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Promoting AI chip cost reduction and efficiency improvement: Nvidia's acquisition of two startups

白云追月素
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Nvidia is taking action again! After investing in over 30 startups last year, the company has recently invested in two more artificial intelligence startups, Run: ai and Deci.
On April 24th local time, Nvidia announced that it had signed a final acquisition agreement with Run: ai. The company believes that this can help customers more effectively utilize their AI computing resources.
Run: AI was founded in 2018 and is a workload management and orchestration software provider based on the open-source container orchestration platform Kubernetes. Currently, the deployment of AI is becoming increasingly complex, with workloads distributed across cloud, edge, and local data center infrastructure. Managing and orchestrating generative AI, recommendation systems, search engines, and other workloads requires complex scheduling to optimize system level and underlying infrastructure performance.
And Run: AI's products can achieve efficient resource utilization of GPU clusters. Simply put, its product can support developers to run multiple AI workloads in parallel, thereby improving the utilization efficiency of AI chips and reducing costs.
At present, Run: ai's solution has been integrated with Nvidia's DGX, DGX SuperPOD, Base Command, NGC container, and AI Enterprise software products. Nvidia's DGX and DGX Cloud customers will be able to use Run: ai's AI workload functionality.
Nvidia has not disclosed the details of the acquisition transaction amount and other terms. But according to Israeli media such as Calcalist, the transaction amount was $700 million.
Deci, another AI startup favored by NVIDIA, is also committed to achieving cost reduction and efficiency improvement in AI chips. According to The Information, Nvidia has agreed to acquire Israeli startup Deci, but the exact amount of the acquisition cannot be determined.
According to Deci's official website, the company was founded in 2019 and provides efficient generative AI and computer vision models that can be deployed in various environments while maintaining data security and controlling inference costs.
It is understood that its solution is to adjust the size of the AI model so that it can run cheaper on AI chips. At present, Deci has reached cooperation with multiple technology giants such as Microsoft, Intel, AMD, Amazon, etc.
It is not difficult to see that both of Nvidia's investments are aimed at helping its customers more effectively utilize their own AI chip products.
The Information report pointed out that two people familiar with the transaction situation said that Run: ai's ability to improve the efficiency of AI chips may attract more customers to use NVIDIA DGX Cloud. In addition, Nvidia may provide Deci and CUDA software, allowing developers to build AI driven applications more cheaply.
Nvidia also pointed out in its official release that customers expect to benefit from better GPU utilization, improved GPU infrastructure management, and greater flexibility brought by open architecture.
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