Andrew Ng Explores The Rise Of AI Agents And Agentic Reasoning BUILD 2024 Keynote (AI column)

Three months ago, Andrew Ng performed with keynote report About AI Agents and Agent Reflections. I liked the report and decided to share Sammari with the main thoughts.

1) AI as a transformational technology Andrew likens AI to “new electricity,” highlighting its potential for breakthrough applications. The main focus shifts to the application layer, where core value is generated, thanks to the ability to quickly prototyping. (Create an MVP for days instead of months). 2) The evolution of AI stack technologies Three layers are distinguished: - Infrastructure. Semiconductors, cloud platforms - Basic models - trainings, foundation models - Application layer. A fast-growing segment with examples like chatbots and automated workflows 3) Gen AI as a catalyst Creating applications with AI capabilities has accelerated in some cases. 100 time: Creating applications like speech recognition or image analysis now takes 3 day instead of year. The key challenge is to assess the effectiveness of models, where parallel testing and automated feedback cycles are implemented. 4) Agency workflows – a new paradigm Submitted 4 design pattern: - Reflecation: Iterative Code Improvement Through Automated Criticism (Example: generation of Python script with unit tests). **- Tool use (API calls)**Integration with external services (refund of payments, sending email). - Planning (decide on steps for task): Consistent implementation of complex tasks (Image generation → posture analysis → correction). - Multi-agent collaborationCollaboration of Specialized Agents (Analyst + Designer + Tester). 5) Vision Agent - application case The Landing AI platform demonstrates: Automatic Video Indexing with Key Features (Example: Search for "skier in the air" among 10 record).

• Context recognition: Search for objects of complex description n ("a black suitcase with a scratch at the handle"). Generate metadata to train custom models. 6) Future trends Revolution in image/video processing by analogy with text-based AI. The growth of multimodal agents capable of combining text, images and API calls. Development paradigm shift: shift from hand-coded algorithms to orchestration of autonomous agents.

In conclusion, Andrew encourages developers to experiment with agency frameworks, predicting the explosive growth of applications in computer vision and multimedia analytics. Now is the best time to create AI products where 90Agents do the job, and people focus on high-level design.

#AI #ML #Engineering #Software #Architecture #SystemDesign #DistributedSystems