The full report is almost 400 pages long but here’s the TLDR version:

  • Industry races ahead of academia. Until 2014 best machine learning models were produced in academia but since then industry took the lead. New AI systems get MILLION times more data than 10 years ago

  • AI systems improve by year-over-year improvement on many benchmarks is marginal

  • AI is getting increasingly bigger footprint on environment. Modern giant AI models require massive infrastructure, expensive, long to train and this results in a much higher carbon emissions

  • AI systems assists and speeds up scientific progress when used by researchers. Examples include hydrogen fusion, drug discovery

  • Cases of AI misuse is on rise

  • Year over year investment in AI decreased, after many years of consistent increase

  • Proportion of companies adopting AI plateaued but companies that adopted AI continue to decrease costs and increase revenues. The number of companies adopting AI doubled from 2017.

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Image source from https://aiindex.stanford.edu/report/


This article reflects my personal views and opinions only, which may be different from the companies and employers that I am associated with.