Small Language Models (SLMs) are seen as key to unlocking AI innovation in Nigeria and Africa. They require less computational power than Large Language Models (LLMs), making them more accessible. Experts emphasize that SLMs can support localized AI solutions amidst infrastructural challenges, although they have limitations in handling complex language tasks.
Small Language Models (SLMs) present a viable opportunity for Nigeria and Africa to foster innovation in Artificial Intelligence (AI). Experts suggest that these models can enhance accessibility and efficiency, particularly essential in regions with limited computational infrastructure, such as Nigeria.
Since the launch of ChatGPT in November 2022, Large Language Models (LLMs) have demonstrated vast capabilities, leading to the development of models such as Google’s Gemini and Microsoft’s Co-pilot. While LLMs require substantial computational power and large datasets, SLMs are designed to function effectively with fewer resources, typically ranging from tens of millions to under 30 billion parameters.
Olubayo Adekanmbi and Ife Adebara, both advocates for SLMs, argue that these smaller models can deliver competitive performance in domain-specific tasks while being more cost-effective and efficient. They highlight that SLMs can address queries with localized expertise, thus making AI tools more accessible in Emerging Markets.
Nigeria’s draft AI strategy acknowledges the country’s aspiration to become a leader in AI development, noting that inadequate digital infrastructure presents a significant barrier. The strategy aims to create affordable and localized resource systems to support sustainable AI growth.
In discussing the practical impact of SLMs, Olivia Shone from Microsoft remarked that these models require lower computational resources and offer rapid response times, which aligns well with the needs of mobile-driven economies like Nigeria. Furthermore, SLMs are compatible with offline use, ensuring that people in rural areas can also participate in AI advancements.
Experts Libing Wang and Tianchong Wang indicated that SLMs can help circumvent obstacles associated with digital infrastructure in the Global South, allowing for the creation of bespoke technologies that cater to local needs and challenges. They argue that SLMs hold considerable potential for shaping the future of AI, emphasizing accessibility, efficiency, and affordability.
Despite their advantages, the World Economic Forum has cautioned that SLMs may struggle with complex language tasks and have performance limitations. Nevertheless, their adaptability and reduced resource demands could facilitate a significant leap forward for AI accessibility in regions like Nigeria.
Small Language Models represent a strategic path for Nigeria and Africa to enhance their AI capabilities by overcoming existing infrastructure limitations. By providing accessibility, efficiency, and localization, SLMs can enable innovative tech developments tailored to local challenges, despite some performance constraints when handling complex tasks. Their potential to bridge digital divides positions SLMs as vital tools for accessing AI benefits in emerging markets.
Original Source: businessday.ng
