How Nutanix uses GenAI versatility in its GPT-in-a-Box development package
Enterprises are busy trying to figure out how they can use GenAI to move themselves ahead in their markets.
It's artificially generated rather than collected from real-world events and is typically created using algorithms, computer simulations, or other techniques to mimic the statistical properties and patterns of real data.show that synthetic data is also being used for training. Llama 3.1 was pretrained on ~15 trillion tokens of data from publicly available sources. The fine-tuning data includes publicly available instruction datasets as well as over 25M synthetically generated examples.
, is that it provides users with a consistent set of tools, data services, and best practices to accelerate development and usage of their AI applications. This can help to reduce operational complexity and costs compared to a multi-vendor approach, where users need to learn and manage multiple tools and platforms.
"Our enterprise users will need to look at a consistent set of tools and best practices/processes to accelerate their GenAI applications," Dutta added."In order to do that, we feel that we are extremely well-positioned to provide them with an entire set of full-stack solutions and with the right partnerships."
All these are embodied in the company's GPT-in-a-Box solution. There's an entire menu of tools and services all in one place for users to pick and choose the ones they want to deploy first, second, and third, according to their own GenAI strategy.Dutta described a few dominant use-case types that Nutanix has identified early in the GPT-in-a-Box era.
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