The latest AI market insights reveal a clear trend – industry is leading the charge in frontier AI research and development. In 2023, industry produced over 3 times as many notable machine learning models as academia.
This industry dominance highlights a critical advantage – the ability to rapidly translate emergent AI capabilities into real-world applications that drive tangible business value. By closely aligning AI innovation with industry needs and challenges, companies can unlock new opportunities for growth, efficiency, and competitiveness.
In contrast, startup and research-led AI efforts, while valuable, often struggle to achieve the same level of scale and impact. They may lack the deep industry expertise, resources, and go-to-market channels that established enterprises possess.
The key is to foster stronger collaboration between industry leaders and the AI research community. This symbiotic relationship can accelerate the development of trustworthy, responsible AI solutions that address pressing industry problems.
By embracing an industry-led approach to AI innovation, organizations can position themselves at the forefront of this transformative technology. The path to realizing AI’s full potential lies in harnessing the power of industry expertise and resources.
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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.
