IBM GenAI Course for Business Leaders Outline

• 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