System 2 Reasoning Capabilities Are Nigh
Scott C. Lowe

TL;DR
This paper reviews the progress and remaining challenges in developing neural models capable of human-like System 2 reasoning, suggesting that minimal further advances are needed to achieve this goal.
Contribution
It provides a comprehensive review of current reasoning models and outlines the remaining steps to develop neural systems with human-like System 2 reasoning capabilities.
Findings
Current models are close to achieving System 2 reasoning
Very little additional progress is needed to attain human-like reasoning
The review identifies key remaining steps for future research
Abstract
In recent years, machine learning models have made strides towards human-like reasoning capabilities from several directions. In this work, we review the current state of the literature and describe the remaining steps to achieve a neural model which can perform System~2 reasoning analogous to a human. We argue that if current models are insufficient to be classed as performing reasoning, there remains very little additional progress needed to attain that goal.
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Taxonomy
TopicsAI-based Problem Solving and Planning
