Why Small AI Models Will Beat Giant Ones for Most Businesses
Most conversations about AI focus on the biggest models. They are impressive, and they can do almost anything. But most businesses do not need a model that can do anything. They need one that does a single job extremely well, every time, at a cost that makes sense.
Giant models are generalists
A large general model is like hiring a brilliant consultant for every small task in your company. It works, but it is slow, expensive and often more than the job needs. For tasks that repeat thousands of times a day, those costs add up quickly.
Small models are specialists
A small model trained for one task behaves more like a skilled specialist. It answers in milliseconds, runs on modest hardware and can be trained on your own data so it understands your exact use case.
- Lower running costs, because each answer needs far less computing power
- Faster responses, which matters for anything customers see
- More control, since the model and the data stay with you
- Easier testing, because a narrow job is easier to measure
How distillation makes this possible
Distillation uses a large model as a teacher. It produces high quality examples for one specific task, and a small student model learns to copy that behaviour. The student does not need the teacher's general knowledge. It only needs to master its one job.
Where small models work best
- Sorting and tagging documents, emails or support tickets
- Matching related items, like linking video clips on the same story in Havoc
- Pulling key fields out of forms, invoices or resumes
- Scoring quality, risk or priority in a consistent way
When you still want a big model
Open ended conversation, complex reasoning across many topics and early experiments are still where large models shine. A sensible approach is to explore with a big model first, then distil the parts that repeat into small, fast models.
The practical future of AI
I believe most real business value will come from many small, precise models working together rather than one giant model doing everything. They are cheaper, faster and easier to trust. That is the kind of AI I build.