Learn how to use small language models for industry and domain-specific use cases, and why you should leverage this approach in your enterprise.
David Berrio, our Senior AI/ML Engineer, will teach you:
- What small language models are
- Why you should be leveraging them (especially for domain-specific use cases)
- How to implement them
- Why is this important?
Many enterprises are leveraging large API-based models like ChatGPT. This can become cost-prohibitive, less performant, and even less accurate when applied to domain-specific use cases.
By leveraging small language models (especially open-source ones), you can fine-tune your model to your specific use case, saving money and time while providing a more accurate experience.
Who is this for?
- Leaders and practitioners in engineering and application development who are curious about how to leverage small language models for more control and cost savings
- Business leaders looking to leverage Gen AI for industry-specific use cases
Don't miss out!
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Chapters:
00:00 - Introduction to GenDD Lab Live
00:24 - Overview of Generative-Driven Development (GenDD)
00:42 - Topic Introduction: Small Language Models
01:28 - Introduction of David Berrio
01:49 - Presentation Begins
02:12 - Importance of Small Language Models
03:20 - Opportunities with Small Language Models
04:18 - Challenges with Large Language Models (LLMs)
05:07 - Use Case 1: Financial Oversight and Receipt Processing
07:10 - Broader Applications Beyond Chatbots
07:57 - Use Case 2: Ensuring Package Integrity
09:43 - Multimodality and Computer Vision
11:14 - Comparison Between Small and Large Language Models
12:44 - Knowledge and Reasoning in LLMs
13:40 - Limitations and Cost of LLMs
15:40 - Overkill of Using LLMs for Simple Tasks
16:40 - Architecture for Invoice Processing with LLMs
19:37 - Architecture for Package Condition Monitoring with LLMs
20:35 - Benefits of Small Language Models
22:18 - Definition and Efficiency of Small Language Models
24:31 - Fine-Tuning and Knowledge Distillation
27:02 - Real-Life Examples of Small Language Models
28:21 - Invoice Data Extraction Demo
30:37 - Automating Invoice Processing
31:22 - Image-Based Invoice Processing Demo
34:08 - Final Thoughts on Small Language Models
36:00 - Streamlit for AI/ML Prototyping
37:00 - Q&A Session Begins
37:25 - Computing Power for Small Language Models
40:58 - Using Large Language Models Locally
44:23 - Mini RAG and Code Generation
48:18 - Vector Database Explanation
52:02 - Future of Small and Large Language Models
55:10 - Training and Fine-Tuning Small Language Models
58:45 - Closing Remarks and Upcoming GenDD Labs
01:02:20 - Final Q&A and Audience Interaction
01:03:35 - Conclusion and Thanks
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