Data center infrastructure supplier Nutanix Inc. today is jumping into the generative pre trained transformer fray with GPT-in-a-Box, which it describes as a toolkit for companies that are looking to jumpstart artificial intelligence and machine learning projects without risking their data or budget.

Nutanix described the new offering as a full-stack, software-defined artificial intelligence-ready platform that includes all the elements needed to build AI-ready infrastructure. It includes services to help organizations size and configure hardware and software infrastructure to support a curated set of large language models using popular open-source AI and machine learning operations frameworks on the Nutanix Cloud Platform. Customers can procure AI-ready infrastructure to fine-tune and run generative GPT models, including LLMs.

“AI applications are new and introduce performance considerations that are different from traditional applications,” said Lee Caswell, senior vice president of product and solutions marketing at Nutanix in emailed comments. “Hardware to develop large language models, for example, can be quite different from hardware best suited to run AI inferencing. Similarly, different AI software workflows can require different performance needs between, say, a natural language processing and a video analytics app.”

The company said the offering is aimed at companies that want to begin working with AI but are concerned about intellectual property, compliance and privacy issues. They also struggle with how to best support machine learning administrators and data scientists and the risk that costs could rise out of control.

Security concerns

McKinsey & Co. reported that cybersecurity, regulatory compliance, privacy and model explainability are the top risks that hold organizations back from investing in AI and that there has been little perceived mitigation of any of those risks since 2019. “There is also a consideration around large upfront AI investment costs which can stall AI and ML initiatives,” Caswell said. “We are offering a service to help customers optimize their infrastructure with an eye to preserving data privacy, governance, and security.”

Nutanix GPT-in-a-Box is described as a ready-to-use customer-controlled AI infrastructure package for edge or data center deployment that includes a full set of security and data protection offerings.

It includes Nutanix’s cloud infrastructure, file and object storage, the Nutanix AHV hypervisor and Kubernetes platform with Nvidia Corp.’s graphics processing unit acceleration, services to help users size their cluster and deploy open-source deep learning and MLOps frameworks, an inference server and a curated set of large language models, including Llama2, Falcon LLM and MosaicML.

The company said data scientists can immediately use the supplied models with their choice of applications as well as with an enhanced terminal or command language interface. The platform can also be leveraged to run other GPT models as well as to fine-tune models leveraging internal data hosted on the included file and object services.

Pricing wasn’t specified.

Photo: Nutanix

Nutanix announces the new AI solution Nutantix GPT-in-a-box. The tool should make it easier for companies to introduce generative AI into the workplace.

Nutanix GPT-in-a-box is a new tool from Nutanix to help companies get started implementing AI and machine learning (ML). Notably, the tool allows companies to maintain full control over their data.

The new platform’s essential goal is to help define hardware and software infrastructure suitable for running AI and ML on. To do this, the platform can rely on the capabilities of open-source AI and MLOps frameworks from the Nutanix Cloud Platform.

The tool focuses on implementing generative AI in the workplace, but many enterprises are likely to ignore the tool. Indeed, generative AI was found to be banned in three-quarters of organizations, according to an earlier survey. There are two concerns about generative AI tools that trigger the ban. Many focus on the risk of using unsecured apps, while others fear that company secrets will leak.

Nutanix recognizes these fears. The tool, therefore, puts data management in the company’s hands but also adds (data)security capabilities to the platform.

According to the company, many organizations additionally struggle with questions about how best to support ML administrators and data scientists. To that end, Nutanix GPT-in-a-Box provides turnkey AI infrastructure for the edge or core data center.

Also read: Nutanix wants to be infrastructure for all workloads, including Kubernetes

Nutanix has launched GPT-in-a-Box, a bundled service that adds artificial intelligence (AI) software stack elements – such as foundation models and AI frameworks – to scale-out hyper-converged infrastructure (HCI).

GPT-in-a-Box also offers consulting so that customers can specify the right infrastructure configuration, in terms of hardware – for example, GPU spec – and software, such as AI components.

Nutanix will aim the initial launch squarely at customer on-premise use cases, but including edge workloads, with expansion to the cloud coming later.

Essentially, Nutanix believes customers need help to specify an infrastructure for AI because it can involve a complex mix of software elements plus hardware add-ons, and that concerns are commonplace over privacy and governance in AI applications.

“It’s activity that consumes, creates and generates a lot of data,” said Nutanix senior vice-president for product management Thomas Cornely. “And discussion about what you can do on-premise often resolves around privacy and governance.”

Nutanix will offer what it calls a “full-stack AI-ready platform”, in which it expects customers to deploy hardware and software to train and retrain models and be able to expose results to application developers.

GPT-in-a-Box bundles will comprise Nutanix HCI, Nvidia GPU hardware or recommendations, the Nutanix AHV hypervisor, a Kubernetes container layer, AI foundation models, open-source AI frameworks that could include KubeFlow, Jupiter and PyTorch, and a curated set of large language models including Llama2, Falcom GPT and MosaicML, all of which will provide outputs exposed for application development.

Nutanix’s offering is the latest effort from storage array makers to target AI/ML use cases, and clearly aims to hook on the surge in interest in chat-format AI. All of the big storage makers have addressed the rise in prominence of unstructured data as a source of analytics processing, but not all have been so explicit in targeting product bundles. An exception is Vast Data, which wants to build its recently launched Vast Data Platform as a global brain-like network of AI learning nodes.

Meanwhile, Nutanix GPT-in-a-Box is not just a self-service deploy-and-run offer. “It’s a bundled offer and it can scale down and out,” said Cornely. “But there’s a consulting phase, on GPUs, for example, and the software elements needed to support customer requirements.”

It’s an offer primarily launched at greenfield deployments in core datacentre or edge locations. Existing Nutanix customers can, in theory, build AI-ready infrastructures but would still need to consult over, for example, GPU sizing. “They do need different components,” said Cornely.

“They could upgrade their own infrastructure, but many customers lack the time to get started,” he said. “And there are different components for different parts of the [machine learning] process. There’s quite a lot of consulting up-front, but Nutanix has people that are chairs and vice-chairs of organisations that are putting this stuff out so they can say, ‘This is what’s needed for this deployment’.”

According to Cornely, many customers lack policies for the data that’s going into models and where it goes after it comes out, so for the time being, this offer is aimed at deployments on-premise to simplify matters of privacy, copyright and governance.

“It’s clearly targeted at on-premise and edge, and allowing customers to be fully in control of what they’re paying for and what data is going into it,” he said. “The cloud element is limited to getting foundation models, registering for LLMs, etc.”

Nutanix touches many clouds.

Indeed, the company’s self-style tagline is the hybrid multi-cloud computing company.

If its public, private on-premises, edge-based, mobile-centric and/or hybrid in any given combination of the aforementioned virtualized computing resources, plus other… Nutanix is all about working with cloud.

Being as Environmentally, Social and Governance (ESG)-aware as most technology vendors, Nutanix has worked on a number ESG-related initiatives over the years.

Started in 2018, Nutanix annually provides $50K in scholarship funds to undergraduate and graduate students majoring in computer science, engineering or similar disciplines.

Nutanix’s .heart program supports mission-driven causes making a bigger impact on communities globally and it has three strategic pillars: Education, Climate Change and Diversity & Inclusion. 

Now, in 2023, we see the firm announce the Nutanix Carbon and Power Estimator, a new tool to help organisations understand how different factors can influence their environmental footprint by estimating annual power and emissions for various Nutanix solutions using Nutanix Validated Designs. 

Nutanix software and solutions can help organisations meet power and carbon goals by optimising IT infrastructure through reduced footprint, on-demand resource scaling and fast and easy workload movement between on-prem and cloud options.

According to the 5th Annual Enterprise Cloud Index, for 92% of IT decision makers sustainability is more important today than it was a year ago — a development driven by an increasing number of pending and imposed regulations globally that add to the heightened interest in this space. 

As sustainability comes into view for many enterprises, they seek strategies to reduce their environmental impact.

The industry globally is increasingly asserting that data traffic, generated by cloud services and streaming provided by Netflix, Google, Amazon, Meta and Microsoft, will make investment unsustainable without compensation.

“While multinational tech giants continue to get a free ride, Australia’s telecommunications network operators are collectively investing billions of dollars every year to upgrade and maintain the backbone of our digital society,” Mr Rickards said. “Tech giants and streaming companies continue to profit from every connection we provide, without the burdens of infrastructure ownership or regulatory responsibilities.”

‘Fair share’ resolution

A spokesman for Communications Minister Michelle Rowland said the government was “aware of concerns” raised by the companies “about the costs of network enhancements needed to meet growing data demand, and their suggestions that digital platforms contribute to telecommunications infrastructure costs”.

The government had been “monitoring developments in the EU, and is analysing the European arrangements in detail, as well as approaches being considered in other jurisdictions,” he said.

In Europe, a “fair share” resolution – sometimes referred to as a “telco tax” – was included in a competition policy proposal voted through by the European Parliament in June. It requires tech and streaming companies to help telecommunications operators with their expenses.

An NBN spokesman said 43 per cent of all traffic on its networks was driven by online streaming services, whereas Optus said up to 80 per cent of demand across networks came from big digital content providers like streaming services, gaming operators and social media platforms.

Mobile data traffic demand is growing at about 37 per cent a year, according to data provided by Optus. In Europe, research has predicted a $28 billion investment gap in the UK for advanced 5G coverage by 2030.

Streamers disagree

Last Thursday, Telstra chief executive Vicki Brady demonstrated the perceived value of owning the infrastructure that runs the digital economy, with a decision not to sell its InfraCo arm, which houses assets such as fibre optic cable, data centres and subsea cables, and is valued about $15 billion.

Ms Brady suggested Telstra was not actively pursuing the government to intervene and force streaming platforms to pay for some of the costs of the infrastructure. But the company is looking at more commercially negotiated arrangements with larger technology firms.

“We are watching closely, and I speak to my peers in other parts of the world, and particularly in Europe, [but] I think it is a very different conversation,” Ms Brady said.

Any moves to legislate payments to the telco sector would draw the government into a similar political argument endured when the Coalition attempted to force Google and Facebook to negotiate commercial arrangements with news media, under a bargaining code.

A Netflix spokesman declined to comment directly on the demands of the Australian telecommunications companies, but noted comments made by the company’s co-chief executive, Greg Peters, at a conference earlier this year.

At the time, Mr Peters said those companies were already paid for their network investment through the phone bills of their consumers. He said Netflix also helped the sector by providing infrastructure to store its content locally rather than streaming it from overseas, and that its investments in encoding technology had reduced file sizes and optimised bandwidth use.

“Broadband customers, who drive this increased usage, already pay for the development of the network through their subscription fees. Requiring entertainment companies – both streamers and broadcasters – to pay more on top would mean ISPs effectively charging twice for the same infrastructure,” Mr Peters said.

Nutanix announced the Nutanix Carbon and Power Estimator, a new tool to help organizations understand how different factors can influence their environmental footprint by estimating annual power and emissions for various Nutanix solutions using Nutanix Validated Designs. Nutanix software and solutions can help organizations meet power and carbon goals by optimizing IT infrastructure through reduced footprint, on-demand resource scaling, and fast and easy workload movement between on-prem and cloud options.

According to the 5th Annual Enterprise Cloud Index, for 92% of IT decision makers sustainability is more important today than it was a year ago — a development driven by an increasing number of pending and imposed regulations globally that add to the heightened interest in this space. As sustainability comes into view for many enterprises, they seek strategies to reduce their environmental impact. One of the first facets of the business that leaders evaluate when looking to minimize environmental impact is IT, where changes in equipment or practices have the potential to make significant impacts when it comes to energy consumption and emissions.

The Nutanix Carbon and Power Estimator provides users with a report that helps illustrate how infrastructure choices can impact an environmental footprint with regard to power and emissions, with insights for developing more sustainable IT strategies. Based on user inputs regarding workloads, the efficiency of the data center, and location, an organization can conceptualize how IT choices can help them meet their sustainability goals.

“Understanding what drives carbon and power consumption is an important first step for many enterprises looking to advance on their sustainability journey,” said Faiz Shakir, Vice President & Managing Director, Sales, Nutanix India and SAARC at Nutanix. “The Nutanix Carbon and Power Estimator can help enterprises take initiative by educating organizations on factors that can influence their environmental impact.”

The Nutanix Carbon and Power Estimator enables organizations to:

• Estimate the effects of different factors on power and emissions for Nutanix solutions. As an example, with the Nutanix Carbon and Power Estimator, a user could see that if an organization deploys Nutanix Cloud Infrastructure for a general virtualization use case with 300 virtual machines (VMs) in a U.K. data center with a Power Usage Effectiveness (PUE) of 2.0, it would generate an estimated 68 metric tons of carbon dioxide (MTCO2) annually. If, on the other hand, the organization was able to find a way to bring the data center’s PUE down to 1.5, this change would reduce the emissions estimate by 17 MTCO₂ to 51 MTCO₂.
• Account for geography, which can also play a major factor in sustainability. The Nutanix Carbon and Power Estimator demonstrates the impact of moving workloads to geographies that leverage low carbon sources for energy generation compared to fossil fuels, which have a higher carbon intensity. For example, if the same general virtualization use case described above, with the reduced PUE of 1.5, were moved to a data center in Sweden, then the estimated carbon emissions would drop from 51 MTCO₂ to just two MTCO₂. This is because Sweden leverages a relatively high share of low carbon energy sources to power its grids. The Nutanix Carbon and Power Estimator makes clear that migrating workloads can be a viable part of an organization’s sustainability strategy. 
• Compare power consumption of Nutanix’s hyper-converged infrastructure (HCI) and 3-Tier (SAN-based) infrastructure. After using the Estimator, users can get a report that highlights how eliminating proprietary SAN components can help reduce power consumption. Based on a third-party reviewed methodology, Nutanix HCI demonstrated significant power savings compared to 3-Tier solution with the ability to run a similar workload.

Because every customer configuration is unique, the Nutanix Carbon and Power Estimator provides typical estimates that are generalized to help customers develop sustainability strategies rather than to provide exact usage figures.