The Transformer architecture has become a major component of the success of large language models (LLMs). To further improve LLMs, new architectures that may outperform the Transformer architecture are being developed. One such approach is Mamba, a state space model. The paper “Mamba: Linear-Time Sequence Modeling with Selective State Spaces” introduces Mamba, which we have … Read more
Big Data Digest Authorized Reprint from Leading Technology Author丨Congerry Transformer Challenged! In June 2017, eight Google researchers published a groundbreaking paper titled “Attention is All You Need”. It is called groundbreaking because this paper proposed a new neural network architecture – the Transformer, which opened a new era of generative artificial intelligence and large models. … Read more
Feng Se from Aofeisi Quantum Bit | Public Account QbitAI Exciting news! The first project to truly scale the popular Mamba architecture to a sufficiently large size has arrived. 52 billion parameters, still using the Mamba+Transformer hybrid architecture. Its name is Jamba. By taking the strengths of both architectures, it achieves both model quality and … Read more
New Intelligence Report Editor: Editorial Department [New Intelligence Guide] The production-grade Mamba model with 52B parameters is here! This powerful variant, Jamba, has just broken the world record, capable of directly competing with Transformers, featuring a 256K ultra-long context window and a threefold throughput increase, with weights available for free download. The Mamba architecture, which … Read more
Machine Heart reports Editor: Rome Rome Video understanding faces immense challenges due to significant spatiotemporal redundancy and complex spatiotemporal dependencies. Overcoming these two issues is extremely difficult, and CNNs, Transformers, and Uniformers struggle to meet these demands. Mamba presents a promising approach; let’s explore how this article creates video understanding with VideoMamba. The core goal … Read more