Fruit fly AI: SLMs are the new LLMs

AI is devouring the planet’s electricity ... already using up to 2% of global energy and projected to hit 5% by 2030. But a Spanish-Canadian company, Multiverse Computing, says it can slash that energy footprint by up to 95% without sacrificing performance. They specialize in tiny AI: one model has the processing power of just 2 fruit fly brains. Another tiny model lives on a Raspberry Pi. The opportunities for edge AI are huge. But the opportunities in the cloud are also massive. In this episode of TechFirst, host John Koetsier talks with Samuel Mugel, Multiverse’s CEO, about how quantum-inspired algorithms can drastically compress large language models while keeping them smart, useful, and fast. Mugel explains how their approach -- intelligently pruning and reorganizing model weights -- lets them fit functioning AIs into hardware as tiny as a Raspberry Pi or the equivalent of a fly’s brain. They explore how small language models could power Edge AI, smart appliances, and robots that work offline and in real time, while also making AI more sustainable, accessible, and affordable. Mugel also discusses how ideas from quantum tensor networks help identify only the most relevant parts of a model, and how the company uses an “intelligently destructive” approach that saves massive compute and power. 00:00 – AI’s energy crisis 01:00 – A model in a fly’s brain 02:00 – Why tiny AIs work 03:00 – Edge AI everywhere 05:00 – Agent compute overload 06:00 – 200× too much compute 07:00 – The GPU crunch 08:00 – Smart matter vision 09:00 – AI on a Raspberry Pi 10:00 – How compression works 11:00 – Intelligent destruction 13:00 – General vs. narrow AIs 15:00 – Quantum inspiration 17:00 – Quantum + AI future 18:00 – AI’s carbon footprint 19:00 – Cost of using AI 20:00 – Cloud to edge shift 21:00 – Robots need fast AI 22:00 – Wrapping up