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AI Value Creators - Helion

AI Value Creators
ebook
Autor: Rob Thomas, Paul Zikopoulos, Kate Soule
ISBN: 9781098168308
stron: 300, Format: ebook
Data wydania: 2025-04-01
Księgarnia: Helion

Cena książki: 228,65 zł (poprzednio: 265,87 zł)
Oszczędzasz: 14% (-37,22 zł)

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Tagi: Sztuczna inteligencja

We've arrived in a new era—GenAI is reshaping industries and decision-making processes across the board. As a result, understanding their potential and pitfalls has become crucial. But in order to stay ahead of the curve, you'll need to develop fresh perspectives on leveraging AI beyond mere technical know-how. Geared toward business leaders and tech professionals alike, this book demystifies the strategic integration of AI into business practices, ensuring you're equipped not just to participate but to lead in this new landscape.

This insightful guide by industry leaders Rob Thomas, Paul Zikopoulos, and Kate Soule goes beyond the basics, offering real-life success stories and learned lessons to provide a blueprint for meaningful AI engagement. Whether you're a novice or a seasoned expert, you'll come away with an enhanced understanding of GenAI.

  • Recognize the transformative potential of AI in business and how to harness it
  • Navigate the ethical and operational challenges posed by AI with confidence
  • Understand the dynamic interplay between AI technology and business strategy
  • Implement actionable strategies to integrate AI into your organizational culture
  • Step confidently into the role of an AI value creator, equipped to lead and innovate

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Spis treści

AI Value Creators eBook -- spis treści

  • Preface
    • GenAI Is a Lift, Shift, Rift, or Cliff Moment
    • As You Journey into the Book
    • Conventions Used in This Book
    • OReilly Online Learning
    • How to Contact Us
    • The Collective Thank-Yous
    • Our Personal Dedications
  • 1. +AI to AI+: Generative AI and the Netscape Moment
    • What Is a Netscape Moment?
    • AI and the Magical Moment
      • But...AI Is Not Magic
    • Moving Your Business from +AI to AI+
    • Before You Do Anything, Change Your Mental Model from +AI to AI+
      • The AI Ladder, Rebooted for GenAI
    • Before You Start Your Journey, Classify the Budget and Identify How AI Is Going to Help
      • Dimension One: Spend Money to Save Money, or Spend Money to Make Money? How Will AI Help Your Business?
      • Dimension Two: Categorize How the AI Helps Your Business
      • Use an Acumen Curve to Visualize How AI Helps Your Business
      • Where to Start? Heres Our Helpful Advice
    • Become a Shifty Business: Shift Left, and Then, You Can Shift Right!
      • Every Day, We Walk by Problems That Can Be Solved or Made Better with Technology
        • Personal mobility: A fundamental human right
        • A diabetic foot ulcer and an episode of care
        • And so many more
        • Now, shift right
    • Tips for Harnessing Foundation Models and GenAI for Your Business
      • Tip 1: Act with Urgency
      • Tip 2: Be an AI Value Creator, Not Just an Occasional AI User
      • Tip 3: One Model Will Not Rule Them All, So Make a Bet on Community
      • Tip 4: Run Everywhere, Efficiently
      • Tip 5: Be Responsible Because Trust Is the Ultimate License to Operate
    • And with That, Lets Focus on the AI Part
  • 2. Oh, to Be an AI Value Creator
    • AI Through the Years: The AI Time Lapse Section
      • A Quick Bit on Foundation Models
      • Going a Little Deeper: The Evolution of Large Language Models and Comparing Supervised Learning with Self-Supervised Learning
    • AI Value Creation Should Be Your Destination
      • How Do You Consume AI: Be Ye a Value Creator or a Value User?
        • AI User: Shake (embed) and bake (into the product) the AI
        • AI User: Dont fall when you make the service call (the even bigger but)
        • Fire starter: Becoming an AI Value Creator
        • The path forward: How to create value with AI
        • Look before you leap
    • Planning Your AI Future: A Future with Many GenAI Models
      • Its Time to Demystify and Apply AI
        • The componentry
          • A unified, modern data fabric with an accompanying data-as-a-product point of view
          • A development environment and an engine
          • The modality of human features
          • AI management and exploitation
          • Agents and assistants for the masses
        • The process: Cake ingredients without a recipe do not make a cake
          • Step 1: Identify the right business opportunities for AI
          • Step 2: Prepare the organization for AI
          • Step 3: Select technology and partners
          • Accept failures but do so in a safe manner
    • The Future of AI
    • Lets Get into It
  • 3. Equations for AI Persuasion
    • Some Things Are Timeless
      • Tension Has Always Existed with TechnologyAlways
      • No Calculators Needed! Our Three Persuasion Equations
        • Populations are declining
        • Productivity varies around the globe
        • Debt growth with expense and access headwinds
        • Uneven GDP growth
      • Equation 1: How to Grow GDP
      • Equation 2: What Makes for AI Success?
        • Bake the layer cake: A platform that helps you master the AI success equation
          • The base: Hybrid cloud and AI tools
          • Data services need to be at your service
          • The AI and data platform: The heart of the cake
          • Im more than OK with an SDK
          • Agents and assistants empower AI for the many
      • Equation 3: Find Your BalanceNavigate the Paradox
        • Leadership is stewardship: Guiding with care
        • Drills and skills help you master the craft
        • The different facets of being open
    • One Last Piece of Advice: See AI as a Value Generator, Not a Cost Center
    • Wrapping Up
  • 4. The Use Case Chapter
    • The Use Case Value Creation Curve
    • Going Horizontal Gets You the Most Vertical
      • Experimentation
      • Putting Your Data to Work
      • IT Automation
      • CodeThe Language of Computers
      • Digital Labor and AI Assistants
      • Agents
      • The Business Lens: Use CasesHorizontally Speaking
      • The Bonus (Horizontal) Use CaseSynthetic Data
    • A Smattering of Use CasesVertically Speaking
      • Agriculture
      • Accounting
      • Education
      • Healthcare
      • Insurance
      • Legal
      • Manufacturing and Production
      • Pharma
    • Endless Possibilities: More Industries Where GenAI Shines
    • The Building Blocks of AI
  • 5. Live, Die, Buy, or TryMuch Will Be Decided by AI
    • LLMsThe Stuff People Forget to Tell You
      • The Knowledge Cut-Off Date
      • LLMs Can Be Masters of Making It Up as They Go
      • Footprints in the Carbon: The Climate Cost of Your AI BFF
      • Copyright and Lawsuits
      • What About Digital Essence?
      • Your Expanding Surface Area of Attack
        • Data poisoning
        • Prompt injection attacks
        • Social engineering and deepfake attacks
      • Data Privacy
      • Steal Now, Crack Later
    • Good Actor Levers for All Things AI
      • FairnessPlaying Fair in the Age of AI
      • Bias Here, Bias There, Data Bias Is Everywhere
      • RobustnessEnsuring Artificial Intelligence Is Unbreakable Intelligence
      • ExplainabilityExplain the Almost Unexplainable
      • LineageTracing the Trail: Let Good Data Prevail
    • RegulationsThe Section That Wasnt Supposed to Be
      • What to RegulateOur Point of View
      • Managing the AI Lifecycle
        • What lies beneath
        • An example of an end-to-end governed process
    • Wrapping It Up
  • 6. Skills That Thrill
    • Let the Skilling Begin
    • The Path to AI+ Requires Scaling Skills Across a Broad Spectrum of Roles
    • AIJob Destroyer or Job Creator?
      • Youre Only Going to Get Checkmated if You Dont Up Your Skills
      • Democratized Technology: The Job Creator
    • Levers of Clever: Unlocking a Skills Program That Lasts Forever
      • Lever 1: Start at the BeginningHire Employees Who Want to Know the Why
        • Be a Mozart of learning
      • Lever 2: Recruit Digitally Minded Talent
      • Lever 3: Take CountInventory Your Skills
        • Bevel your levels
      • Lever 4: Plan for EveryoneA Plan Without Action Is a Speech
      • Lever 5: Embrace the Learning (and Forgetting) Curves
      • Lever 6: Combine Instruction + Imitation + Collaboration
        • Living for Gagas Applausedo it for real or dont do it at all
        • Build the sandboxencourage the messy
        • Show off (and celebrate) those digital credentials!
      • Lever 7: Culture MattersBe a Skills Verb, Not a Noun
      • Lever 8: Set the Organizational Tone for AI
    • Case Study: IBMs Skills Challengethe CEO Asked; We All Responded
    • The Final Word
  • 7. Where This Technology Is HeadedOne Model Will Not Rule Them All!
    • The Bigger the Better, Right? Perhaps at the Start, But That Was a Long Time Ago
    • The Rise of the Small Language Model
      • Data Curation Results in AI Salvation
        • Data quantity
        • Data quality
        • Domain specialization
      • Think About This When It Comes to Data Curation
      • Model DistillationUsing AI to Improve AI
      • Think About This When It Comes to Model Distillation
    • Where Are We Going Next? Small Language Models...Assemble!
      • Model Routing
      • Think About This When It Comes to Model Routing
      • Mixture of Experts (MoE) Architecture
      • Think About This When It Comes to MoEs
    • Agentic Systems
      • Whats Your Reaction to This Agent in Action?
      • A Little More on Agents
      • How Agents Are Built
        • ReAct (Reasoning and Action)
        • ReWOO (Reasoning WithOut Observation)
      • Risks and Limitations of Agentic Systems
      • Three Tips to Get You Started: Our Agentic Best Practices
        • 1. Activity logs
        • 2. Interruption and runtime observability
        • 3. Human supervision
      • Think About This When It Comes to AI Agents
    • Wrapping It Up
  • 8. Using Your Data as a Differentiator
    • Customizing Open Source for the Enterprise: A New Way of Looking at Enterprise Data
      • The Original Eras Tour: Looking Back a Few Decades on Data Representations
        • Up to the 1980s: Expert systems
        • 1980s to ~2010: Machine learning
        • 2010 to ~2017: Deep learning
        • Today: Foundation models (aka LLMs)
    • Stand Up and Represent!...Your Data
      • Step 1: It All Starts with Trust
        • The IBM commercialin Granite you should trust
      • Step 2: Representing your Enterprise Data within an LLM
        • Introducing InstructLab
        • Dipping your toe into the InstructLab pool
        • Can you smell whats cooking? Skill and knowledge recipes
        • Harnessing the power of the community
        • A day in the life of an InstructLab contributor
      • Step 3: The Grand Finale: Deployment and Experimentation
    • The Future Is Open, Collaborative, and Customizable
  • 9. Generative ComputingA New Style of Computing
    • The Building Blocks of Computing
      • TransformersMore Than Meets the AI
    • Not Back to the Future; Back to Computer Science
      • Doors Wide OpenReimagining the Possible
    • How Models Are Built in Generative Computing
      • Libraries for Adding Capabilities to a Generative Computing System
      • The Quick Compare SummaryHow You Use LLMs Today Versus Generative Computing
      • A Generative Computing RuntimeWhat Can We Program It to Do?
      • OpenAIs StrawberryA Berry Sweet Innovation
    • From Generative Computing to a Generative ComputerWhat Does All of This Mean for Hardware?
      • Experimenting with the Acceleration of AI at the IBM NorthPole
    • The Final Prompt: Wrapping It All Up
  • Index

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