Nutanix Enterprise AI FAQs

Nutanix Enterprise AI Overview Questions and Answers

What is Enterprise AI?

There are many “types of AI” today. These include AI types such as generative AI (GenAI) with visual, text, analytics, etc., computer vision, natural language processing (NLP), etc. Regardless of the type of AI, businesses need AI to align with their outcomes and strategy. Enterprise AI is the focus of all types of AI aligned to business outcomes for resiliency, Day 2 operations, and security surrounding AI.

The Nutanix GPT-in-a-Box solution is tailor-made for enterprise AI. Driven by a service-led approach, GPT-in-a-Box has evolved to include new products and features making it a leading answer for enabling enterprise AI with turnkey infrastructure and composable solutions on-premises or in the public cloud.

A key feature of GPT-in-a-Box 2.0 is the Nutanix Enterprise AI product that makes deploying, operating, and monitoring generative AI models (large language models, LLMs) and secure APIs for enterprise AI applications simple. Nutanix Enterprise AI is the first component of GPT-in-a-Box enterprise customers' leverage to see tangible results for their enterprise AI initiatives, with an ease of use that may substantially reduce or even eliminate the need to hire new talent, allowing customers to scale current IT resources into AI resources.

What is Nutanix Enterprise AI?

Nutanix Enterprise AI (NAI) offers endpoint APIs for leading LLM providers, including NVIDIA NIM and HuggingFace, making it easy for organizations to deploy a wide range of Gen AI models on-premises or in the public cloud. NAI includes a simple UI, role-based access controls (RBAC), and the capability for untethered operations (dark site or air-gapped deployments) to simplify the operation, monitoring, and adaptation of AI models (LLMs) with enterprise resiliency, Day 2 operations, and compliance.

What’s the difference between enterprise AI and Nutanix Enterprise AI?

What is the difference between inference, tuning, and training when it comes to AI?

Here are the technical details of the differences:

AI Model Training: AI model training is the initial and most comprehensive process of building a model from scratch
AI Model Fine-Tuning: Fine-tuning is the process of adapting a pre-trained model for a specific task or domain
AI Model Inference: Inference is the application of a trained or fine-tuned model to make predictions or draw conclusions from new data

To make this easier to explain, GenAI explains these using a cake-baking metaphor:

AI model training is baking the cake.
AI Model fine-tuning is decorating it.
AI Model inference is eating it!

What is the difference between generative AI and ‘regular’ AI?

These days, these terms may be used interchangeably, but their outcomes are different. GenAI describes it as the following:

Generative AI and traditional (predictive) AI differ fundamentally in capabilities, applications, and technologies.

Traditional AI focuses on performing specific tasks like data analysis, predictions, and pattern recognition, utilizing rule-based systems and narrow machine learning algorithms.
Generative AI (GenAI) creates original content—such as text, images, and music—using advanced deep learning techniques and large language models. While traditional AI is designed for narrow tasks and requires specialized knowledge, generative AI is more versatile and accessible, allowing for natural language interactions and the generation of novel outputs across various modalities.

As the field evolves, these two approaches increasingly integrate to enhance overall AI functionality.

Does Nutanix Enterprise AI provide generative AI (GenAI) apps, LLMs, and endpoint APIs?

Nutanix Enterprise AI provides Nutanix-validated third-party LLMs and secure APIs to create endpoints for generative AI applications you provide.

Nutanix does not provide GenAI applications but has multiple AI partners that can help you can learn more about GenAI you can learn about here: https://www.nutanix.com/partners/technology-alliances?tag=nutanix:filters/solution-categories/ai

How is Nutanix Enterprise AI different?

Nutanix Enterprise AI provides three key differentiators for inferencing:

Makes IT Resources AI Resources
- Enterprise AI can be complex. From new technical requirements to vastly different concepts, it may feel like a whole new world.
  
  Nutanix Enterprise AI helps ease this transition by providing simple workflows to find, deploy, manage, and test generative AI models (LLMs) in minutes. Secure APIs are included to help make your enterprise AI apps work. Key metrics and monitoring help you understand gaps or problems as you ramp up operations.
Simplify LLM (large language model) Deployment and Operations
- Many enterprise AI solutions have dedicated common line instructions that present a steep learning curve for implementing and operating core enterprise AI components.
  
  Nutanix Enterprise AI provides a simple, yet elegant, user interface that allows you to quickly ramp on the LLMs and secure APIs you create and manage. Paired with secure role-based access controls, creating a secure enterprise AI environment is a snap. Nutanix Enterprise AI integrates with Hugging Face and NVIDIA NIM out-of-the-box to deploy the Nutanix co-validated LLM you need. Not available? Simply upload your own AI model (LLM) for total control.
Enables Choice for Enterprise AI
- What works for generative AI today may need to be updated quickly as new, better models are made available. The requirement to be able to adapt and shift demands the ability to choose, but without changing architectures or infrastructures.
  
  Nutanix Enterprise AI provides a choice of Kubernetes® environments, including the Nutanix Kubernetes Platform (NKP) solution, products from software partners (e.g. Rancher and Docker), bare metal, or hyperscaler container instances (e.g., Google Cloud, AWS, and Azure). When a new model is available, you can decide to wait for a co-validation of the new model from Nutanix, or upload it yourself and with ease provide a new LLM and API to your generative AI applications.
For a deeper dive, check out the diagram below for more considerations:

Who should consider Nutanix Enterprise AI?

Nutanix customers and prospective customers should consider the improvements that Nutanix Enterprise AI can bring to their AI use cases.

For Nutanix Customers:

Leverage your Nutanix infrastructure and investments right now making GenAI with Nutanix Enterprise AI seamless to secure, manage, and deploy AI key components like your choice of AI models and APIs for GenAI apps.
For further simplicity, use the Nutanix Kubernetes Platform and deploy Nutanix Enterprise AI through its validated application catalog. Nutanix Kubernetes Platform makes managing and scaling Kubernetes effortless from the edge to public clouds.

For prospective Nutanix Customers:

Use Nutanix GPT-in-a-Box - a turn-key solution with your choice of Nutanix-validated hardware platforms and a Nutanix-validated stack of software products ranging from infrastructure management to Kubernetes and Nutanix Enterprise AI, bundled with professional services.
Bring-your-own-infrastructure - Run Nutanix Enterprise AI on VMware by Broadcom* VCF, three-tier datacenter infrastructure with the Kubernetes you choose, or even on bare-metal Kubernetes servers.
Leverage previous investments or a mix - Already have GenAI investments you’re using? No problem. Nutanix products can be configured and leveraged in different ways to take advantage of your AI stack by giving you choices like:
- Using Red Hat OpenShift? Deploy Nutanix Enterprise AI.
- Using public cloud Kubernetes for Google Cloud GKE, AWS EKS, or Azure AKS? Deploy Nutanix Enterprise AI.
- Using NVIDIA AI Enterprise? Deploy Nutanix Cloud Infrastructure and Nutanix Unified Storage and use Nutanix Enterprise AI to deploy NVIDIA NIM, part of the NVIDIA AI Enterprise software platform.
- Using open-source tools? Deploy Nutanix Kubernetes Platform for easy Kubernetes management and Nutanix Enterprise AI.

* Nutanix, Inc. is not affiliated with VMware by Broadcom or Broadcom.

What is the difference between Nutanix Enterprise AI and GPT-in-a-Box?

Nutanix Enterprise AI is a product licensed by Nutanix. Nutanix GPT-in-a-Box (v1.0 and 2.0) is a validated Nutanix solution/offer for enterprise AI, including the Nutanix Enterprise AI product among other Nutanix products for infrastructure, data, security, virtualization, Kubernetes, and management. This Nutanix-validated stack allows you to build secure enterprise AI on private clouds, and public clouds, or to leverage both creating a hybrid multicloud.

Nutanix Enterprise AI Product Questions and Answers

How does Nutanix Enterprise AI work?

What are the key features of Nutanix Enterprise AI?

The following list outlines the most prominent components:

Elegant, Enterprise-Grade User Interface
Choice of AI Models (LLMs) from Hugging Face or NVIDIA NIM
Upload Your Own AI Models (LLMs)
API Token Creation and Management
Partner API Token Management for Hugging Face and NVIDIA NIM
API Code Samples
Role-Based Access Controls (RBAC)
AI Model Preflight Testing
AI Model and API Monitoring
Kubernetes Resource Monitoring
GPU Usage Monitoring
Event Auditing
Integrated Nutanix Pulse Reporting

What is an IEP?

Which AI models (LLMs) are available with Nutanix Enterprise AI?

Currently, only text-based Generative AI models from Hugging Face and NVIDIA NIM via NVIDIA NGC are validated for Nutanix Enterprise AI. The validated models supported are listed in the product when choosing either option. There is also an option to upload your own, private model using whatever model you choose.

Below is the launch-day list of models in Nutanix Enterprise AI (as of Nov. 12, 2024)

Does Nutanix Enterprise AI have integration with Hugging Face?

How do I get models from Hugging Face?

A Hugging Face API token is required inside of Nutanix Enterprise AI to make API calls to Hugging Face. This can be created using the steps from Hugging Face.

Depending on the model available on the Nutanix Enterprise AI list, it is likely steps must be taken to get access to models through a Hugging Face Gated Repository. A Gated Repository is configured by a model owner (e.g., Meta, Google, etc.) and must be followed in order to correctly download and gain access to a model. The steps to do this are available from Hugging Face.

Why doesn’t the list of models for Hugging Face reflect everything on their website?

Does Nutanix Enterprise AI have integration with NVIDIA NIM?

Does NVIDIA NIM require a license when used with Nutanix Enterprise AI?

What is NVIDIA NGC?

Do NVIDIA GPUs require a license when used with Nutanix in general?

How is Nutanix Enterprise AI licensed?

Is there a trial license for Nutanix Enterprise AI?

Is Nutanix Enterprise AI included with other Nutanix product licenses?

If I have GPT-in-a-Box 1.0 today can I upgrade to GPT-in-a-Box 2.0 and receive access to Nutanix Enterprise AI?

Is hardware required to run Nutanix Enterprise AI?

Which AI Accelerators (i.e., GPUs, CPUs, etc.) does Nutanix Enterprise AI support?

What GPUs are supported for Nutanix Enterprise AI?

NVIDIA GPUs.

Each hardware/server system supports different GPUs. Also, Kubernetes must be configured to leverage GPUs. Please check compatibility for GPUs via these locations:

Enabling Kubernetes to run with GPUs:
- https://www.run.ai/guides/multi-gpu/kubernetes-gpu
Nutanix hardware/server GPUs:
- https://portal.nutanix.com/page/documents/compatibility-interoperability-matrix/nvidia-drivers

What about CPUs? Is Intel AMX supported for Nutanix Enterprise AI?

What other Nutanix products are typically used with Nutanix Enterprise AI?

Does Nutanix have AI partners they recommend?

Are there services included to help deploy and operate Nutanix Enterprise AI?

Where can Nutanix Enterprise AI be deployed?

On any environment with a CNCF-certified (Cloud Native Computing Foundation) Kubernetes runtime
We also have support for the following:
- Via Nutanix hyperconverged infrastructure (HCI) on any supported system that includes GPUs for AI acceleration through the AHV hypervisor
- Via Nutanix Kubernetes Platform (NKP)
- Via any supported hyperscaler using public cloud-based infrastructure-as-a-service.
  Currently, we support:
  - AWS EKS
  - Azure AKS
  - Google Cloud GKE
- Via bare metal
- Any dark site or air-gapped environment (non-internet connected) with CNCF-certified Kubernetes running

Does Nutanix Enterprise AI require Nutanix hyperconverged infrastructure (HCI)?

Can Nutanix Enterprise AI be deployed in public clouds

Why should I deploy Nutanix Enterprise AI in a public cloud?

Nutanix Enterprise AI helps streamline the development and deployment of LLMs (large language models) and APIs of generative AI applications.

Nutanix Enterprise AI can be run on any CNCF-certified Kubernetes environment making it simple to deploy on public clouds. Once deployed, other public cloud services can be used, like storage, applications, etc. This helps public-cloud-focused organizations to leverage their models and data in a secure location of their choice, on their VPCs and networks they control.

The value of deploying Nutanix Enterprise AI isn’t to compete with similar public cloud offerings, but to make testing and development of LLMs easier and faster. Once your LLMs have been validated by you, Nutanix Enterprise AI can be used in production, or a validated LLM can be handed off to a discrete LLM production workflow (LLMOps).

For customers wanting private enterprise AI, Nutanix Enterprise AI can be used within public cloud VPCs or on-premises to create a private cloud using Nutanix hyperconverged infrastructure (HCI).

Can Nutanix Enterprise AI be run in a dark-site/air-gapped environment?

Where can I find the technical documentation for Nutanix Enterprise AI?

Does Nutanix Enterprise AI have a validated design or reference architecture?

Who are the 3rd-party vendors and partners that work with Nutanix Enterprise AI?

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