U.S. Leads China by Fivefold in AI Basic Model: Stanford University Research

(AsianFin)— In 2023, U.S. companies released a total of 109 basic models, more than five times the number released by Chinese peers, according to the seventh annual Artificial Intelligence (AI) Index Report released by Stanford University’s Human-Centred Artificial Intelligence.

AI is catching up with humans, and polls show that 52% of people are more concerned than excited, said the report.

Compared with Chinese AI developments, the U.S. AI industry demonstrates significant advantages in the number of AI basic model releases and investment activities.

Meanwhile, the U.S. AI industry's investment in 2023 reached $67.2 billion, 8.7 times that of China’s $7.8 billion. Additionally, the U.S. had 61 well-known AI large models, while China had only 15.

Top 10 takeaways from the report are as follows:

1. AI beats humans on some tasks, but not on all.

AI outperforms humans on image classification, visual reasoning and English understanding benchmarks, but it is not as good at more complex tasks such as competition-level mathematics, visual commonsense reasoning, and planning.

2. Industry continues to dominate frontier AI research.

A total of 51 notable machine-learning models were produced by industry, while academia produced just 15. However, a record-high 21 models came from industry-academic collaboration.

3. Frontier models get way more expensive.

Training costs for state-of-the-art AI models are unprecedented. Examples given are the estimated $78m of compute used for OpenAI’s ChatGPT, and $191m for Google’s Gemini Ultra.

4. The United States leads China, the EU, and Britain as the primary source of top AI models.

Institutions in the U.S. were responsible for originating 61 notable AI models during 2023, with 15 from the EU and 12 from China.

5. Robust and standardized evaluations for LLM responsibility are seriously lacking.

AI Index research revealed “a significant lack of standardization in responsible AI reporting”. Leading developers such as OpenAI, Google and Anthropic all primarily test against different benchmarks.

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.

Multiple studies revealed that “AI enables workers to complete tasks more quickly and to improve the quality of their output,” and that it bridges the skill-gap between low- and high-skilled workers. But those studies also found evidence that “using AI without proper oversight can lead to diminished performance”.

8. Scientific progress accelerates even further, thanks to AI.

AlphaDev, which makes algorithmic sorting more efficient, and GNoME, which facilitates the process of materials discovery were cited as two of the most significant science-related applications launched thanks to AI.

9. The number of AI regulations in the United States increases sharply.

In 2016, there was a single AI-related regulation in the U.S. By 2023, there were 25, a rise of 56.3% from the number in 2022.

10. People across the globe are more cognizant of AI’s potential impact – and more nervous.

Polling company Ipsos found 66% of people think AI will “dramatically affect” their lives within five years, a rise of 6% on previous polling, while 52% are nervous about AI products and services, up 13%. Pew research in the United States also found more than half those surveyed, 52%, were more concerned than excited about AI.