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Nervana

Nervana Systems was a San Diego deep-learning hardware and software startup acquired by Intel in 2016.

San Diego, CA, US🇺🇸
Founded
2014
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Contents

  1. 01Competitive Strengths
  2. 02Market Outlook
  3. 03Products & Services
  1. 01Competitive Strengths
  2. 02Market Outlook
  3. 03Products & Services

Competitive Advantages

Nervana's principal advantage was its combination of algorithm-level and silicon-level expertise: the team optimized deep-learning computation from the framework layer down to assembler-level kernels and then to a custom ASIC, rather than treating hardware and software as separate problems. Its neon framework was recognized among the fastest deep-learning libraries of its period, and its Winograd convolution implementation contributed to that standing.

The company also assembled a mix of investors spanning venture capital and strategic corporate backers, and it held a research contract with In-Q-Tel, the United States intelligence community's venture arm, which reflected the applied value of its technology. That combination of performance-focused engineering and enterprise-oriented cloud delivery distinguished it from research-only projects in the same field.

Source: vox.com

Market Outlook

When Nervana operated, businesses were adopting deep learning for tasks such as crop recognition, seismic-image analysis, and detection of fraudulent trading activity. Its cloud platform served companies building their own models, while its hardware program pursued processors designed around neural-network computation.

Intel's acquisition of Nervana in 2016 placed that hardware and software effort alongside established competition from Nvidia and Google's specialized chips. Intel subsequently stopped development of Nervana's training processors in 2020 and shifted its focus to Habana Labs, illustrating the risk that a strategic owner can replace an acquired accelerator program.

Source: extremetech.com

Product Overview

Nervana Systems offered a full-stack deep-learning platform spanning software and custom hardware. Its Nervana Cloud was a software-as-a-service environment for training custom deep-learning models, built on the company's open-source neon framework, which supported swappable hardware backends across CPUs, GPUs, and Nervana silicon.

The company was also developing the Nervana Engine, a custom ASIC accelerator optimized specifically for deep-learning computation, which it positioned as offering substantially higher compute density than general-purpose graphics processors because it carried only the circuitry deep-learning algorithms require. The platform was aimed at businesses building their own machine-learning capabilities rather than at consumers.

Source: en.wikipedia.org