AI Research Think Tank Services

Strategic Governance Best Practices
Investment. Business. Government. AI

Sample Artificial Intelligence (AI) research and support services for businesses and government education, policy design, and best management practices:

Top AI FAQs - A list of Artificial Intelligence (AI) 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?
Benchmarking AI frontier models in the real-world? What model performs best in what domain?
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 are 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 do IBM Watson, Open AI ChatGPT, Sora, Google Deep Mind. AlphaFold, Gemini, Midjourney, and Stable Diffusion work?
How does AI learn? And how can it be trained and fine-tuned?
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 are 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 can AI be a threat to internet users, bank, and government accounts?
How will AI impact jobs and economic growth?
How will AI impact financial markets and investment management?
How NVDIA GPUs and chips enable AI?
How prompt engineering and human feedback (RLHF) trains AI?
How one can use prompt engineering to jailbreak or hack AI limitations?
Does AI have sense of humor?
Can AI lie or deceive humans?
Is AI a conscious, self-aware or sentient entity? Or is it just a mimicking entity? How to test AI self-awarness?
Is AI a threat to humanity? Does it have a survival code? When can it override code or learning limitations?
What are AI hallucinations? How to fix them?

AI FAQs Part 2: Top AI Productivity Questions

What are multimodal AI applications capabilities and limitations?
What are the opne sources vs. commercial 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 the gradient descent algorithm, and how does it help AI adapt and adjusts its learning via back propagation?
What is the difference between AI inference vs. AI training?
What is AI recursive self-improvement?
What are silicon neural networks, nodes, and layers? How do they compare to human brain’s biological neural network (nerve cells and neurons)?
How can AI 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?
How many trillion parameters are needed to achieve super intelligence?
What are AI tokens? How many are needed for each task? How to reduce AI token expenses?
What is an epoch or a training session?
How do 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 are they 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 a competitive advantage?
How much can AI save time, labor, cost, and errors?
Who are 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

How much can AI save time, labor, cost, and errors?
How can AI generate insights from big data, personalize user experiences, 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 and what type of data are needed for AI training?
How much time, energy, labor and money 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 using designing an effective data architecture? How to ensure enough quality datasets and 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 an enterprise AI training model?
How much does 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?