Smaller AI Models Gain Momentum as Costs and Risks Rise

[AIcash]

As demand for AI efficiency grows, smaller models are emerging as a viable alternative to traditional large-scale systems developed by companies like OpenAI and Meta.

Multiverse Computing claims its compressed models can deliver faster responses at lower cost, narrowing the performance gap with large language models. These models are particularly attractive for enterprise use cases, including edge environments like drones and satellites where connectivity is limited.

With clients such as the Bank of Canada and Bosch, the startup is gaining traction—and is reportedly seeking new funding at a valuation above €1.5 billion as interest in efficient AI solutions accelerates.

[johnblockbuster]

So we spent years building massive models just to… not use them. Love that journey for us