Nick Henry, General Manager, Managed Public Cloud at Rackspace.
There is no doubt that emerging technologies such as artificial intelligence (AI) and machine learning will crucially support future productivity and services across a range of sectors, from retail to manufacturing to public sector services. More and more companies are looking for ways to implement the latest innovations, leading to massive growth in the global AI enterprise market, which is expected to reach $ 9880.4 million by 2023.
To increase the value of AI and machine learning initiatives, more and more companies are consulting public cloud platforms for support. However, looking at the public cloud to support the implementation of new technologies raises a number of questions. Why is the public cloud better suited for AI and machine learning initiatives than the private cloud? And how exactly can the organization migrate operations smoothly without causing too much disruption?
Where flexibility meets control
Compared to private cloud and on-premise setups, the public cloud is known for its flexibility. This flexibility offers almost unlimited customization options, so platforms can scale as needed. This is an important feature that supports innovative new technologies, such as AI, that are expected to scale at the same pace of business growth.
The public cloud also provides a higher level of security and controlled access. As AI and machine learning systems accumulate a massive amount of data that may be sensitive, the public cloud provides a level of security that is more appropriate for these initiatives. This is mainly because cloud service providers can help with the 24-hour management and protection of records required to support AI and machine learning technologies.
Put the right basics
Google Cloud provides unparalleled support to companies looking to implement AI and machine learning initiatives. It is ahead of the game with its advanced tools that focus on supporting data analysis, machine learning and artificial intelligence.
Support for live migration of virtual machines is an important feature for companies that may have already begun to deploy AI. Google Cloud has this feature to help ensure that internal systems run smoothly as data moves from the existing enterprise infrastructure to the cloud. In addition, Google Cloud supports relocating data from a private cloud or local system at any point in the implementation timeline when some public cloud platforms need to be set up before AI and machine learning systems are deployed.
As the development of artificial intelligence increases exponentially, it is now time for companies to create the appropriate foundation in the form of public clouds. With the right setup, public clouds like Google Cloud can boost a new level of decision-making in the form of business intelligence and advanced data analytics.
For example, it can support large datasets for big data, and from these AI systems can access historical data to make comparisons, identify patterns, and then make appropriate decisions. This facilitates more efficient processes and enables a better and faster customer experience.
However, the benefits of the public cloud for businesses do not end there. As the most cost-effective option for businesses seeking 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 attraction for businesses, as it allows organizations to buy only the amount of cloud storage needed for AI systems.
Enterprises can focus on additional AI and machine learning development by putting additional costs into physical data centers and traditional infrastructures. Most importantly, these cost savings can be passed on immediately to the customer.
Innovation in practice
The Swedish mobile games company LeoVegas has recently implemented Google Cloud to support its significant investments in machine learning and AI. In a complex and competitive industry, the company's strategy is to leverage the popularity of smartphones and deliver an outstanding customer experience. As part of this, the company built a complex system to provide real-time updates to customers. This required a solid infrastructure that would scale with growth.
Because LeoVegas is largely located outside of Europe due to licensing restrictions, global scalability was required to ensure that investment in AI and machine learning was also made by customers outside the region. At that time, there were only a select number of cloud vendors operating in LeoVegas' markets, and the company realized it needed a partner that not only supported its global ambitions, but also provided the flexible support that would be available For improvements and investments in new providers is required technologies at the same speed.
For LeoVegas, the rate at which Google Cloud provides new functionality is the level of support required as investment in machine learning and AI technologies has increased. These new innovations require a tremendous amount of resources, especially at levels that would not be sustainable in a local or private cloud environment. Offering Google Cloud enabled public cloud technology to keep pace with LeoVegas' own innovation.
Partner for success
The scale of designing, planning, and implementing a public cloud to support AI and machine learning initiatives can be an overwhelming process that is by no means about recovery and displacement. To really maximize the benefits of the public cloud for new technology goals, working with a technology service provider is critical.
A partnership will increase the value and breadth of available offerings to support new technology implementations. Creating value is not only critical to businesses, but also to their customers, who always seek the best experience.
For companies like LeoVegas, emerging technologies such as AI and machine learning are leading to smoother processes, greater efficiency and, ultimately, a better customer experience. The key to realizing the promise of these technologies is to leverage the scalability, security and agility of the public cloud, combined with the expertise of a technology partner.
Nick Henry, Managing Director, Managed Public Cloud Rackspace,
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