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AI Pricing: A Technical Breakdown of the Cost and Revenue Opportunities

Via LinkedIn Learning

LinkedIn Learning based on 46 ratings

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Overview

"AI Pricing: A Technical Breakdown of the Cost and Revenue Opportunities" is an insightful course designed for product managers, business strategists, and AI practitioners seeking to understand the financial dynamics of AI deployment. This course explores the technical factors influencing the cost structures of AI systems and the potential revenue streams they can unlock. Participants will learn to analyze the components contributing to AI expenses, including infrastructure, data acquisition, model training, inference, and maintenance. The course delves into pricing models for...

Syllabus

Introduction

  • Considering the cost of AI

1. Build vs. Buy

  • Framing build vs. buy in an AI context
  • Setup vs. ongoing costs
  • Selecting the right models for the tasks
  • SaaS, PaaS, and IaaS in the context of AI

2. Costs of Using an AI API

  • Introduction to AI as an API
  • Introduction to AI as a platform
  • Setup costs for AI APIs
  • Ongoing costs for AI APIs
  • Estimating cost for a translation feature
  • Estimating cost for a RAG solution: What is RAG?
  • Estimating cost for a RAG solution: Costs of RAG
  • Estimating costs for an image generation feature
  • Challenge: Estimating the cost of a book summarization
  • Solution: Estimating the cost of a book summarization

3. Examining Major Vendor Pricing

  • Diving into ChatGPT pricing (OpenAI)
  • Diving into Anthropic-based pricing
  • Diving into Google AI pricing
  • Diving into AWS Bedrock pricing
  • Diving into Azure AI-based pricing
  • Diving into Hugging Face-based pricing

4. Costs of Training AI

  • Overview of technical components and tooling
  • Setting up an AI training cluster
  • Cost of compute for training AI models
  • Data cleanliness and sourcing
  • Data movement and storage
  • AI model training iteration and evaluation
  • Tracking AI experiments
  • Fine-tuning models
  • Hiring the team that trains the models
  • Challenge: Training AI for your enterprise
  • Solution: Training AI for your enterprise
  • Challenge: Training AI for your start-up
  • Solution: Training AI for your start-up

5. Costs of Hosting AI

  • Hosting and running your AI models
  • Running your own models or outsourcing
  • Choosing the right hardware for AI models
  • Logging and monitoring AI inference
  • Hiring the team for AI inference
  • Challenge: Running AI for your start-up
  • Solution: Running AI for your start-up
  • Challenge: Running AI for your enterprise
  • Solution: Running AI for your enterprise

6. Other Costs

  • AI copyright and legal risks
  • AI reputational risks
  • AI security risks
  • AI impact on service level agreements
  • AI's environmental impacts

7. Revenue-Generating Models

  • Unit and margin pricing for AI
  • Time consumption pricing for AI
  • Value-based pricing for AI
  • Subscription pricing for AI
  • Start-up funding and grant programs for AI
  • Challenge: Pricing your logo generator
  • Solution: Pricing your logo generator
  • Building a business case for AI projects
  • Building a financial projection for AI projects
  • Challenge: Building an AI business case
  • Solution: Building an AI business case

Conclusion

  • Next steps
AI Pricing: A Technical Breakdown of the Cost and Revenue Opportunities
Go to Class

via LinkedIn Learning

2 hours 55 minutes

Certificate Available

English

On-Demand

Instructor

Denys Linkov

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