As we inch closer to the end of 2024, the landscape of artificial intelligence (AI) reveals fascinating trends that illustrate both rapid growth and strategic maturation. Recent insights from Elsevier’s Scopus database indicate that generative AI is experiencing an extraordinary compound annual growth rate (CAGR) of 313.3%. In 2019, there were merely four publications on generative AI. Fast forward to November 27, 2024, and that number has surged to a staggering 4,821 research papers published on the topic. Similarly, Large Language Models (LLMs) have seen an increase from 72 publications to 15,522, with a CAGR of 215.9%.

The genAI Hype Bubble May Have Popped

Despite this impressive growth, signs indicate that generative AI may be moving past its peak hype phase. According to Gartner’s “Hype Cycle for Artificial Intelligence, 2024,” generative AI has entered the “trough of disillusionment.” The firm stated, “the technology has yet to deliver on its anticipated business value for most organizations.” This sentiment has been echoed by other analysts. In June, Goldman Sachs posed the question, “Gen AI: too much spend, too little benefit?” Furthermore, the popularity of the Substack newsletter “AI Snake Oil,” which has amassed over 43,000 subscribers, suggests skepticism surrounding the sector’s value proposition.

Amidst this skepticism, there are indications of slowing growth. Reports suggest that scaling models within generative AI are plateauing, although Dario Amodei, CEO of Anthropic, has disputed this notion.

AI Remains a Strong Patent Area

While generative AI might be tempering, the race for AI patents is intensifying. Data from October 2024 reveals that Intel Corporation has obtained 1,499 AI patents across 1,389 unique patent families, with about 14.81% of its focus in machine learning (ML) applications. Following closely behind, Samsung Electronics has secured 1,002 patents, with an emphasis on neural networks.

Alphabet Inc. leads the way in ML patent concentration at 50.14%, while its subsidiary, DeepMind Technologies, shows an even greater focus with 55.88% of its patents in the neural network space. IBM represents a significant player as well, boasting an impressive 86.79% concentration in ML patents.

Chinese firms are also making their mark, with Tencent Holdings, Huawei Technologies, and Baidu each securing hundreds of patents in the AI sector, showcasing their originality with high ratios.

The publication trends in 2024 outline a maturation curve for various AI technologies. Generative AI and LLMs exhibit impressive growth, yet mature technologies like ML show steady, more predictable expansion at a CAGR of 21.6%, amounting to 140,574 publications this year. Technologies such as Edge Computing and Neural Networks appear to be plateauing, which suggests a higher level of maturity within these fields. In contrast, emerging technologies like Federated Learning continue demonstrating significant growth and interest.

Moving Beyond GenAI

The AI market, according to Gartner, is transitioning beyond the confines of generative AI. Organizations are encouraged to examine composite AI approaches, AI engineering, and knowledge graphs. Emerging technologies represent the next phase in AI development, integrating various methodologies for innovative solutions. This trend is increasingly reflected in the patent strategies of leading AI entities. For instance, Alphabet holds a well-rounded patent distribution across machine learning, neural networks, and knowledge-based systems, positioning itself robustly for future advancements.