SAP - LLM Flashcards
(20 cards)
What is LLM
An LLM is a type of artificial intelligence model that specializes in processing, understanding, and generating human language.
LLM models are a subset of machine learning models known as
Deep learning models
what are deep learning models design for
They are designed to handle large-scale data and complex pattern recognition.
What are key aspects of LLMs
- Architecture
- Training data
- Training processes
- Capabilities
- Scale
6 Applications - Challenges & limitations
What are the benefits of LLMs
- Efficiency
- Cost Reduction
- Data Analysis
- Improved Customer Experience
- Scalability
What are the Risk of LLMs
- Data Privacy Concerns
- Bias and Fairness
- Misinterpretation of Data
- Dependency
- Technical Complexity
What type of a setup is used for the LLMs in the context of the generative AI hub?
SaaS
The integration of LLM into Business Application involves some key steps
- Ideation
- Validation
- Realization & Productization
- Operation, Continuous improvement
What does the ideation involve
The Ideation phase is focused on identifying potential use cases for LLMs within SAP’s ecosystem.
What does the Validation Phase involves
The validation phase assesses the feasibility, desirability, and viability of implementing LLMs.
What does the Realization and Productization Phase onvolve
The third phase is where the developed use cases are turned into actual products:
Use Case Finalization: Based on customer feedback, the use case is refined to ensure it meets business requirements.
Technical Finalization: Feasibility and security are key focus areas here, ensuring the product can be reliably deployed. Software Architects are primarily responsible for these activities.
Commercialization Finalization: It is crucial to define the pricing model, finalize business cases, and establish a metering concept for consumption objectives . This is where the commercial aspect of the product is solidified, followed by regular productization steps like executing the commercialization model.
What does Operation, Continuous Improvement Phase involve
The final phase involves the ongoing management and enhancement of your product:
Operations: Regularly gathering customer feedback, monitoring user adoption, and assessing model performance are critical tasks. This is where the User Experience team plays a significant role.
Continuous Improvement: The product is continuously refined based on real-world usage data and customer feedback, ensuring that it remains effective and relevant.
This structured approach ensures that each phase of product development is thorough, collaborative, and geared toward creating robust, market-ready generative AI products that adhere to SAP’s standards for software development and operations life cycle.
What is LangChain
It is a framework designed for developing data-aware applications powered by LLMs. It excels in integrating multiple tools and building intelligent agents capable of performing various tasks. Developers can use Python and JavaScript with LangChain.
What LlamaIndex specialises in
data indexing and retrieval
Why choosing Langchin
its versatility in agent-based applications
Why choosing LlamaIndex
When there is need for efficiency in data handling is crucial.
What the main difficulties of increasing performance of the LLM
Context (what the model needs to know to solve the problem=> to overcome we use RAG) and action (how LLM needs to act => to overcome we use fine tuning)
Optimization is rarely linear and often requires an iterative approach, moving back and forth between different techniques such as
prompt engineering, RAG, and fine-tuning based on ongoing evaluations.
What are Advanced prompting techniques,
Chain-of-Thought (CoT) and Tree-of-Thought (ToT)
