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Understanding Autonomous Machine Learning: Addressing Major AI Challenges

This panel discussion delves into Autonomous Machine Learning (AML) focusing on misconceptions, intent-directed reasoning, and major AI challenges like general-purpose vision, audition, and language understanding. The session explores solutions to central AI problems using a 5-chunk brain-mind model.

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Understanding Autonomous Machine Learning: Addressing Major AI Challenges

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  1. Autonomous Machine Learning PanelIJCNN 2010, July 20 Juyang Weng Embodied Intelligence LaboratoryDepartment of Computer Science Cognitive Science Program Neuroscience Program Michigan State University East Lansing MI 48824 USA http://www.cse.msu.edu/~weng/

  2. Intent-Directed Reasoning with Pixels Luciw & Weng IJCNN 2010

  3. Autonomous Machine Learning (AML):Misconceptions • Generate own supervision: a lot of work! • Semi-supervised, reinforcement learning • Select the most informative samples: a lot of work! • Border points, bottom-up attention (e.g., saliency) • Generate own loss function: Is a loss function good? • Evaluate own performance: Without teacher? • Human supervision? • Human internal (inside the brain) intervention: Bad • Human external (outside the brain) supervision: Goodas it is essential for human intelligence, e.g., classroom teaching

  4. AML: Let Us Face Major AI Challenges • General-purpose vision: • Multiple objects, complex backgrounds • General-purpose audition: • Speaker independence, noisy environment, beyond speech (e.g, music) • General-purpose language understanding: • Acquisition of ontology, language acquisition, discourse • The bottleneck problem: Internal Representation! Emergent! • Symbolic, monolithic representation: Handcrafting a representation • Neural networks: One-shot recognition, cannot perform goal-directed reasoning, lack of autonomy of intents • The bottleneck problem seems to have a solution: A 5-chunk brain-mind model (Weng, IJCNN 2010, Tuesday AM) • The above 3 central problems of AI seem to be tractable by AML

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