on Azure ML to optimize them to run in hardware accelerated environments for the cloud and the edge using FPGAs and Neural Network accelerators. We then show you how to deploy the model to highly scalable web services and nimble edge applications that Azure can manage and monitor for you. Finally, we illustrate how you can leverage the model telemetry to retrain and improve your content.
A Glimpse Into the Future of Data Science - What's Next for AI, Big Data & Ma...Pangea.ai
We are living in the era of "the fourth industrial revolution". How did we get here? Read this presentation to explore current application trends in Artificial Intelligence (AI,) The Internet of Things (IoT), Big Data, and Machine Learning (ML) technology. Also, to discover the future implications of big data in our lives.
Read the original article here: https://www.pangea.ai/data-science-resources/future-of-data-science/
Work with a data science expert at Pangea: https://www.pangea.ai/
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
This talk overviews my background as a female data scientist, introduces many types of generative AI, discusses potential use cases, highlights the need for representation in generative AI, and showcases a few tools that currently exist.
GENERATIVE AI, THE FUTURE OF PRODUCTIVITYAndre Muscat
Discuss the impact and opportunity of using Generative AI to support your development and creative teams
* Explore business challenges in content creation
* Cost-per-unit of different types of content
* Use AI to reduce cost-per-unit
* New partnerships being formed that will have a material impact on the way we search and engage with content
Part 4 of a 9 Part Research Series named "What matters in AI" published on www.andremuscat.com
How Deloitte Uses AI to Simplify Reporting and Increase ValueAmazon Web Services
In this webinar, you’ll learn how Deloitte, a multinational consultancy, solves client pain points around employee efficiency, scale, regulatory compliance, and customer engagement using Quill, a NLG solution created by Narrative Science and deployed on AWS. You’ll learn how you can easily get started with artificial intelligence on AWS to derive deeper insights, improve operational efficiency, enhance customer experiences, and meet compliance requirements.
Join our webinar to learn:
- How NLG can solve problems around internal reporting, operational efficiency, and regulatory compliance
- How Deloitte delivered transformative solutions both internally and to clients on AWS while saving over $600K
- How to get started with NLG in your organization
Generative AI: Past, Present, and Future – A Practitioner's PerspectiveHuahai Yang
Generative AI: Past, Present, and Future – A Practitioner's Perspective
As the academic realm grapples with the profound implications of generative AI
and related applications like ChatGPT, I will present a grounded view from my
experience as a practitioner. Starting with the origins of neural networks in
the fields of logic, psychology, and computer science, I trace its history and
align it within the wider context of the pursuit of artificial intelligence.
This perspective will also draw parallels with historical developments in
psychology. Against this backdrop, I chart a proposed trajectory for the future.
Finally, I provide actionable insights for both academics and enterprising
individuals in the field.
In this session, you'll get all the answers about how ChatGPT and other GPT-X models can be applied to your current or future project. First, we'll put in order all the terms – OpenAI, GPT-3, ChatGPT, Codex, Dall-E, etc., and explain why Microsoft and Azure are often mentioned in this context. Then, we'll go through the main capabilities of the Azure OpenAI and respective usecases that might inspire you to either optimize your product or build a completely new one.
Artificial Intelligence for Product Managers by former Yahoo! PMProduct School
Jobs requiring artificial intelligence skills in the US has grown 450% in the last five years. Corporations are seeking relentlessly for product leaders who can utilize AI technologies on their products and services to improve the company’s bottom line or top line. It's called the Fourth Industrial Revolution, and it is happening right here, right now.
However, as a Product Manager, how do you gain the necessary knowledge to analyze, understand, plan, and design products based on artificial intelligence technologies? Since you cannot get a college degree in AI Product Management, how do you adapt to this rapid change? In this talk, Adnan helped to answer these questions.
Generative AI models, such as ChatGPT and Stable Diffusion, can create new and original content like text, images, video, audio, or other data from simple prompts, as well as handle complex dialogs and reason about problems with or without images. These models are disrupting traditional technologies, from search and content creation to automation and problem solving, and are fundamentally shaping the future user interface to computing devices. Generative AI can apply broadly across industries, providing significant enhancements for utility, productivity, and entertainment. As generative AI adoption grows at record-setting speeds and computing demands increase, on-device and hybrid processing are more important than ever. Just like traditional computing evolved from mainframes to today’s mix of cloud and edge devices, AI processing will be distributed between them for AI to scale and reach its full potential.
In this presentation you’ll learn about:
- Why on-device AI is key
- Full-stack AI optimizations to make on-device AI possible and efficient
- Advanced techniques like quantization, distillation, and speculative decoding
- How generative AI models can be run on device and examples of some running now
- Qualcomm Technologies’ role in scaling on-device generative AI
Transforming your business through data driven insights and action with AzureInovar Tech
A data-driven culture is critical for today’s businesses to thrive. Azure analytics services enable you to use the full breadth of your data assets to help build transformative and secure analytical solutions at enterprise scale.
Advanced Analytics and Artificial Intelligence - Transforming Your Business T...David J Rosenthal
Recent advances in AI have incredible potential and they are already fundamentally changing our lives in ways we couldn’t have imagined even five years ago. And yet, AI is also probably one of the least understood technological breakthroughs in modern times. Come to this event to learn about breakthrough advances in AI and the power of the cloud, and how Microsoft provides a flexible platform for you to infuse intelligence into your own products and services. Microsoft empowers you to transform your business, uniquely combining AI innovation with a proven Enterprise platform, deriving intelligence from a wide range of data relevant to your business no matter where it lives.
Building Intelligent Apps with MongoDB and Google Cloud - Jane FineMongoDB
Intelligent apps are emerging as the next frontier in analytics and application development. Learn how to build intelligent apps on MongoDB powered by Google Cloud with TensorFlow for machine learning and DialogFlow for artificial intelligence. Get your developers and data scientists to finally work together to build applications that understand your customer, automate their tasks, and provide knowledge and decision support.
Achieving Business Transformation with UiPath RPACelonis
UiPath delivers the most advanced Enterprise RPA Platform, built for business and IT. As you strive to benefit from the opportunities of the “Automation First” era, your digital transformation can be accelerated here. And UiPath RPA is constantly adding new AI skills that can be applied to more complex use cases. Join Christian Berg, Director of AI Product Management, and Bella Liu, AI Partnership Lead to learn how UiPath RPA is enabling robots to address process automation end to end with new AI skills powered by Celonis.
Presenters:
Bella Liu, AI Partnership Lead, UiPath
Christian Berg, Director of AI Product Management, UiPath
re:cap Generative AI journey with BedrockPhilipBasford
Wherever you are on your Generative AI journey — Amazon Bedrock allows you to rapidly prototype Generative AI concepts, using the latest Foundational Models. This session also included architectures to accelerate your prototype into a real-world GenAI solution using LLMOps. Providing the safeguards to keep your data private & secure, handle any regulatory compliance and responsibility requirements.
Every business is looking for a game-changer in data science, machine learning, and AI. Most organizations are also looking for ways to tap into open-source and commercial data science tools such as Python, RStudio, Apache Spark, Jupyter, and Zeppelin notebooks, to accelerate predictive and machine learning model building and deployment while leveraging the scale, security and governance of the Hortonworks Data Platform and other commercial platforms.
Ana Maria Echeverri will demonstrate how to accelerate data science, machine learning, and deep learning workflows by using IBM Watson Studio, an integrated environment for data scientists, application developers, and subject matter experts. This suite of tools allows to collaboratively connect to data, wrangle that data and use it to build, train and deploy models at scale while using Open Source skills (i.e.: Python) and expanding into cognitive capabilities through access to Watson APIs to build AI-powered applications. If you love Python and want to tap into the power of IBM Watson, this is the session for you.
IBM i & digital transformation - Presentation & basic demo
IBM Watson Studio, IBM DSX Local w/ Open Source (Spark) & IBM Technology (OpenPower, CAPI, NVLINK)
Devoteam itsmf 2021 - from business automation to continuous value-driven i...itSMF Belgium
The race for enterprise business process digitalization is raging. IT is often left behind as enterprise budgets for innovation are shifting towards business teams.
During this session, we will present the challenges and our field-tested approaches to catch-up and how to take this opportunity to create new app factories. All the while using low-code and RPA platforms.
You will discover how to capture business demands, and create an operating model for your IT department to stay in control of the applications being deployed, while bringing value at speed.
CIO Leadership Summit 2018 - From Digital to Intelligent EnterprisePhilippe Nemery
Presentation given at the MasterClass of the CIO Leadership Summit in Brussels. I present here the transformation from the Digital Enterprise to the Intelligent Enterprise where tasks will be automated thanks to Machine Learning and Artificial Intelligence so that the employees can focus on high end value tasks.
http://www.cioleadershipsummit.net/
Artificial Intelligence is the ability of machines to seemingly think and learn just like Human brain. It enables Machine to learn by themselves using the provided data and make accurate prediction.
How could OpenAI, a small organization of just 200 employees, managed to shake the foundations of large companies like Google and Meta? Everyone dreams about being a unicorn – having razor sharp focus, high talent-density , rapid speed of innovation but in reality, even startups end up becoming slow organizations very quickly. Why does this happen?
Big Data Analytics offers a nearly endless source of business and informational insight, that can lead to operational improvement and new opportunities for companies to provide unrealized revenue across almost every industry.
Empowering you - Power BI, Power Platform & AI BuilderRui Quintino
Slides for the "Microsoft Empowering You" webinar about Power BI, Power Apps, Power Automate & AI Builder by DevScope.
Explore how Power Platform & AI Builder can enrich your Power BI experience.
Watch the full session at https://youtu.be/IhwiESvFaxg
(English subtitles available)
This presentation was made on June 16, 2020.
A recording of the presentation can be viewed here: https://youtu.be/khjW1t0gtSA
AI is unlocking new potential for every enterprise. Organizations are using AI and machine learning technology to inform business decisions, predict potential issues, and provide more efficient, customized customer experiences. The results can enable a competitive edge for the business.
H2O.ai is a visionary leader in AI and machine learning and is on a mission to democratize AI for everyone. We believe that every company can become an AI company, not just the AI Superpowers. We are empowering companies with our leading AI and Machine Learning platforms, our expertise, experience and training to embark on their own AI journey to become AI companies themselves. All companies in all industries can participate in this AI Transformation.
Tune into this virtual meetup to learn how companies are transforming their business with the power of AI and where to start.
About Parul Pandey:
Parul is a Data Science Evangelist here at H2O.ai. She combines Data Science , evangelism and community in her work. Her emphasis is to spread the information about H2O and Driverless AI to as many people as possible, She is also an active writer and has contributed towards various national and international publications.
Similar to Reading the IBM AI Strategy for Business (20)
HumanTechBiota is acting as the human microbiota
(the collective microorganisms that resides symbiotically in our bodies) having an increasing role for our overall well being
A slide deck that supported my recent university lectures during this autumn in Italy (Polytechnic of Bari), Switzerland (EPFL Lausanne) and Poland (SWPS University Warsaw).
It introduces Artificial Intelligence from a business perspective, talks about the need to have a more robust AI tools with AI Ethics and Trust and eventually presents future trajectories such as the Active Intelligence frontier.
A number of Artificial Intelligence and Aanalytics tools already support our decisions but ACTIVE INTELLIGENCE SYSTEMS, that blend AI, Big Data , Analutics and IotT and much more, will take care of us
The future of AI & ML in Cognitive DiscoveryPietro Leo
My keynote slide deck for the ENEL Innovation Community MeetUp. Recorded session here: in Italian, English and Spanish https://echannel.enel.com/livePages/innovation-communities-meetup-with from minute 2h-38'
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
Machine learning and optimization techniques for electrical drives.pptx
Reading the IBM AI Strategy for Business
1. 1
Reading the AI strategy for
Business and digitization.
1
Pietro Leo
Executive Architect for Data, AI and Automation for large ISVs
IBM AoT/Open Innovation Community Member,
Head of Center for Advanced Studies
2. 2
2
2
By 2030, the global GDP will
grow by 14%, equivalent to
$15.7 trillion, thanks to
artificial intelligence1
• Half of the growth will come from
labour productivity savings, and the
other half from increased consumer
demand because of improvements in
AI-based products 1
• 60-70% of business task time could
be compressed using generative AI
models.2
• 62% of executives believe that
generative AI will disrupt the way
their organization designs and
shapes experiences and processes in
the company3
Source: 1) PwC; 2) McKinsey; 3) IBM IBV;
4. 4
4
4
+AI → AI+
IBM Strategy for AI for Business
Digital Transformation
Process/Task
Automation
New Hybrid
Processes
+
5. 5
5
5
The modern-day AI ladder
+AI
AI+
Collect, organize, grow data
Add AI to your applications
Replace/update your workflows
Automate tasks in your workflows
AI orchestrates the work to be done
6. 6
6
6
+AI
AI+
Collect, organize, grow data
Add AI to your applications
Replace/update your workflows
Automate tasks in your workflows
AI orchestrates the work to be done
All Data and Products and for kind of AI processing
Classic Algorithms + AI Models –
Enterprise AI layer
Business Task Automation
Workflow Re-Engineering e
Ottimizzazione -
Intelligent Process Layer
New Use-Cases,
Products, Services
The modern-day AI ladder
7. 7
7
7
Classic IT
Business
Processes
Data Depbt / Data Collection /
Accuracy / Costs
Business Tasks / Business Use Cases / Business Workflows
Training
from scratch
Fine Tuning
Retrieal & Search
Augmented
General Models
LLMs Apps (e.g. ChatGPT,
Co-pilots, etc)
e.g. Search / Answer Tasks
e.g. Scoring / Assessing Tasks
e.g. Summarization / Translation Tasks
AI
Models
Traditional AI
Generative AI
Enterprise AI layer
AI Enterprise layer: it is intended to host thousands of specialized AI models of different types, not just a single
large generalist model. These models will be derived from open models and adapted for specific use cases or
settings: Traditional models and generative models will be used in a hybrid fashion.
8. 8
8
Data Depbt / Data
Collection / Accuracy /
Costs
Business Tasks / Business Use Cases / Business Workflows
Fine Tuning
Retrieal & Search
Augmented
General Models
e.g. Search /
Answer Tasks
e.g. Scoring / Assessing Tasks
e.g. Summarization / Translation Tasks
e.g. Claim management workflow
Training from
scratch
Intelligent Process Layer
Classic IT
Business
Processes
AI
Models
Traditional AI
Generative AI
Enterprise AI layer
Intelligent Business Processes layer: dynamically orchestrates and optimizes the work of business
workflows, considering heterogeneous activities performed by both humans and autonomous systems.
9. 9
9
The industry’s leading unified
hybrid cloud app platform
watsonx
Enterprise-ready generative AI
and data platform
Open Targeted
Trusted Empowering
Based on the best AI and multi-
cloud and hybrid technologies
Designed for targeted business
use cases
Built with governance,
transparency, and ethics
Bring your own data and models &
run anywhere
IBM: Open
Innovation,
AI Tech
trustworthy
and
problem
solver for
enterprises
Consulting
Trusted solution provider for
enterprises
Business Focus
Customer Experience and Care
Employee Experience, Productivity and Talent
IT development, coding, app modernization, and
operations
Core business operations, sustainability
AI Competencies
20k+ Skilled data and AI
practitioners, +1k on
Consultants skilled in
generative AI
Enterprise Projects
~2K AI use cases developed
for clients, 40k+ Active and ongoing AI and analytics
client engagements worldwide
Industrialized frameworks to support the full
development cycle: from early PoC, to MVP, to scalable
production
10. watsonx
10
Hybrid cloud
AI tools
Data services
AI and data
platform
SDKs and APIs
AI assistants
Scale and accelerate the impact of AI with trusted data, an open architecture, and
seamless integration
watsonx Orchestrate
watsonx Assistant
watsonx Code Assistant
watsonx Orders
Build on a consistent, scalable
foundation based on open-
source technology
Empower individuals to do
work without expert
knowledge across a variety of
business processes and
applications
Use programmatic interfaces to
embed watsonx platform
capabilities in assistants and
applications
Leverage generative AI and
machine learning — tuned with
your data — with
responsibility, transparency
and explainability
Access data fabric services to
define, organize, manage, and
deliver trusted data to train
and tune models
Red Hat OpenShift AI
(e.g., Ray, Pytorch)
watsonx
watsonx.ai
watsonx.governance
watsonx.data
Ecosystem
integrations
Data fabric
services
Foundation models
Open Source | Hugging
Face
Llama 2 | Meta AI
Geospatial | IBM +
NASA
Granite | IBM
• Digital Labor
• IT Automation
• Security
• Sustainability
• Application
Modernization
• Data and
Transaction
Processing
IBM Software
Infrastructure
• IBM Z
• Distributed
Infrastructure
• Infrastructure
Support
• Quantum
AI+
Software
and SaaS
Partners
and ISVs
Multi - Public Clouds
AWS ● Azure ●
Others
Enterprise
Infrastructure
Edge
Open Innovation