Age of Industrialized AI // Dan Jeffries // LLMs in Production Conference

Key notes

• 1500 people efforts done by 100 people
• AI can add value, cut down some challenges
• Large Language Models to Large Thinking Models

• AI is a collaboration partner

• Intelligence in everything
• Industrialized AI
• Problems solved in isolation
• Problems and Opportunities to integrate
• LLM rudimentary reasoning engine

• Massive and open-ended systems

• Error rate will reduce in coming years

• newer versions, more consistent reasoning engines will come
• add keywords under the hood

• heuristic-based hacks
• alter prompts

• human-based domain knowledge baked in models
• generalized models
• LLM to label data

• Model patching

• Adaptors - LoRA

My Summary

• There will be a transition from LLM to LTM
• Models will learn to reason/validate
• LLM can be used to generate labels
• LLM can be trained for custom domains
• LLM + Reasoning + Continual Learning + Iterations 
• The newer architecture will emerge to address
• Industrialization of domain-specific models and the ability to reason is the way to go

Keep Exploring!!!