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AI Overview - What, How, Why Context Matters
AI: What You Need to Know 1. AI is Multi-Generational AI is evolving across generations, affecting various sectors and applications. 2. AI Has Zero Barriers to Entry Accessibility of AI technology allows anyone to engage with and utilize AI tools. 3. The AI Can Train You on How to Use It AI systems often include built-in training mechanisms to assist users. 4. AI Add-Ons: Apps Search Development 5. AI Lifecycle vs AI Adoption Stages: The idea The invention Select access Public access Media hype News Reports Evolution Stages: Fad Trend Utility Use-Case Next Gen Mainstream 6. Innovation Invites Investigation Historical innovations include: Flying machines Distance writing Speaking telegraph Horseless carriage Electric lamp Word processing Spreadsheets Electronic mail Wireless Telephone Social Media 7. Dirk’s Demon to Toaster Cycle Understanding the innovation lifecycle and its impact on society. 8. Gartner’s Hype Curve Introduction to the Gartner New Tech Hype-Curve. Current estimates and implications for AI stages in hype. 9. Browser Tools: Chrome / Firefox / Edge Functions: Data Collection Formatting Research Keyword Highlighting Audio Readers Note Taking Tab Management Grammar 10. AI Functions Learning Models Inference Models Developing Training Plans Automation of Tasks Data Set Collection Web Searches 11. AI Augmented Search Enhancements through AI Browser Extensions. AI Reporting and Data Wrangling. Development tools: Python, Data Science, and Data Engineering. 12. AI Prompt Engineering Key components of successful prompters: Question Context Verify Answer 13. AI Prompt Context Management Contextual relationships, e.g., Ocean and Water. 14. Large Language Model Limitations LLMs are “stateless” technologies with: Lack of memory management. Absence of quality control and quality assurance. Need for programming code for traceability. 15. Your Go-To Strategy with LLMs/AI Control the context and ask relevant quality assurance questions. Address omissions and changes in data. 16. AI Prompt Context Has a Domain Examples from various domains: HR Finance Talent Acquisition Interviews 17. AI Prompt Speed and Importance Control Strategies for concise responses and emphasis on critical information. 18. Roadmap: AI Trainer / AI Coaching Recommended tools: ChatGPT Jasper White Sonic Bard Character AI Perplexity You Chat CoPilot 19. AI: Pick a Starting Point learn coding in fields like NLP, ML, an
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AI Overview - What, How, Why Context Matters
- 1. AI: What You Needto Know
- 2.
- 3. AI Has Zero Barriersto Entry Everybody & Anybody Has Access
- 4. The AI CanTrain You on How to Use It +
- 5.
- 6. The idea The invention Selectaccess Public access Media Hype News Reports AI Lifecycle vs AI Adoption Fad Trend Utility Use-Case Next Gen Mainstream
- 7. Innovation Invites Investigation •Flying machines • Distance writing • Speaking telegraph • Horseless carriage • Electric lamp • Word processing • Spreadsheets • Electronic mail • Wireless Telephone • Social Media
- 8. Dirk’s Demon toToaster Cycle to
- 9. Innovation Lifecycle Timeline fromInception to Common Place
- 10.
- 11. Gartner New TechHype-Curve Early Adopters Investigate 1st Gen Products Start Up Companies R&D Media Hype Begins Suppliers Proliferate Getting Beyond Early Adopters Negative Press Begins Supplier Consolidate 2nd / 3rd Round VC < 5% of Audience Adopt 2nd Gen Products / Services Methods & Best Practices Start Being Developed 3rd Gen Products Out of the Box, Product Suites High Growth Adoption! (20% to 30% Potential Audience Adoption)
- 12. Gartner New TechHype-Curve
- 13. AI Hype CurveStage Estimate Supplier Consolidate 2nd / 3rd Round VC < 5% of Audience Adopt 2nd Gen Products / Services
- 14.
- 15. Browser Tools: Chrome/ Fire Fox / Edge • Data Collection • Formatting • Research • Keyword Highlighting • Audio Readers • Note Taking • Tab Management • Grammar BROWSER Tools
- 16. AI • Learning Models •Inference Models • Developing Training Plans • Automation of Tasks • Data Set Collection • Web Searches AI
- 17.
- 18.
- 19. AI Reporting /Data Wrangling
- 20.
- 21. AI Data Science& Data Engineering
- 22.
- 23. AI Proompter BuildingBlocks •Question •Context •Verify •Answer
- 24. AI Proompter ContextManagement Ocean Water
- 25. AI Proompter ContextManagement Water Ocean
- 26. Large Language ModelLimitations •LLMs are a “stateless” technology •Lack “memory” management (Part of their appeal for developers as the architecture is light weight) •No Quality Control •No Quality Assurance •Requires “programming code” for traceability
- 27. Your Go-To Strategywith LLMs/AI Control the Context
- 28. Your Go-To Strategywith LLMs/AI Maintain Relevance
- 29. AI Proompter QA /QC Questions •What did you omit? •What did I omit? •Percentage of info omitted? •Why was the data omitted? •What changed? •What is missing given our context?
- 30. AI Proompter Cheat Codes •Continue •Whatelse •Keep Going •Please finish •Correct any mistake
- 31. AI Proompter Hasa Domain Knowledge • HR • Finance • TA • Interviews • Examples • Behaviors • Use Cases
- 32. AI Proompter SpeedControl “provide concise answers to save tokens”
- 33. AI Proompter ImportanceControl Bold CAPITALIZE Manners Matter
- 34. Roadmap: AI Trainer/ AI Coaching • ChatGPT • Jasper • White Sonic • Bard • Character AI • Perplexity • You Chat • CoPilot
- 35. AI: Pick aStarting Point
- 36. Learn to CODE:NLP, ML, LL-Models
- 37.