Small Language Models are emerging as a vital avenue for Nigeria’s AI innovation, providing accessible solutions amid limited digital infrastructure. They offer reduced computational requirements, cost-efficiency, and adaptability, particularly beneficial for mobile economies. Experts advocate for SLMs to address local needs and enhance accessibility while acknowledging their limitations in complex tasks.
Small Language Models (SLMs) may provide a transformative avenue for Nigeria and the broader African continent to foster innovation in Artificial Intelligence (AI). Experts acknowledge that since the advent of ChatGPT in November 2022, Large Language Models (LLMs) have showcased the potential of AI, leading to advancements such as Google’s Gemini and Microsoft’s Co-Pilot. These developments have catalyzed numerous applications across generative text, speech, images, and video technologies.
The adoption of LLMs remains challenging in Nigeria due to their substantial computational infrastructure requirements and extensive datasets, as emphasized by AI leaders such as Olubayo Adekanmbi and Ife Adebara. Their findings suggest that SLMs could fill this gap by offering a more accessible and practical solution for AI integration in the region. Notably, while LLMs like GPT-4 can exceed 175 billion parameters, SLMs operate within a narrower range, typically from tens of millions to under 30 billion parameters.
The Nigerian government’s draft AI strategy highlights a crucial barrier: inadequate digital infrastructure threatens aspirations of becoming an AI powerhouse in Africa. The strategy aims to establish affordable, localized infrastructure and the necessary computational power for supporting AI advancements. Olivia Shone from Microsoft indicates that SLMs focus on specific tasks requiring less resource investment, thus enhancing accessibility and cost-effectiveness.
Adekanmbi and Adebara, co-founders of EqualyzAI, contend that SLMs facilitate sustainable AI development in emerging markets, countering issues such as limited infrastructure, offline access points, and budget constraints. They assert that SLMs not only reduce computational demands but also offer efficient, customizable solutions for both governmental entities and small enterprises striving to leverage generative AI in their operational processes.
Moreover, because SLMs necessitate minimal computational resources, they are particularly advantageous for mobile-driven economies like Nigeria. Their offline capabilities ensure access in rural areas, addressing the digital divide. Libing Wang from UNESCO notes that SLMs represent a strategic opportunity for Global South nations to harness local expertise in developing tailored technologies amid existing infrastructure challenges.
Overall, while SLMs exhibit significant potential in enhancing accessibility and efficiency in AI deployment, it is important to recognize their limitations. As cited by the World Economic Forum, SLMs face challenges in handling complex language tasks and maintaining accuracy, which may hinder their effectiveness in certain applications.
In conclusion, Small Language Models present a promising pathway for Nigeria and Africa to enhance their engagement with Artificial Intelligence. They offer solutions that are more accessible, cost-effective, and tailored to local needs, enabling a broader range of stakeholders to participate in AI innovation. Despite certain limitations, SLMs may indeed bridge critical gaps in digital infrastructure and promote sustainable technological development across the continent.
Original Source: businessday.ng
