Let’s talk size not of ambition, but of models.
LLMs get the spotlight. But they also need massive infrastructure: supercomputers, endless power, and bandwidth that most parts of Africa simply don’t have.
SLMs (Small Language Models), on the other hand, offer a different promise efficiency without exclusion.
With new techniques like Upside-Down Reinforcement Learning and synthetic distillation, SLMs are proving that you don’t need to be big to be brilliant. They perform competitively across tasks while running on smaller devices, even mobile phones.
For Africa, this could be revolutionary.
Imagine AI tools built for classrooms in Kano, not just labs in California. Translation engines that understand Xhosa on a budget. Smart apps trained to pronounce your name right in Igbo, not English defaults.
At EqualyzAI, we’re watching the SLM wave closely. Because if LLMs built the highway, SLMs might just bring everyone on the ride.
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