The generative AI race has long been a game of ‘bigger is better.’ But as the industry hits the limits of power consumption and memory bottlenecks, the conversation is shifting from raw parameter counts to architectural efficiency. Liquid AI team is leading this charge with the release of LFM2-24B-A2B, a 24-billion parameter model that redefines
The post Liquid AI’s New LFM2-24B-A2B Hybrid Architecture Blends Attention with Convolutions to Solve the Scaling Bottlenecks of Modern LLMs appeared first on MarkTechPost. Read More
