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Top AI FAQs - A list of questions that every manager should know the answer to.

AI FAQs Part 1: Basic questions that every professional must answer about artificial intelligence (AI):

  • What is Artificial Intelligence (AI)? What are its capabilities and limitations?
  • How does AI compare to human intelligence? In what way is it superior and in what way is it inferior?
  • What are the limitations of current AI generations vs. next generation AI?
  • What are the different types of AI?
  • What are generative AI applications? What are its capabilities and limitations?
  • What are multi-modal AI applications? What are its capabilities and limitations?
  • What Large Language Models (LLM)? What are their capabilities and limitations?
  • What is Machine Learning (ML)? What are its capabilities and limitations?
  • What are the different practical applications of AI in business and government sectors?
  • What are generative Artificial Intelligence (AI) applications? How does AI compare to human intelligence? What are its capabilities and limitations?
  • How does AI work?
  • How does IBM Watson, Open AI ChatGPT, Sora, Google Deep Mind AlphaFold, Gemini, and Midjourney, Stable Diffusion work?
  • How does AI learn? And how it can be trained?
  • How does image generation work?
    Does AI steal art or copyrighted material?
  • How to deal with AI Plagiarism?
  • How does AI solve math problems?
  • Are AI capabilities hyped?
  • Where does AI outperform human intelligence and where does it under-perform?
  • How does AI Learning compare to Human Learning?
  • How does AI pattern recognition compare to Human Pattern Recognition?
  • What is the AI predictive analytics capabilities? How fast are they growing?
  • How can AI solve difficult problems
  • Can AI hack usernames and passwords or break encryption systems?
  • How AI can be a threat to internet user accounts, bank accounts and government accounts?
  • How will AI impact jobs and economic growth?
  • How will AI impact financial markets and investment management?
  • What is the controversy between Open IA and Sam Altman?
  • What is Q-Star program at Open AI?
  • How NVDIA GPUs and Chips enable AI?
  • How prompt engineering and human feedback trains AI?
  • How to use prompt engineering to jailbreak or hack AI limitations?
  • Does AI have sense of humor?
  • Can AI lie, or deceive humans?
  • Is AI conscious, self-aware or sentient entity? Or is it just a mimicking entity?
  • Is AI a threat to humanity? Does it have survival code? Can it override code or learning limitations?
  • What are AI hallucinations?

AI FAQs Part 2: Top AI Productivity Questions

  • What are multi-modal AI applications capabilities and limitations?
  • What large language models LLM capabilities and limitations?
  • What are the different applications of AI in business and government sectors?
  • How will AI change R&D, production and delivery of products and services, and customer support and productivity in general?
  • Do you need government and business process re-engineering to implement effective AI systems?

AI FAQs Part 3: AI Deep Dive Questions

  • What is the AI Algorithmic code structure?
  • What is gradient descent algorithm and how it helps AI adapt and adjust its learning via back propagation?
  • What is the difference between AI inference vs. AI training?
  • What is AI recursive self-improvement?
  • What is silicon neural network, nodes, and layers? How do they compare to human brain’s biological neural network (nerve cells and neurons)?
  • How AI can see or identify numbers, letters, and images of things and people?
  • What is Deep Learning?
  • What are the AI learning and pattern recognition parameters, data points, associations (links), layers, data flows (filtering), weights, biases and activation functions?
  • Is it true GPT 4 has close to 2 trillion parameters?
  • What are AI Tokens? How many are needed for each task?
  • What is an Epoch or a training session?
  • How does correction, penalization, positive and negative re-enforcement work?
  • What is the optimal number of layers and nodes architecture for a specific task?
  • What are convolutional neuron networks or CNNS? How they are used for processing images and object recognition
  • What are recurrent neuron networks or RNNS?
  • What are LSTMS or long short-term memory neuron networks? How they are used for forecasting time series or predicting the stock market?
  • What is Transformers Architecture? How is it used by Large Language Models (LLMs) such as GPT CLA, and Llama?

AI FAQs Part 3: AI Strategy, Governance & Leadership Questions

  • Strategic analysis and planning of AI systems in business and government
  • How will AI disrupt your industry, target market and operations?
  • What are the risks and opportunities?
  • Where is the true value and return on investment (ROI) of AI systems deployment?
  • How will AI change the behavior of consumers, workers, managers, and government?
  • How can AI and the machine learning models help or hurt my business or organization?
  • What are the dangers and the unintended consequences of AI?
  • What is the AI Value Chain - What does it take to build a complete AI system?
  • How to use AI to gain competitive advantage?
  • How much can AI save time, labor, cost, and errors?
  • Who the top AI application and platform vendors?
  • How to align my organization with AI strategy?
  • What are the cultural, ethical, legal, intellectual property (IP) and copyright dimensions of AI projects and data training?
  • How to create an AI governance framework?
  • How to manage legal, reputational, relational, technical, operational and business risks of AI systems?

AI FAQs Part 4: AI Implementation and Project Management

  • What is the AI Value Chain - What does it take to build a complete AI system?
  • How much can AI save time, labor, cost, and errors?
  • How can AI generate insights from big data, personalize user experiences, and streamline business processes and improve creativity and innovation?
  • How will AI change R&D, production and delivery of products and services, and customer support and productivity in general?
  • Do you need government and business process re-engineering to implement an effective AI system?
  • How much data and what type of data is needed for AI training?
  • How much time it take to train an AI system?
  • How much does it cost to build an in-house AI system vs. buying external AI services?
  • Who the top AI application and platform vendors?
  • How to manage the product life cycle (PLC) of AI in business?
  • How to manage enterprise data privacy when using outsourced AI platforms?
  • How does AI impact data centers, power usage and real estate?
  • What skills are needed to implement an enterprise AI?
  • How to overcome the limitations of AI, including designing an effective data architecture, ensure enough quality datasets, mitigate biases & decision errors?
  • How critical thinking & design thinking training help with AI effectiveness?
  • What are the cultural, ethical, legal, intellectual property (IP) and copyrights dimensions of AI projects and data training?
  • How to audit AI algorithms and models for reliability and trust?
  • What are the best practices for implementing an AI project?
  • What is MMLU (Massive Multitask Language Understanding)?
  • How many GPUs are needed to build one AI training model?
  • How much it cost to build a training model data center and electric power generation and consumption?
  • Is it better to build our own AI data center or outsource it?

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