It’s without a doubt that emerging technologies like artificial intelligence (AI) (opens in new tab) and machine learning will critically underpin future productivity and services across a range of sectors, from retail to manufacturing and public sector services. More businesses are looking for ways to implement the newest innovations, driving massive growth in the global enterprise AI market, which is now anticipated to reach US$9880.4 million by 2023.
To accelerate the value of AI and machine learning (opens in new tab) initiatives, a growing number of organisations are beginning to consult public cloud platforms for support. But when looking into public cloud to support the implementation of new technologies, a number of questions arise. Why is public cloud more fitting for AI and machine learning initiatives than private cloud? And how exactly can the organisation smoothly migrate operations without causing too much disruption?
Nick Henry, General Manager, Managed Public Cloud at Rackspace.
Where flexibility meets control
In comparison to private cloud and on-premise setups, public cloud (opens in new tab) is known for being flexible. With this flexibility comes an almost unlimited degree of adaptability where platforms can scale on demand. This is an important feature that supports innovative new technologies like AI, which are expected to scale at the same rate of business growth.
Public cloud also offers an increased level of security and controlled access. With AI and machine learning systems amassing a monumental amount of data – which may be sensitive – the public cloud offers a level of security better suited to these initiatives. This is largely because cloud service providers (opens in new tab) can assist with the 24/7 management and protection of datasets needed to support AI and machine learning technologies.
Lay the right foundations
Google Cloud (opens in new tab) offers unparalleled support for businesses looking to implement AI and machine learning initiatives. It is ahead of the game with its advanced set of tools that are dedicated to the support of data analytics, machine learning and artificial intelligence.
Supporting the live migration of virtual machines is a vital capability for businesses that may have already begun deploying AI. Google Cloud has this capability, ensuring internal systems run smoothly as data is shifted from a business’ existing infrastructure to the cloud. On top of this, where some public cloud platforms need to be set up before AI and machine learning systems are deployed, Google Cloud supports the shift of data from a private cloud or on-premise system at any point in the implementation timeline.
With developments in artificial intelligence growing at an exponential rate, now is the time for organisations to lay the appropriate groundwork in the form of public cloud. With the correct set-up, public clouds such as Google Cloud can help drive a new level of decision making in the form of business intelligence (opens in new tab) and advanced data analysis.
For example, it can support vast datasets for big data (opens in new tab), and from this, AI systems are able to access historical data to draw comparisons, identify patterns and then make appropriate choices. This in turn facilitates more efficient processes, enabling better and faster customer experience.
But the benefits of public cloud for organisations do not end here. As the most cost-efficient option for businesses looking for support for their AI and machine learning technologies, the public cloud is the most efficient option. Many argue that the public cloud model is the main appeal for businesses, as its set-up enables organisations to purchase only the amount of cloud storage (opens in new tab) needed for AI systems.
Freeing up the additional costs once ploughed into physical datacenters (opens in new tab) and traditional infrastructure, businesses are able to refocus their investments into further AI and machine learning developments. Most importantly, these cost savings can be immediately passed onto the customer.
Innovation in practice
Swedish mobile gaming company LeoVegas recently deployed Google Cloud to support its significant investment in machine learning and AI. In a complex and competitive industry, the company’s strategy is to tap into the popularity of smartphones and offer a superior customer experience. As part of this, it built a complex system to deliver real-time updates to customers, which required solid infrastructure that could scale as it grew.
Yet with most of its operations based out of Europe due to licensing restrictions, LeoVegas needed global scalability to ensure that its investments in AI and machine learning were also experienced by customers outside of the region. At the time, there were only a select number of cloud providers working in LeoVegas’ markets, and the business realised that it needed a partner which could not only support its global ambition, but also provide the flexible support needed for advancements and investments in new technologies at the same rate.
For LeoVegas, the rate at which Google Cloud ships new functionality matches the level of support needed as it grew its investment in machine learning and AI technologies. These new innovations demand huge amounts of resources, particularly at a level that would not be sustainable in an on-premise or private cloud environment. Google Cloud’s offering meant that its public cloud technology could keep pace with LeoVegas’ own innovation.
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Partnering for success
The scale of designing, planning and implementing public cloud to support AI and machine learning initiatives can be an overwhelming process that is by no means a case of lift and shift. To truly maximise the benefits of public cloud for emerging technology ambitions, partnering with a technology service provider is essential.
A partnership will increase both the value and range of offerings available to support new technology implementations. Driving value is not only crucial for businesses, but for their customers who are ultimately always seeking the best experience.
For companies like LeoVegas, emerging technologies such as AI and machine learning drive more seamless operations, increased efficiency and ultimately, a better experience for customers. The key to realising the promise of these technologies is leveraging the scalability, security and agility of public cloud, coupled with the expertise of a technology partner.
Nick Henry, General Manager, Managed Public Cloud at Rackspace (opens in new tab).
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