MAGIC Research Introduces Fabric Hypergrid for Cost-Effective AI
MAGIC Research has launched Fabric Hypergrid, a private AI platform that aims to significantly reduce computing costs by 90%, announced in a press release. This innovative platform is designed to provide organizations with a scalable, high-performance AI infrastructure that is both cost-effective and secure.
Fabric Hypergrid is a multi-model, multimodal, and hardware-agnostic AI platform. It optimizes AI workloads by deploying tasks across a mix of state-of-the-art and legacy GPUs, CPUs, and accelerators. This approach allows businesses to transform their existing hardware into an enterprise-grade AI supercomputer without compromising on speed, security, or scalability.
The platform supports a wide range of applications, including text, image, audio, and video generation, as well as complex workflows like course creation and enterprise automation. It also caters to research initiatives in fields such as molecular research and computational chemistry. Fabric Hypergrid's flexible deployment options allow it to be installed on-premises, in the cloud, or in hybrid environments, offering companies the freedom to choose configurations that best meet their compliance, security, and performance needs.
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Whitepaper
Tensordyne Napier: What If One Rack Could Do the Work of Nine?
Tensordyne
This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.
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