SMRTR AIJan 15, 2026PYMNTS

AI’s New Math: More Power, Less Compute

SMRTR summary

AI development is breaking free from its traditional cost trap through mixture-of-experts (MoE) architectures that activate only specialized sub-models needed for each task rather than powering entire networks for every query. This selective computing approach enables banks and fintech companies to deploy advanced AI across high-volume operations like fraud detection and real-time payments without prohibitive costs, making organization-wide AI implementation economically viable.

SMRTR provides this summary for quick context. The original article belongs to PYMNTS.

Read the original article
SMRTR AI

Get the next batch of curated stories in your inbox.

This archive is built from SMRTR newsletter stories. Subscribe for hand-picked stories without the extra noise.

Related Stories

Browse AI
AIAug 27, 2026

SpaceKit AI

SpaceKit AI is a public research hub for Growformer, an ML system with a promote-freeze neural substrate, language model experiments, neural cellular automata, and reproducible...

AIAug 27, 2026

Small Models Have Arrived

Small AI models are now 10x cheaper than before, making high-volume consumer and business AI apps financially viable—tasks costing $1 now cost ~$0.10, enabling affordable,...

AIAug 27, 2026

Why I Am Right About AI

The piece satirizes tech-bro certainty about AI replacing writers, using absurd logic and fake statistics to parody real thought leaders—exposing how hollow and self-serving those...