The Shifting Balance in AI Research and Development
In recent years, the landscape of artificial intelligence (AI) research and development has undergone a significant transformation. Historically, academia was the driving force behind the release of machine learning models. However, by 2014, the balance began to shift, with industry increasingly taking the lead. In 2023, for example, industry released 51 notable machine learning models compared to just 15 from academia.
This shift is largely attributed to the growing demands of cutting-edge AI development, which now requires immense amounts of data, computational power, and financial resources—resources that are often beyond the reach of academic institutions. As a result, industry players, with their access to vast datasets and advanced computing infrastructure, have become the primary engines of AI innovation.
Data Scarcity and the Future of AI
This trend raises concerns about the sustainability of AI’s data-driven approach. Researchers from Epoch AI, a group dedicated to studying the evolution of advanced AI, have pointed out that future generations of computer scientists might face a shortage of high-quality data to further scale and improve AI systems. Their projections suggest that the stock of high-quality language data could be depleted as early as 2024, with low-quality language data potentially exhausted within two decades. Image data, too, may run out by the late 2030s to mid-2040s.
To address this challenge, the AI community is increasingly turning to synthetic data—data generated by AI models themselves. While synthetic data offers a potential solution to the looming data shortage, recent research highlights limitations in training models solely on this type of data. Nevertheless, the use of synthetic data remains an attractive option, particularly in areas where naturally occurring data is scarce, such as rare diseases or underrepresented populations.
Foundation Models: The New Frontier
The rise of foundation models, such as GPT-4, Claude 3, and Llama 2, has further revolutionized the AI landscape. These versatile models are trained on vast datasets and can be applied to a wide range of downstream tasks. According to data from Stanford’s Ecosystem Graphs, which tracks the foundation model ecosystem, the trend toward open access models has grown significantly, with 65.8% of foundation models released as open access in 2023.
The high costs associated with training these models have become a prominent topic of discussion. For instance, OpenAI’s CEO, Sam Altman, revealed that the training cost for GPT-4 exceeded $100 million. Such costs have largely excluded academic institutions from developing their own leading-edge models. In response, policy initiatives like President Biden’s Executive Order on AI aim to level the playing field by creating a National AI Research Resource, providing non-industry actors with the necessary compute and data to conduct high-level AI research.
Understanding the cost structure of AI training is crucial, yet detailed information remains scarce. To address this, the AI Index, in collaboration with Epoch AI, has made significant strides in estimating these costs, analyzing factors such as training duration, hardware utilization, and other technical details.
Morocco’s AI Revolution: A New Leader in Africa ?
Morocco is rapidly positioning itself as a key player in the African AI landscape, leveraging its strategic location, growing technological infrastructure, and forward-looking policies. The Moroccan government’s commitment to digital transformation and AI adoption is evident in its national strategies, such as the “Morocco Digital 2025” plan, which aims to foster innovation and enhance the country’s technological capabilities. This plan includes a focus on AI as a critical component for driving economic growth and improving public services.
The Moroccan AI ecosystem is supported by a network of academic institutions, startups, and research centers that are increasingly engaged in AI research and development. Initiatives like the establishment of AI research labs at major universities, including Mohammed VI Polytechnic University (UM6P) and Hassan II University, are creating hubs for innovation and talent development. These institutions are not only advancing AI research but also collaborating with international partners to bring cutting-edge technologies to the Moroccan market.
Moreover, the country’s strategic position as a gateway between Africa and Europe is enhancing its role in the broader AI landscape. Morocco is becoming a hub for AI-driven projects that aim to address both local and regional challenges, such as healthcare access, agricultural productivity, and smart city development. The government’s emphasis on fostering public-private partnerships is also contributing to the growth of the AI sector, encouraging collaboration between Moroccan tech startups and global technology firms.
As Morocco continues to build its AI infrastructure, there is a growing emphasis on aligning with international standards and fostering an innovation-friendly environment. The country’s efforts to improve collaboration between academia, industry, and government are positioning it as a leader in AI innovation in the region, with the potential to influence AI adoption across Africa.
References:
- “Morocco Digital 2025” National Strategy Report (2023)
- Mohammed VI Polytechnic University (UM6P) AI Research Initiatives (2023)
- Hassan II University AI Development Programs (2023)
- AI Index Report 2024
- Epoch AI Research Data (2024)
- Stanford Ecosystem Graphs (2023)
- Executive Order on AI, U.S. Government (2023)