Author: Steve Fenton

  • hosted·ai and FuriosaAI partnership logo emphasizing AI infrastructure and Tensor Contraction Processors for efficient cloud deployments

    FuriosaAI and hosted·ai Form Strategic Partnership to Deliver Industry-Leading AI Infrastructure Powered by Tensor Contraction Processors

    Redefining price/performance/power for AI cloud deployments with next-generation inference hardware

    Santa Clara, CA – 8th July 2025 – FuriosaAI, a pioneering leader in next-gen AI semiconductor, today announced a strategic partnership with hosted·ai to deliver ultra-efficient, high-performance AI infrastructure built on Furiosa’s Tensor Contraction Processor (TCP) architecture. The hosted·ai cloud platform will fully support Furiosa’s flagship RNGD (pronounced “Renegade”) processors, enabling service providers to leverage TCP-powered infrastructure for hosting AI workloads. 

    hosted·ai is a turnkey AI cloud platform for service providers. It delivers multi-tenant virtualization of infrastructure for AI inference and training, with full software-defined control and oversubscription of hardware accelerators such as RNGD and GPUs. This enables service providers to pool the resources of multiple accelerators, provision those resources on demand to multiple clients, and sell 4x-10x the physical capacity available. As a result they can price their offerings competitively and improve unit economics, achieving higher revenue with an increasing average margin.

    The new partnership will add support for Furiosa’s flagship RNGD Processor for LLM and agentic AI inference to the hosted·ai platform. RNGD leverages Furiosa’s Tensor Contraction Processor (TCP) chip architecture, which solves the fundamental hardware challenge of running AI algorithms: providing not just raw compute power, but also using that compute effectively and efficiently to deliver excellent real-world performance. 

    “We’re excited by this partnership and its potential to transform the cost and impact of AI infrastructure,” said Furiosa’s SVP of Product and Business, Alex Liu. “Furiosa’s processors are purpose-built for AI and represent a huge leap forward in performance per watt compared to GPUs thanks to our Tensor Contraction Processor (TCP) architecture. hosted·ai has the same devotion to efficiency and performance in its AI cloud software stack, enabling service providers to properly virtualize the accelerator and maximize utilization. This unique combination delivers the best solution for sovereign service provider AI clouds.” 

    “This partnership is an important step in our mission to make AI infrastructure accessible and affordable for service providers and their customers,” said Ditlev Bredahl, CEO of hosted·ai. “Together we’ll bring new ways for service providers to accelerate AI workloads with reduced hardware CAPEX and OPEX, optimal utilization, sustainable profitability for their business, and the best price/performance for their customers.”

    Availability of Furiosa RNGD support in the hosted·ai platform is expected by the end of 2025. Looking ahead, the two companies plan to develop an off-the-shelf appliance for service provider AI cloud, combining hosted·ai software, Furiosa accelerators, and rack server modules for easy turnkey adoption by service providers.

    About hosted·ai
    hosted·ai provides software to make AI infrastructure and GPUaaS simple and profitable for service providers. The hosted·ai platform fully virtualizes AI datacenter infrastructure, including GPUs and other hardware accelerators. This makes it possible to share and utilize 100% of hardware resources with users in a secure multi-tenant environment, which reduces the overall hardware requirement, minimizes idle resources, and dramatically changes the cost/revenue/margin equation for AI cloud service providers. For more information, visit https://hosted.ai.  

    About furiosa.ai
    FuriosaAI is building a new class of AI processor for enterprise and data center workloads. Powered by the Tensor Contraction Processor (TCP) architecture, Furiosa delivers sustainable, high-efficiency AI compute designed from the ground up for modern inference applications. Its mission is to democratize powerful AI through AI-native designed ASICs and software stack, giving everyone on Earth access to powerful AI. For more information, please visit furiosa.ai.

  • Software-Defined GPU whitepaper cover, highlighting GPUaaS benefits for service providers and AI hosting, with title and key topics on virtualization.

    Software-Defined GPU

    Software-Defined GPU

    Making GPUaaS work for service providers and the mainstream AI hosting market

    Software-Defined GPU whitepaper cover, highlighting GPUaaS for service providers and AI hosting, featuring title and key points on GPU virtualization methods.

    You’re not virtualizing GPU the wrong way – you’re just not doing it the optimal way for maximum utilization, flexibility and ROI from your hardware investments.

    This high-level whitepaper explains the difference between GPU virtualization and true GPU as a Service (GPUaaS).

    It explores the benefits and drawbacks of GPU passthrough, instancing and slicing, and explains why service provider GPUaaS requires a different approach – especially for AI inference workloads. To get your free copy, just fill out the form.


    Contents

    Why GPU virtualization ≠ GPUaaS

    What does service provider GPUaaS need?

    Software-Defined GPU requirements

    hosted·ai GPUaaS architecture

    hosted·ai hyperconverged platform

    Standalone GPUaaS with hosted·ai

    More information

  • Three GPUaaS playbooks for service providers by hosted·ai, focusing on AI infrastructure and cloud hosting solutions.

    Three GPUaaS playbooks for service providers

    Three GPUaaS playbooks for service providers

    GPU-as-a-Service is a huge opportunity for the cloud hosting industry – but what kind of GPUaaS should you launch to compete, grow and make serious money selling AI hosting? In this 30-minute session we explore three go-to-market playbooks for GPUaaS. Fill out the form to watch it now.

    Speakers:

    Ditlev Bredahl, CEO of hosted·ai, smiling in a casual setting, emphasizing leadership in GPU-as-a-Service strategies for service providers.

    Ditlev Bredahl

    CEO

    hosted·ai

    Man with beard and glasses wearing a light vest, smiling and posing in a professional setting, related to GPU-as-a-Service discussions at hosted·ai.

    Narendar Shankar

    CCO

    hosted·ai


    What will you learn?

    We’ll give you a quick introduction to hosted.ai, and how it overcomes the drawbacks of the way that GPU cloud is built and sold today. Then, we’ll focus on the opportunities this creates for service providers to fill those gaps in the market, with three suggested GPUaaS playbooks:

    Developer-Focused GPUaaS: why not build a DigitalOcean for GenAI? Here’s how we’d do it.

    SLA-Focused GPUaaS: the Neoclouds might be super-rich, but their service levels don’t make sense. You can do better, of course.

    By The Numbers: in today’s GPUaaS market there is a LOT of space to adjust price and margin in your favor, in your customers’ favor, or both.

  • Three GPUaaS playbooks for service providers – webinar replay

    GPU-as-a-Service is a huge opportunity for the cloud hosting industry – but what kind of GPUaaS should you launch to compete, grow and make serious money selling AI hosting? In this 30-minute session we explore three go-to-market playbooks for GPUaaS.

    Speakers:

    Ditlev Bredahl, CEO of hosted·ai, smiling in a casual setting, emphasizing leadership in GPU-as-a-Service strategies for service providers.

    Ditlev Bredahl

    CEO

    hosted·ai

    Man with beard and glasses wearing a light vest, smiling and posing in a professional setting, related to GPU-as-a-Service discussions at hosted·ai.

    Narendar Shankar

    CCO

    hosted·ai

    What will you learn?

    We’ll give you a quick introduction to hosted·ai, and how it overcomes the drawbacks of the way that GPU cloud is built and sold today. Then, we’ll focus on the opportunities this creates for service providers to fill those gaps in the market, with three suggested GPUaaS playbooks:

    Developer-Focused GPUaaS: why not build a DigitalOcean for GenAI? Here’s how we’d do it.

    SLA-Focused GPUaaS: the Neoclouds might be super-rich, but their service levels don’t make sense. You can do better, of course.

    By The Numbers: in today’s GPUaaS market there is a LOT of space to adjust price and margin in your favor, in your customers’ favor, or both.