Stanford's yearly AI index report has recently been published.

Short summary of take-aways:

• Human still beats AI on competition-level mathematics, visual common sense, reasoning and planning

• There is a record number of models as a result of industry-academia collaborations

• Frontier models more and more expensive (OpenAI’s GPT-4 used an estimated $78 million worth of compute to train, while Google’s Gemini Ultra cost $191 million for compute)

• USA leading the race on notable models (61 notable AI models originated from U.S.-based institutions, far outpacing the European Union’s 21 and China’s 15)

• The lack of standards for evaluation of LLM responsibility complicates efforts to systematically compare the risks and limitations of top AI models

• Investments are skyrocketing  ("Despite a decline in overall AI private investment last year, funding for generative AI surged, nearly octupling from 2022 to reach $25.2 billion. Major players in the generative AI space, including OpenAI, Anthropic, Hugging Face, and Inflection, reported substantial fundraising rounds.")

• Sharp increase in number of AI regulations in the US. 25 AI-related regulations in 2023 - up from just one in 2016

• People across the globe are getting more nervous about AI impact. 52% express nervousness toward AI products and services, marking a 13 percentage point rise from 2022

  Download full report from here.