Decoding the Trends: A Deep Dive into AI Landscape of 2024

The September 2024 issue of IEEE Spectrum

The AI Index tracks the generative AI boom, model costs, and responsible AI use. Each year, the AI Index report provides valuable insights into the world of AI, showcasing key trends and developments. This year’s report, spanning 393 pages, highlights the significant advancements and challenges faced by the AI industry, particularly in light of the events of 2023.

Key Highlights from the Report

This year’s report, published by the Stanford Institute for Human-Centered Artificial Intelligence (HAI), delves into various aspects of AI, including responsible AI, AI in science and medicine, R&D, technical performance, the economy, education, policy and governance, diversity, and public opinion. A notable inclusion in this year’s report is a citation of an article from IEEE Spectrum focusing on generative AI’s visual plagiarism problem.

One of the significant trends highlighted in the report is the exponential growth in investment in generative AI. Despite an overall decrease in corporate investment, generative AI saw a surge in funding, reflecting the increasing interest and adoption of technologies like ChatGPT and DALL-E 2.

The Rise of Foundation Models

The report sheds light on the emergence of foundation models, such as GPT-3 and GPT-4, which serve as the building blocks for various AI applications. These multipurpose models, primarily developed by industry players like Google, play a crucial role in advancing AI capabilities and innovation.

Debates surrounding open versus closed models have been a hot topic in the AI community. While some argue for the dangers of open models, others advocate for their role in driving innovation. The report presents insights into the performance trade-offs between open and closed models, with closed models demonstrating superior performance on several benchmarks.

Cost and Environmental Implications

The report delves into the financial implications of training large models, highlighting the substantial resources required for such endeavors. Collaboration with the AI research organization Epoch AI provided insights into the costs involved in training models, with some models, like Google’s 2017 transformer model, trained for relatively low costs.

Additionally, the report touches on the environmental impact of AI, particularly in terms of the carbon footprint associated with large language models. Efforts to assess and mitigate the environmental effects of AI training and deployment are crucial for sustainable AI development.

Business Adoption and Impact of AI

Businesses are increasingly leveraging AI technologies to drive efficiencies and boost revenues. Data from Fortune 500 companies’ earnings calls indicates a pervasive discussion around AI, reflecting a widespread recognition of AI’s potential to transform businesses.

Responsible AI and Future Outlook

The report emphasizes the importance of responsible AI practices, with a focus on privacy, fairness, and data governance. While AI continues to outperform humans in various tasks, the need for ethical AI development remains paramount.