A brief history of AI: how to prevent another winter (a critical review)
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Abstract (arXiv)
The field of artificial intelligence (AI), regarded as one of the most enigmatic areas of science, has witnessed exponential growth in the past decade including a remarkably wide array of applications, having already impacted our everyday lives. Advances in computing power and the design of sophisticated AI algorithms have enabled computers to outperform humans in a variety of tasks, especially in the areas of computer vision and speech recognition. Yet, AI's path has never been smooth, having essentially fallen apart twice in its lifetime ('winters' of AI), both after periods of popular success ('summers' of AI). We provide a brief rundown of AI's evolution over the course of decades, highlighting its crucial moments and major turning points from inception to the present. In doing so, we attempt to learn, anticipate the future, and discuss what steps may be taken to prevent another 'winter'.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 5 of its 109 references that are in the map. First posted on arXiv 3 Sep 2021.
Builds on
5 of 109 references.
References · 5
- 2020Language Models are Few-Shot Learnerscited by 32,199
- 2019Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AIcited by 1,543
- 2020Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scanscited by 158
- 2018Troubling Trends in Machine Learning Scholarshipcited by 107
- 2021The AI Index 2021 Annual Reportcited by 34
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Citing papers per year: 2021: 1; 2022: 0; 2023: 1; 2024: 2; 2025: 3; 2026: 1.
8 papers.
- 2023An Overview Of Temporal Commonsense Reasoning and Acquisitioncited by 10
- 2025Large Language Models for Agent-Based Modelling: Current and possible uses across the modelling cyclecited by 4
- 2024PReLU: Yet Another Single-Layer Solution to the XOR Problemcited by 3
- 2021AI-Based Detection, Classification and Prediction/Prognosis in Medical Imaging: Towards Radiophenomicscited by 2
- 2024DeepDiveAI: Identifying AI Related Documents in Large Scale Literature Datacited by 2
- 2025What is Implementation Science; and Why It Matters for Bridging the Artificial Intelligence Innovation-to-Application Gap in Medical Imagingcited by 1
- 2025Semantic Web and Software Agents -- A Forgotten Wave of Artificial Intelligence?cited by 0
- 2026Rethinking Artificial Intelligence in Medical Imaging: Assumptions, Reality, and Reframingcited by 0
- 2026Rethinking Artificial Intelligence in Medical Imaging: Assumptions, Reality, and Reframing29 Jul 2026
- 2025What is Implementation Science; and Why It Matters for Bridging the Artificial Intelligence Innovation-to-Application Gap in Medical Imaging14 Oct 2025
- 2025Large Language Models for Agent-Based Modelling: Current and possible uses across the modelling cycle8 Jul 2025
- 2025Semantic Web and Software Agents -- A Forgotten Wave of Artificial Intelligence?20 Mar 2025
- 2024PReLU: Yet Another Single-Layer Solution to the XOR Problem17 Sep 2024
- 2024DeepDiveAI: Identifying AI Related Documents in Large Scale Literature Data23 Aug 2024
- 2023An Overview Of Temporal Commonsense Reasoning and Acquisition28 Jul 2023
- 2021AI-Based Detection, Classification and Prediction/Prognosis in Medical Imaging: Towards Radiophenomics20 Oct 2021