Deep Learning: A Critical Appraisal

2018/01/02 by Gary Marcus, Marcus, Gary · 13 voices · 29 citations
Computer Science · #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #Domain Adaptation and Few-Shot Learning #cs.AI #cs.LG #stat.ML

paper · pdf · doi:10.48550/arxiv.1801.00631

openalex publication_date 2018/01/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Although deep learning has historical roots going back decades, neither the term "deep learning" nor the approach was popular just over five years ago, when the field was reignited by papers such as Krizhevsky, Sutskever and Hinton's now classic (2012) deep network model of Imagenet. What has the field discovered in the five subsequent years? Against a background of considerable progress in areas such as speech recognition, image recognition, and game playing, and considerable enthusiasm in the popular press, I present ten concerns for deep learning, and suggest that deep learning must be supplemented by other techniques if we are to reach artificial general intelligence.

Citations

• Deep learning in neural networks: An overview
• ImageNet classification with deep convolutional neural networks
• Visual Interaction Networks
• Schema Networks: Zero-shot Transfer with a Generative Causal Model of Intuitive Physics
• Neural-Symbolic Learning and Reasoning: A Survey and Interpretation

Cited by

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• Mechanism-Based Intelligence (MBI): Differentiable Incentives for Rational Coordination and Guaranteed Alignment in Multi-Agent Systems
• Few-Shot Learning of a Graph-Based Neural Network Model Without Backpropagation
• AI/ML based Joint Source and Channel Coding for HARQ-ACK Payload
• Foundations of Artificial Intelligence Frameworks: Notion and Limits of AGI
• Consciousness in Artificial Intelligence? A Framework for Classifying Objections and Constraints
• Spectral imaginings and sympoietic creativity: AI hallucinations and the ethics of posthuman creativity
• Education Paradigm Shift To Maintain Human Competitive Advantage Over AI
• Video2Commonsense: Generating Commonsense Descriptions to Enrich Video Captioning
• Shallow Unorganized Neural Networks using Smart Neuron Model for Visual Perception
• Neuro-Symbolic Spatial Reasoning in Segmentation
• Dual approach for object tracking based on optical flow and swarm intelligence
• Hybrid Models for Natural Language Reasoning: The Case of Syllogistic Logic
• Towards Neurocognitive-Inspired Intelligence: From AI's Structural Mimicry to Human-Like Functional Cognition
• HTMformer: Hybrid Time and Multivariate Transformer for Time Series Forecasting
• Physics Knowledge in Frontier Models: A Diagnostic Study of Failure Modes
• Intercontinental prediction of soybean phenology via hybrid ensemble of knowledge-based and data-driven models
• Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies
• Shortcut learning in deep neural networks
• Out of Distribution Generalization in Machine Learning
• Learning model-based strategies in simple environments with hierarchical q-networks
• Deep opacity and AI: A threat to XAI and to privacy protection mechanisms
• Cross-Domain Few-Shot Learning by Representation Fusion
• A decision theoretic approach to model evaluation in computational drug discovery
• Memorisation and forgetting in a learning Hopfield neural network: bifurcation mechanisms, attractors and basins
• Spatial Broadcast Decoder: A Simple Architecture for Learning Disentangled Representations in VAEs
• Limits of trust in medical AI
• A model of cortical cognitive function using hierarchical interactions\n of gating matrices in internal agents coding relational representations
• AI anthropomorphism [wikipedia]

Discussions

• Deep learning: a critical appraisal [hn, 147 points, 61 comments]
• Deep Learning: A Critical Appraisal (2018) [hn, 77 points, 41 comments]
• Deep Learning: A Critical Appraisal [hn, 5 points, 0 comments]
• Deep learning: a critical appraisal [pdf] [hn, 4 points, 0 comments]
• Deep Learning: A Critical Appraisal [pdf] [hn, 4 points, 0 comments]
• Deep Learning: A Critical Appraisal [hn, 3 points, 0 comments]
• Deep Learning: A Critical Appraisal by Gary Marcus [hn, 3 points, 0 comments]
• Deep Learning: A Critical Appraisal [hn, 3 points, 0 comments]
• Deep Learning, a critical appraisal [hn, 2 points, 0 comments]
• In his 2018 critical appraisal of deep learning, @garymarcus.bsky.social made a similar point that he has been making since: while performance can be mustered in "some limited" circumstances, it's "qu [bsky, 2 points, 1 comments]
• Deep Learning: A Critical Appraisal [pdf] [hn, 1 points, 0 comments]
• A good critical look at deep learning https://arxiv.org/pdf/1801.00631.pdf [bsky, 0 points, 0 comments]
• Weekend reading. Going back to a paper by Gary Marcus from 2018 Marcus, Gary. “Deep Learning: A Critical Appraisal,” January 2, 2018. doi.org/10.48550/arX.... #academicSky #PhilAI [bsky, 0 points, 0 comments]

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