Here’s how Nutanix is giving businesses data control in AI
• A lack of data control is stalling some businesses’ expansion with generative AI.
• Nutanix has a solution that maintains data control.
• GPT-in-a-box can help set businesses back on the right track with their AI aspirations.
As businesses increase their use of generative AI tools in their organization, some need to be more concerned about data control within their AI tools.
Most generative AI tools work with available data, and must properly acknowledge its source.
But fresh use cases arise as organizations strive to exploit generative AI to enhance customer service, boost developer productivity, refine operational efficiency, and perform any number of other critical tasks, including automated transcription of internal documents, rapid multimedia content searches, and automated analysis.
Despite recognizing the potential benefits of AI, many organizations are wrestling with escalating apprehensions related to data control, especially when it comes to safeguarding intellectual property, ensuring compliance, and preserving privacy.
Moreover, organizations that are trying to construct an AI-ready stack often struggle with the task of developing optimal support for machine learning (ML) administrators and data scientists. This challenge – and the potential high costs associated with AI investments – have led several enterprises to stall in their AI and ML strategic pursuits.
The common questions on data control with which organizations must grapple include to whom the source code belongs. Whose data is being used to generate an algorithm? How was the data compiled? Was it aggregated from multiple sources securely?
These are just some of the questions businesses have on data control when using generative AI tools.
Generative AI in Asia Pacific
Statistics from IDC show that Asia Pacific organizations currently lead the way in prioritizing generative AI investments, due to their proactive stance on new technologies and government support. IDC Survey data shows that two-thirds of Asia Pacific organizations are exploring potential use cases or are already investing in generative AI technologies in 2023.
IDC also highlights that the ongoing evolution of generative AI technology and data management presents challenges for governments developing regulatory frameworks that provide guardrails without creating obstacles to innovation. These challenges include data quality, ethical issues, deepfakes, copyright and IP complexities, talent shortages, and high technology costs.
As such, governments in several countries in the Asia Pacific have already initiated guidelines that will likely shape the direction of future policy and regulatory frameworks. These guidelines include adopting fundamental principles such as transparency, data protection, safety, IP protection, open data access, and ethical standards to address the immediate challenges.
Data control with Nutanix GPT-in-a-Box
To address these concerns, Nutanix introduced the Nutanix GPT-in-a-Box. The solution helps businesses looking to speed up their ventures into AI and machine learning (ML) advancement, but also retain authority over their data. The solution centers on a comprehensive software-defined AI-prepared platform and corresponding services to help organizations gauge and configure their hardware and software infrastructure, so they can deploy a curated selection of large language models (LLMs).
Using open-source AI and MLOps frameworks on the Nutanix Cloud Platform delivers customers a seamless way to obtain AI-ready infrastructure. That infrastructure is intended for fine-tuning and executing generative pre-trained transformers (GPT), encompassing LLMs at the edge or within their data center.
The Nutanix GPT-in-a-Box solution gives organizaions a readily deployable AI infrastructure that lets them exercise authority over their data, whether at the edge or within the core data center. It allows for the operation and refinement of AI and GPT models, while crucially maintaining data control.
Greg Macatee, Senior Research Analyst in the Infrastructure Systems, Platforms, and Technologies Group at IDC said “As customers look to design and deploy generative AI solutions, they find themselves struggling with balancing the deep expertise required to install, configure, and run these workloads with concerns around their data security and protecting company IP – all while controlling costs.
With GPT-in-a-Box, Nutanix offers customers a turnkey, easy-to-use solution for their AI use cases. It provides enterprises struggling with generative AI adoption an easier on-ramp to deployment.”
This new solution includes:
- The Nutanix Cloud Infrastructure platform, with both file storage and object storage solutions, the Nutanix AHV hypervisor, and Kubernetes, along with NVIDIA GPU acceleration.
- Nutanix services to help customers size their cluster and deploy an opinionated stack with open-source deep learning and MLOps frameworks, an inference server, and a curated set of large language models such as Llama2, Falcon, and MPT.
- The ability for data scientists and ML administrators to immediately use these models with their choice of applications.
The platform can also be used to run other GPT models and fine-tune these models with internal data.
“Helping customers tackle the biggest challenges they face in IT is at the core of what we do, from managing increasing multi-cloud complexity to data protection challenges, and now the adoption of generative AI solutions while keeping control over data privacy and compliance,” said Thomas Cornely, SVP, Product Management at Nutanix.
“GPT-in-a-Box is an opinionated AI-ready stack that aims to solve the key challenges with generative AI adoption and help jump-start AI innovation.”
Nutanix – bringing data control to your generative AI.
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