Introduction to the AI Index Report 2024

Stanford Unversity Report 2024

Top 10 Takeaways

  1. AI beats humans on some tasks, but not on all. AI has surpassed human performance on several
    benchmarks, including some in image classification, visual reasoning, and English understanding. Yet it trails
    behind on more complex tasks like competition-level mathematics, visual commonsense reasoning and planning.
  2. Industry continues to dominate frontier AI research. In 2023, industry produced 51 notable
    machine learning models, while academia contributed only 15. There were also 21 notable models resulting from
    industry-academia collaborations in 2023, a new high.
  3. Frontier models get way more expensive. According to AI Index estimates, the training costs
    of state-of-the-art AI models have reached unprecedented levels. For example, OpenAI’s GPT-4 used an
    estimated $78 million worth of compute to train, while Google’s Gemini Ultra cost $191 million for compute.
  4. The United States leads China, the EU, and the U.K. as the leading source of top AI
    models. In 2023, 61 notable AI models originated from U.S.-based institutions, far outpacing the European
    Union’s 21 and China’s 15.
  5. Robust and standardized evaluations for LLM responsibility are seriously lacking.
    New research from the AI Index reveals a significant lack of standardization in responsible AI reporting.
    Leading developers, including OpenAI, Google, and Anthropic, primarily test their models against different
    responsible AI benchmarks. This practice complicates efforts to systematically compare the risks and
    limitations of top AI models.
  6. Generative AI investment skyrockets. 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.
  7. The data is in: AI makes workers more productive and leads to higher quality work. In
    2023, several studies assessed AI’s impact on labor, suggesting that AI enables workers to complete tasks more
    quickly and to improve the quality of their output. These studies also demonstrated AI’s potential to bridge
    the skill gap between low- and high-skilled workers. Still, other studies caution that using AI without proper
    oversight can lead to diminished performance.
  8. Scientific progress accelerates even further, thanks to AI. In 2022, AI began to advance
    scientific discovery. 2023, however, saw the launch of even more significant science-related AI applications—
    from AlphaDev, which makes algorithmic sorting more efficient, to GNoME, which facilitates the process of
    materials discovery.
  9. The number of AI regulations in the United States sharply increases. The number of AI
    related regulations in the U.S. has risen significantly in the past year and over the last five years. In 2023, there
    were 25 AI-related regulations, up from just one in 2016. Last year alone, the total number of AI-related regulations
    grew by 56.3%.
  10. People across the globe are more cognizant of AI’s potential impact—and more nervous.
    A survey from Ipsos shows that, over the last year, the proportion of those who think AI will dramatically affect their
    lives in the next three to five years has increased from 60% to 66%. Moreover, 52% express nervousness toward AI
    products and services, marking a 13 percentage point rise from 2022. In America, Pew data suggests that 52% of
    Americans report feeling more concerned than excited about AI, rising from 37% in 2022

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