The AI future demands a democratized cloud

The AI future demands a democratized cloud

Generative AI is completely transforming the way we build, use and even think about technology. Recent advancements have ignited a new era of innovation, one that McKinsey predicts could provide a $4.4 trillion jolt to the global economy.

The next great AI product could come from anyone, anywhere, and change everyone’s lives. Yet, a handful of Big Tech companies in the United States still control much of the world’s cloud computing infrastructure. These hyperscalers embody the ethos of Silicon Valley with their ambitious goals and aggressive strategies. They’re territorial and competitive and, while that can lead to exceptional service for some customers, it can jeopardize others.

These companies’ cloud supremacy is stifling innovation. By making developers increasingly dependent on their services, they command an unfair share of the market, shutting out smaller cloud startups that often provide more agile, affordable solutions.

If we want to truly unlock the transformative potential of AI, we need to promote a more democratic cloud: one where developers have the freedom to choose their vendors and compose the ideal cloud infrastructure for their goals. This will promote interoperability, streamline the application development lifecycle and ultimately lead to better-performing AI products and services.

Kevin Cochrane

Chief Marketing Officer at Vultr.

The traditional Hyperscalers

The Big Three – Microsoft Azure, AWS and Google Cloud – were once the Only Three. As recently as eight years ago, these providers were virtually the sole option for any organization working in the cloud.

The environment has since changed rapidly. People say “every company is a tech company” now, and research shows it’s true. It’s not only major enterprises and world governments that require substantial cloud support, but startups, mid-market players and even companies whose primary offering isn’t a technology product at all.

However, one organization’s “substantial” is another’s overload. What might be a useful feature to an international megacorporation might be a massive obstacle to a small AI developer. Product overload creates more inefficiencies than advantages, and those inefficiencies will eventually offload to the customer, as applications won’t be able to meet performance demands.

The Big Three are notorious for product overload; in their efforts to out-innovate their competition, they sidle their customers with complicated features that most of them will never need. That said, the solution is not to oust the Big Three in a cloud marketplace coup, but to create a more equitable cloud ecosystem overall – and that starts with letting businesses know they have options.

Hope in the independent market

The AI boom is accelerating the growth of independent cloud providers. Beyond supporting cloud engineers, developers need expanded solutions for their data science teams, whose work in training and maintaining the AI requires diverse computational resources. This need has precipitated a groundswell of demand for leaner, cheaper cloud providers.

Independent clouds allow smaller businesses to develop, test and deploy in accordance with their unique business needs. However, “independent” certainly doesn’t mean scrappy or new to the market. These providers are running on the latest products in data centers situated at strategic locations around the world, and their solutions are helping businesses to scale and meet demand.

Multi-cloud and hybrid cloud adoption has also ramped up, with developers seeking improved flexibility and scalability. In orchestrating operations across multiple clouds, companies can save money while composing a computational toolkit that best enables their growth.

This ballooning independent cohort is also challenging the longstanding US-centricity of the cloud market. Deployment on the edge requires localized support, and when developers can build close to home while deploying close to their customers, they’ll provide better software performance while simultaneously streamlining their development and testing operations. Independent clouds are highly suited to this sort of agility, and they’re popping up all over the world.

Democratizing the cloud for AI and beyond

Democratizing the cloud is crucial to the sustainability of AI development. AI workloads are highly resource-intensive, and at the current pace of innovation, future AI programs will require even more complex solutions to bear the processing load. ChatGPT is far from the final frontier, and as generative AI becomes smarter and more capable, developers will need more custom cloud options. When businesses first migrated to the cloud, many got locked into a single vendor, and they don’t plan on repeating this with AI. By improving the accessibility of composable, multi-cloud strategies, we can enable businesses of all sizes and scopes to scale.

Don’t get it wrong. The Big Three have their place in a democratized cloud marketplace – they offer valuable services, and they can provide the vast computational power that the world’s mega-enterprises require. But for the other 90%, we need a flourishing independent market to promote the innovation that will deliver an AI-powered future. In the age of AI, every organization in every region around the globe should have the power to build, test and deploy ML-driven, cloud-native applications.

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