Part 5/13:
Proprietary LLMs: To maintain competitive advantage and data privacy, companies are keen to develop and deploy their own models.
Model Diversity: Not every use case requires massive models; smaller, optimized models (e.g., 11B parameters) are easier to serve and adapt.
Multi-Modal AI: Tasks like text generation, summarization, translation, code completion, and image generation are now performed with high accuracy, often leveraging transformer architectures.
Mig emphasized that the focus is shifting toward deploying these models efficiently across different modalities—text, images, speech—highlighting the importance of versatile serving frameworks.
Challenges in Large-Scale Model Serving
Despite advances, deploying large models is fraught with challenges: