Vultr and Domino Data Lab to enable firms gain edge in era of generative AI

Vultr, one of the world’s largest privately-held cloud computing company, and Domino Data Lab, provider of the revolutionary Enterprise MLOps platform trusted by over 20% of the Fortune 100, announced the integration of Domino Nexus with Vultr’s Kubernetes Engine.

What is the market offering of the joint solution?

This new integration between these two companies helps businesses achieve competitive advantage in the era of generative AI by accelerating innovation while balancing compute cost, performance, and availability with seamless bursting of cutting-edge AI workloads to GPU-accelerated compute clusters across cloud and on-premises environments.

This announcement delivers on Vultr and Domino’s recently announced partnership, which gives enterprise data science teams unparalleled access to state-of-the-art NVIDIA-powered cloud infrastructure on Vultr, including NVIDIA A100 and H100 Tensor Core GPUs to train, deploy, and manage their own deep learning models with speed, flexibility and affordability. Vultr and Domino are both members of the NVIDIA Partner Network program.

The  offering is underpinned by Vultr Kubernetes Engine (VKE) and Domino’s hybrid- and multi-cloud architecture, Nexus, to break down data science silos and open up flexible compute options, with cost, performance, and scale in mind. Built around a commitment to openness, flexibility and open standards, it democratizes AI innovation for teams.

  • Unified Data Science: Domino Nexus’ unified MLOps platform orchestrates governed, self-service access to common data science tooling and infrastructure across all environments, including Vultr – alleviating infrastructure capacity and data sovereignty challenges during model training.
  • Flexible and Interoperable: Domino’s Kubernetes-native platform runs seamlessly on VKE, with the CNCF-certified and MACH-compliant VKE providing automated container orchestration with support for geographically redundant clusters, so users can operate with confidence to easily scale data science workloads across Vultr’s worldwide locations without fear of vendor lock-in or outages.
  • Cost Effective and Agile: Vultr offers a variety of full and fractional NVIDIA A100 and NVIDIA H100 Tensor Core GPU configurations, enabling enterprises with the agility to optimize infrastructure based on AI workload demands at a significantly lower cost. Data transfer costs are minimized with Vultr’s global bandwidth pricing plan.

What does the integration mean for the tech space?

“Rapid access to cost-effective compute is critical to fuel today’s record demand to train and deploy large language models and generative AI. By unifying cutting-edge hardware and software components in one solution, Domino’s integration with Vultr offers companies pursuing rapid AI innovation a single way to handle workloads without delays or cost overages,” said Andy Thurai, Vice President and Principal Analyst, Constellation Research.

Nick Elprin, CEO and co-founder at Domino Data Lab
Nick Elprin, Chief Executive Officer and co-founder at Domino Data Lab

Commenting on the partnership, Nick Elprin, CEO and co-founder at Domino Data Lab, said, “Customers seeking AI-driven competitive advantage must grapple with staggering GPU demand and cost pressures. Our integration with Vultr provides enterprises on-demand compute to keep developing cutting-edge artificial intelligence without budget overspend.“

“Vultr is committed to democratizing access to high performance cloud computing, so that our customers can focus on driving innovation without worrying about cost, data sovereignty, and security. With Domino Data Lab, we have created a best-in-class solution that will empower machine learning and data science practitioners to solve the world’s most pressing problems across a wide range of industries,” commented J.J. Kardwell, CEO of Vultr.

This joint MLOps and Compute solution’s data plane functionality is available today to Domino Nexus clients, allowing them to add Vultr cloud compute environments to their Domino deployments. Full Domino platform deployments on Vultr will be available by Summer 2023.

Vultr and Domino Data Lab will demonstrate this joint solution at Rev 4, the only conference geared towards data science and analytics leaders, May 31 through June 2 in New York City.

What is the wider industry context of this partnership?

Generative AI is a rapidly developing field with the potential to revolutionize many industries. By automating the creation of content, generative AI can help businesses to improve their efficiency, productivity, and creativity.

One way that businesses can achieve competitive advantage through generative AI is by using it to improve their customer experience. For example, generative AI can be used to create personalized marketing campaigns, generate customer support tickets, and even write customer reviews. This can help businesses to better understand their customers and provide them with a more tailored experience.

Another way that businesses can use generative AI to achieve competitive advantage is by using it to automate their workflows. For example, generative AI can be used to generate reports, create presentations, and even write code. This can help businesses to save time and money, and free up their employees to focus on more strategic tasks.

Finally, businesses can use generative AI to create new products and services. For example, generative AI can be used to design new products, create new marketing campaigns, and even write new songs. This can help businesses to stay ahead of the competition and generate new revenue streams.

While generative AI has the potential to be a powerful tool for businesses, it is important to note that it is still a developing technology. As such, there are some challenges that businesses need to be aware of before they can fully embrace generative AI.

One challenge is that generative AI can be expensive to implement. This is because it requires access to powerful computing resources and specialized software. Additionally, businesses need to invest in training data and algorithms in order to get the most out of generative AI.

Another challenge is that generative AI can be difficult to control. This is because it is a black box technology, meaning that it is difficult to understand how it works. This can make it difficult to ensure that generative AI is producing accurate and unbiased results.

Finally, generative AI can be used to create harmful content. This is because it can be used to generate fake news, create deepfakes, and even generate malware. Businesses need to be aware of these risks and take steps to mitigate them before they use generative AI.

Despite these challenges, generative AI has the potential to be a powerful tool for businesses. By carefully considering the challenges and opportunities of generative AI, businesses can achieve competitive advantage in the era of generative AI.

Here are some additional tips for businesses that are looking to achieve competitive advantage through generative AI:

  • Start small. Don’t try to implement generative AI across your entire business all at once. Start with a small pilot project and see how it goes.
  • Partner with a trusted provider. There are a number of companies that offer generative AI solutions. Partner with a provider that has a proven track record and that you can trust.
  • Invest in training data. The quality of your training data will have a big impact on the quality of the results that you get from generative AI. Invest in high-quality training data to get the best results.
  • Monitor your results. It’s important to monitor the results that you get from generative AI. This will help you to identify any potential problems and to make adjustments as needed.

By following these tips, businesses can achieve competitive advantage through generative AI.

Gerald Ainomugisha is a business news reporter and freelance B2B marketer with over 10 years of experience in writing high-converting copy and content for businesses of all kinds, especially SaaS providers in the niches of HR, IT, fintech, eCommerce and web3. Since joining Upwork in 2012 (back when it was still eLance), Gerald A. has delivered great results for hundreds of clients, maintaining a 98% Job Success rate as well as 5+ years of Top Rated Plus rating (and Premium Writers Talent Cloud membership). Book a meeting with Gerald A. today to get the powerful SEO content you need!

Gerald Ainomugisha, B2B marketing expert