Remove AI Research Remove Explainable AI Remove ML Engineer
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Introducing the Topic Tracks for ODSC East 2025: Spotlight on Gen AI, AI Agents, LLMs, & More

ODSC - Open Data Science

Topics Include: Agentic AI DesignPatterns LLMs & RAG forAgents Agent Architectures &Chaining Evaluating AI Agent Performance Building with LangChain and LlamaIndex Real-World Applications of Autonomous Agents Who Should Attend: Data Scientists, Developers, AI Architects, and ML Engineers seeking to build cutting-edge autonomous systems.

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Where AI is headed in the next 5 years?

Pickl AI

Significantly, McCarthy coined the term “Artificial Intelligence” and organized the Dartmouth Conference in 1956, which is considered the birth of AI as a field. Knowledge-Based Systems and Expert Systems (1960s-1970s): During this period, AI researchers focused on developing rule-based systems and expert systems.

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ML Pipeline Architecture Design Patterns (With 10 Real-World Examples)

The MLOps Blog

At that point, the Data Scientists or ML Engineers become curious and start looking for such implementations. The concept of Explainable AI revolves around developing models that offer inference results and a form of explanation detailing the process behind the prediction.

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