Laptop cloud computing

How Cloud Computing is Powering the AI Revolution

Jim Koenig
,
Head of Data & Cloud Engineering
,
Sep 2, 2024

Cloud-Based AI: How This Tried-and-True Tech Supports the AI Revolution

The public cloud is the most popular location for AI deployment in enterprises, with 45% of those in pilot phases and 48% of those in production choosing this location. Other popular options include enterprise data centers, network devices, and network operator infrastructures, but none reach the use percentages of the cloud.

Why is the relationship between AI and cloud computing so strong? It's a symbiotic integration, with both technologies providing support to each other. Discover how cloud computing drives AI growth below.

Four Ways the Cloud Supports AI Growth

Artificial intelligence offers numerous benefits for organizations and individual users, but it doesn't come without its own demands. This technology requires a tremendous amount of data and other technical resources, and the tried-and-true nature of cloud computing is able to help provide that access.

1. Creating Access to Data

AI of any type requires data, which is used to train AI models and inform autonomous decision-making. During AI model training, systems are fed large datasets. The algorithms within these systems work to identify patterns, correlations, and features in the data, and those analytics help it make predictions and decisions.

Analytics process of using data to make predictions

How much data you need to train an AI model depends on what you are using it for. If you want an AI chatbot capable of answering a handful of simple customer inquiries, you would require less data than you might need for a generative AI system capable of handling problem-solving or writing product descriptions.

Cloud-based AI and systems that have access to cloud-based data are able to ingest copious amounts of data stored in those locations. Without the cloud, many of the most innovative AI developments would not be possible because there simply wouldn't be access to enough data.

2. Supporting the Sharing of Resources and Open Code

The cloud also supports fast and innovative AI development through the sharing of resources and open code. Cloud computing provides sandboxes, forums, and other developer resources that underscore a culture of technological partnerships. These platforms have made it possible for developers and tech professionals from across the globe to collaborate with each other and build upon each other's work, and this has driven much of the growth in AI.

Even AI deployment is more seamless and faster because of cloud resources. Consider ChatGPT. As of mid-2024, this generative cloud-based AI platform had around 100 million users globally. That's up from 1 million users the first week it launched, which was in November 2022. That's incredible growth that is made possible in part by the cloud.

3. Providing a Seemingly Infinite Infrastructure

In 2015, around 30% of corporate data was stored in the cloud. By 2025, estimates are that 50% of all the data in the world will be stored in the cloud, reflecting 100 zettabytes of information. That's an enormous amount of data — you could store 100 trillion books or 21.28 trillion DVD movies with that much data storage space.

Cloud computing market size forecast

But the cloud will continue to support growing AI infrastructure because it is a seemingly infinite resource. As AI systems begin to create a circular loop of data creation — with AI models requiring huge amounts of data to do work that generates more data — cloud storage resources become even more critical for organizations of all types.

4. Driving Cost-Effectiveness

For organizations working on scalable AI models and tools, cloud computing offers potential benefits when it comes to technology costs. Some reasons the cloud tends to be less expensive than on-premises solutions include:

  • Fewer or no hardware costs. Organizations don't have to invest in expensive servers and the resources required to maintain that hardware. This substantially reduces the cost of storing each unit of data, which also makes it less expensive to scale up — an endeavor often required for those implementing AI resources.
  • Decreased expenses related to updates. Cloud solutions can be updated with automated rollouts, reducing the cost of ensuring all iterations of a software, AI model or machine receive updates in a timely manner.
  • Cost savings around downtime issues. Cloud computing makes it easy to create redundancies that reduce downtime, ensuring AI processes have access to what they need to operate efficiently and correctly almost all the time.

How AI Supports Cloud Computing Efforts

The symbiotic relationship between cloud computing and AI means that the benefits don't travel a one-way street. AI also has a lot to offer the cloud, including:

  • More efficient analytics. AI can process astounding amounts of data quickly, making it possible to draw insights and create reports in real time. This helps cloud computing developers and vendors manage the performance of their solutions and has impacts on businesses and individuals. For example, you can thank AI for the fact that you can search for items on sites like Amazon and get links to exactly what you want in seconds.
  • Custom generative AI solutions. Generative AI models are supporting content creation, problem-solving, time management and many other tasks today, revolutionizing the impact that cloud-computing solutions have on businesses and individuals.
  • Automated network and cloud security. With so much data on the line, security is certainly a critical consideration for organizations using both cloud computing and AI solutions. Luckily, AI technology is changing the game for network and data security by supporting automations in an increasingly complex space.

AI and Cloud Computing: An Integral Link for Modern Technology

You can probably consider the relationship between AI and cloud computing an "until death do them part" type connection. In short, it's not going anywhere. Long term, this relationship is likely to become even more complex as innovations in technology draw on the resources that both niches have to offer. Chances are, you're already using both cloud and AI resources in your everyday life or work, so understanding how they relate to each other can be helpful.

Learn more about Further’s Data, Cloud, and AI solutions. Contact us to take your company further.

Jim Koenig
,
Head of Data & Cloud Engineering

Jim is the head of Data & Cloud Engineering at Further with 15 years of experience in industry. He holds multiple certifications from Google Cloud, AWS, Tableau, and Domo, and has extensive expertise with Salesforce Analytics. As the department lead, he oversees a large, multi-disciplinary team that builds business intelligence and cloud warehousing solutions for companies across various use cases, such as customer insights, marketing optimization, and operational efficiency. He fostered partnerships with industry-leading technology vendors and drives go-to-market strategies that deliver value to clients and stakeholders. Jim is passionate about data strategy, cloud systems integration, business intelligence, and strives to create innovative and scalable solutions that empower data-driven decision making.

,

Read More Insights From Our Team

View All

Take your company further. Unlock the power of data-driven decisions.

Go Further Today