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                     How Do Foundation Models 
Power Generative AI?
Corporate Training | Visualpath
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What Is a Foundation Model?
 A large AI model trained on broad 
data Simple idea
 One model can handle many Train once on broad 
different tasks data, then reuse for 
many tasks.
 Applications are built on top of it
 Replaces many narrow, single-
purpose models
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How Foundation Models Are Built
1. Collect 
2. Pretrain 3. Align 4. Deploy
Data
Gather and clean Model learns Teach it to follow Offer it through 
large, varied general patterns instructions apps and APIs
datasets at massive scale safely
Pretraining is costly, so most teams reuse existing models.
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The Core Technology Behind the 
Models
Transformer and Attention Tokens and Context
• Reads input as a connected whole • Text is split into small pieces called 
• Attention focuses on the most relevant tokens
parts • Context window is the model's working 
• Handles long passages and complex memory
meaning • Longer windows allow bigger 
documents
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Common Types of Foundation Models
Language Image and Multimodal 
Code Models
Models Video Models Models
Write, Create visuals Understand text, Help write, 
summarize, from text images, and explain, and 
translate, and descriptions audio together review software
answer questions
Many modern products combine several types in one model.
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How a Model Generates Content
 Model predicts the next token, one 
step at a time Key insight
 Your prompt sets the starting context Generation is 
repeated prediction, 
 Settings like temperature control guided by your 
creativity prompt.
 Output is pattern-based, not fact-
checked
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Adapting Models for Business Use
Prompting RAG Fine-Tuning
• Write clear • Connect to company • Train further on your 
instructions documents examples
• Add examples to • Answers use current • Improves style and 
guide output information specialist tasks
• Fastest and lowest • Reduces unsupported • Needs quality data 
cost answers and effort
Start simple. Add complexity only when results demand it.
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Six Trends Shaping Foundation Models
Multimodal Models Reasoning Models AI Agents
Text, images, audio, and Work through problems Models that plan and use 
video in one model step by step first tools to act
Smaller, Efficient Open-Weight Evaluation and 
Models Models Governance
Lower cost, faster, and More control over hosting Testing and oversight 
easier to deploy and customization become standard practice
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Risks and Responsible Use
Accuracy Fairness and Privacy Cost and Security
• Models can invent • Training data can • Usage costs grow with 
convincing facts contain bias scale
• Verify important • Avoid sharing • Protect against 
outputs sensitive data prompt attacks
• Use trusted sources • Follow company policy • Review data and 
license terms
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Key Takeaways and Discussion
 Foundation models are general-
purpose and reusable Questions and 
Discussion
 They generate content by predicting 
tokens
 Adapt with prompting, RAG, or fine-
tuning
Thank you from Visualpath
 Use them responsibly with human 
review
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For More Information About 
Generative AI
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   Nilagiri Block, Aditya Enclave,  Ameerpet, 
Hyderabad-16
Ph. No: +91-7032290546
www.visualpath.in
 [email protected]
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Thank You
For More 
Information
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