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Examples of mapping human memory systems to AI mechanisms
00:07:09
Human Memory and Its Mapping to LLM / AI Systems
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Chain of Hindsight teach LLM to learn from past mistakes using feedback
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self-reflection + dynamic memory enhance LLM agent's reasoning: Reflexion framework
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Reflexion Framework enhances LLM agents by equipping them with dynamic memory + self-reflection
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Self-Reflection by HotpotQA When doing Knowledge-Intensive Task
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Self-Reflection by AlfWorld Environment when doing Decision-Making Task
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Framework of LLM autonomous agent system: combines LLM  + 4 components, #llmagents
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4 Methods to Decompose tasks when LLM agents planing
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challenges when building and evaluating coding agents #LLMagents
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5 levels of automation in software development: parallel to 5 levels of self-driving #llmagents
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Small Errors in Autonomous Agents Can Cause Catastrophes in Real-World #LLMagents
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10 cases of malicious use of language agents presents significant security risks
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Why AI Struggles in the Physical World, but Thrives Digitally: From Reinforcement Learning to LLM
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structured ladder of job automation opportunities for LLM agents
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3 levels of agents: Text Agents vs LLM Agents vs Reasoning Agents
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intermediate steps: How AI Breaking Down Complex Math Problem with Natural Language
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Last Letter Concatenation: distinction between traditional ML and modern LLM
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Last Letter Concatenation: Simple for Humans, Challenging for AI, Symbolic vs. Pattern Recognition
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Reasoning- Missing Piece in Machine Learning: Why AI Struggles with Few Examples
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How Language Revolutionized AI Agents: From Sensors to Language, from Russell & Norvig to Today
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modern language agents VS earlier AI agents: how they interact with different environments
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LLM Memory: Long-Term & Working Memory in AI Agents
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Wittgenstein: How AI Challenge Rational World, Victory of Vagueness, Why We Can't Define Everything?
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How AI Dialogue Help You Find What You Really Want/ Realizing Your True Needs: From Unclear to Clear
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how the pivot is selected impact on RANDOMIZED-SELECT expected running time
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helpful partitioning pertains to the RANDOMIZED-SELECT to reduce the size of the subarray
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Role of Pivot Elements in Algorithm Efficiency: Randomized Selection Dynamics
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linear expected running time of the RANDOMIZED-SELECT algorithm and why it is effective on average
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Why RANDOMIZED-SELECT Has a Quadratic Worst-Case Time
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