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Home / Technology / Razer Unleashes AI Powerhouse for Developers

Razer Unleashes AI Powerhouse for Developers

8 Jan

•

Summary

  • Razer's new workstation and external accelerator aim for local AI development.
  • The workstation supports up to four professional GPUs for pooled VRAM.
  • Tenstorrent's accelerator connects via Thunderbolt and supports daisy-chaining.
Razer Unleashes AI Powerhouse for Developers

Razer has unveiled its entry into the AI development space with the Razer Forge AI Dev Workstation and an external AI accelerator. These products are designed to enable developers to work on advanced AI models locally, without the need for cloud-based services. The Forge AI Dev Workstation is a powerful system capable of training, inference, and simulation, supporting up to four professional graphics cards for significant VRAM capacity and featuring robust processor and memory options.

The company is also collaborating with Tenstorrent, led by industry veteran Jim Keller, on a compact external AI accelerator. This device connects via Thunderbolt 4 or 5, bringing local AI compute power to laptops and other systems. It's built on Tenstorrent's Wormhole architecture and integrates with an open-source software stack, facilitating the development of LLMs and image generation models.

Both solutions emphasize developer control, flexibility, and mobility. The external accelerator is notable for its ability to be daisy-chained, allowing multiple units to form a small cluster for handling larger AI models. Pricing and availability for the external accelerator are yet to be announced, marking an exciting new frontier for edge AI development.

Disclaimer: This story has been auto-aggregated and auto-summarised by a computer program. This story has not been edited or created by the Feedzop team.
The Razer Forge AI Dev Workstation is a high-performance system designed for local AI training, inference, and simulation, offering developers control over their projects without cloud dependencies.
Tenstorrent's compact AI accelerator connects via Thunderbolt to laptops, adding local AI compute power, and can be daisy-chained with other units for enhanced performance.
Developers would choose Razer's hardware for direct control over datasets and models, to avoid cloud subscription fees, and for flexible, portable AI development.

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