IBM GenAI Course for Business Leaders Outline

Dhiraj Patra

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  • Basic AI terminology includes:
  • Large language models (LLMs)
  • Deep learning
  • Supervised learning
  • Transformers
  • Foundation models
  • Language
  • Self-supervised learning
  • Generative AI
  • It is important to democratize AI, leveraging the energy and the transparency of open science and open-source AI so that we all have a voice in:
  • What AI is
  • What AI does
  • How AI is used
  • How AI impacts society
  • How AI integrates with your business
  • To help you effectively, safely, and responsibly put AI to work, you must:
  • Protect your data
  • Embrace principles of transparency and trust
  • Make sure that your AI is implemented ethically
  • Empower yourself with platforms and processes to control your AI destiny
  • Foundation models are trained using self-supervised learning. If you give the model a few words in a prompt, it can mathematically predict the likelihood of words in the response.
  • There are basically three models of AI consumption, including:
  • Embedded AI
  • APIs
  • Platform models
  • The future of AI is not about one model, it’s multi model.
  • Traditional AI can analyze data and tell you what it sees. Generative AI can use that same data to create something new.
  • A foundation model is a general-purpose AI model that’s trained unsupervised, usually on large amounts of text or data that come from the internet.
  • Foundation models are what will form the basis of generative AI for businesses.
  • To get started with generative AI, the steps are:
  • Establish a team.
  • Pick an internal low risk use case and build a prototype.
  • Have an in-depth conversation about what you require to obtain value drivers.
  • Operate with a level of responsibility and transparency.
  • Some key success factors include:
  • Choosing the right evaluation metrics
  • Understanding that one model doesn’t have to rule them all
  • Choosing a platform that has proven expertise and foundation models, and ensuring that governance tools are in place
  • Trust is critical for AI success in enterprises.
  • Hallucination, leakage of private information, and bullying are new risks with the advent of generative AI.
  • Three key customer service areas that generative AI can significantly improve include: self-service, agents in the contact center or in the field, and contact center operations.
  • Five-step approach for driving the execution include:
  • Have a clear idea of the experience you want to deliver.
  • Understand your customers well.
  • Look at the best tools that can support those channels.
  • Once you have your toolchain sorted, design the journey end to end, so it delivers on the service strategy, the experience you had defined when you started.
  • Application modernization involves taking an outdated computing system and updating it with modern, well aligned capabilities and features to create new business value.
  • Once you make the decision to modernize, the process will kick off in two phases: Advisory and Planning.
  • Benefits of using AI include:
  • Radically streamline the workload migration to the new architecture
  • Enable teams to observe workload performance in the new environment so they can optimize and refine the process
  • Ability to learn and adapt faster

Link for the course https://www.coursera.org/learn/generative-ai-for-executives-business-leaders/supplement/ivayK/course-summary-ai-for-business-leaders

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