After decades of incentivizing the isolation of hardware, software, and algorithm development, the catalysts for closer collaboration are changing the paradigm

HISTORY TELLS US that scientific progress is imperfect. Intellectual traditions and available tooling can prejudice scientists away from some ideas and towards others.(24) This adds noise to the marketplace of ideas and often means there is inertia in recognizing promising directions of research. In the field of artificial intelligence (AI) research, this article posits that it is tooling which has played a disproportionately large role in deciding which ideas succeed and which fail. What follows is part position paper and part historical review. I introduce the term hardware lottery to describe when a research idea wins because it is compatible with available software and hardware, not because the idea is superior to alternative research directions. The choices about software and hardware have often played decisive roles in deciding the winners and losers in early computer science history. These lessons are particularly salient as we move into a new era of closer collaboration between the hardware, software, and machine-learning research communities. After decades of treating hardware,

Automated summary

This article argues that in the field of artificial intelligence research, the success or failure of ideas is largely determined by the tools used. The choices of software and hardware have played a crucial role in early computer science history, deciding the winners and losers.