AI Index Report 2024

The 2024 AI Index Report from the Institute for Human-Centered AI at Stanford University has been released and is accessible here: https://aiindex.stanford.edu/report/.

This comprehensive report spans 9 chapters, covering topics from R&D to Public Opinion. Traditionally, the report begins with 10 key insights that summarize the entire document, along with highlights for each specific chapter. I highly recommended to at least peruse the highlights of each chapter. Below are my top 10 ???????????????? insights from the report:

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. More foundation models and more open foundation models?

In 2023, a total of 149 foundation models were released, more than double the amount released in 2022. Of these newly released models, 65.7% were open-source, compared to only 44.4% in 2022 and 33.3% in 2021.

5. 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.

6. China dominates AI patents

In 2022, China led global AI patent origins with 61.1%, significantly outpacing the United States, which accounted for 20.9% of AI patent origins. Since 2010, the U.S. share of AI patents has decreased from 54.1%.

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. Here comes multimodal AI

Traditionally AI systems have been limited in scope, with language models excelling in text comprehension but faltering in image processing, and vice versa. However, recent advancements have led to the development of strong multimodal models, such as Google’s Gemini and OpenAI’s GPT-4. These models demonstrate flexibility and are capable of handling images and text and, in some instances, can even process audio.

10. Political deepfakes are easy to generate and difficult to detect

Political deepfakes are alreadyaffecting elections across the world, with recent research suggesting that existing AI deepfake methods perform with varying levels of accuracy. In addition, new projects like CounterCloud demonstrate how easily AI can create and disseminate fake content.

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The US continues to dominate in the development of AI models, while China takes the lead in patent registrations. Could China's progress be hindered by limited access to advanced computing chips?