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Today, any business with a website is familiar with server technologies. You may have spent days searching for the most suitable operating systems for standard services like data storage and hosting. But do you know how artificial intelligence, which has been processed for everyday use for a small fee, provides benefits in server technologies? Let’s talk a little about AI Server; first, what is AI Server?
Imagine a cloud server. Whether it has the capacity to store your high-volume data, performs data analytics, is scalable, or has recovery plans... No matter how advanced the capabilities are that you can envision for developing and hosting artificial intelligence applications, you actually need more than that for an AI server. Artificial intelligence technologies are an area that continuously needs to be fed with more data, with requirements for deep learning and data analytics that never cease.
An AI server is a computing system optimized to meet the high demands of artificial intelligence technologies. These servers are specifically designed to handle compute-intensive workloads, such as machine learning (ML), deep learning (DL), and big data analytics. With high processing power, advanced storage capacity, and optimized data transfer speeds, they form the foundation of artificial intelligence projects.
AI servers process large volumes of data very quickly to train artificial intelligence algorithms. With these servers, complex calculations and big data analytics operations are performed at the fastest speed.
High-performance processors and GPUs are essential for running machine learning and deep learning projects. AI servers are created with the aim of fulfilling these needs.
AI tools that require real-time data processing also benefit from AI servers. For instance, decision-making processes in autonomous vehicles or real-time analyses in the financial sector are made possible thanks to these servers. Any instantaneous change in these sectors can have significant consequences. AI operations must also be handled with the same precision.
If you are considering renting or buying an artificial intelligence server, you should be sure to understand the components of these servers.
If you want to learn more about the difference between CPU and GPU, you can read our comparison article.
Artificial intelligence models process large amounts of temporary data quickly. Therefore, high-capacity and fast RAM is preferred.
Especially, software components can vary based on projects and teams. Generally, AI servers can be said to be compatible with popular artificial intelligence frameworks like TensorFlow and PyTorch.
Artificial intelligence (AI) servers are divided into various types based on their hardware and architectural features.
1. Cloud-Based AI Servers AI servers offered by cloud service providers stand out due to their scalability and flexibility. You have the option to increase or decrease the resources you use based on your needs, meaning you pay only for what you use. This way, you can receive cost-effective and easily accessible services without the need to purchase a physical server.
Additionally, for businesses that do not have a large IT team and do not want to manage maintenance and operational processes by purchasing a physical server, cloud-based AI servers are ideal.
2. GPU Servers Graphics Processing Units (GPUs) play a critical role in AI and deep learning applications due to their parallel processing capabilities, as mentioned. A good GPU selection provides an advantage in processing large datasets and complex AI models. These servers are ideal for AI projects that require intensive computation.
They are classified into single GPU and multiple GPU servers. A single GPU server is suitable for some entry-level artificial intelligence operations, while for more complex tasks, one should switch to multiple GPUs. We recommend consulting with an expert to make that decision.
3. CPU-Focused Servers Some AI models require multi-core CPUs with high clock speeds. Especially data preprocessing and machine learning algorithms rely on CPU performance.
4. Hybrid Servers Hybrid servers combine both CPU and GPU resources, providing flexibility for different AI workloads. These servers are designed to meet the needs of various AI applications.
When choosing a server for AI projects, the following factors should be taken into account:
Processor Performance: CPUs with high core counts and clock speeds should be preferred. Memory Capacity: At least 128 GB of RAM is recommended for working with large datasets. Storage Solutions: NVMe SSDs should be used for fast data access. Network Connection: Network connections that offer high bandwidth and low latency should be preferred. Cooling: Effective cooling systems are necessary to manage the heat generated by high-performance components. Scalability: It is important for the server to be easily upgradable for future needs.
These factors are critical to the success of your AI projects. The right AI-powered tools and server selection ensure that your projects are executed efficiently and effectively.
As servers that run artificial intelligence applications are vital for AI technologies, it is equally important to receive AI support in server technologies today. AI servers, with their high performance and capacities, may seem like a magical world to explore, but of course, the needs of all businesses are not the same.
In the past five years, alongside the ever-growing artificial intelligence giants that have managed to enter all of our lives, even small and medium-sized businesses can turn artificial intelligence into a benefit. In fact, we are in an age where falling behind this technology could be a fatal mistake for businesses. It is crucial to adopt an IT infrastructure that can scale according to needs, integrate existing artificial intelligence technologies into your work, and process information in the most intelligent way.
1. High Performance These servers offer significantly higher performance than other servers with their parallel processing capabilities and optimized hardware. With a high-performance server, you can integrate systems that will automate repetitive tasks into your business.
2. Scalability Thanks to cloud services, you can freely increase or decrease resources according to your needs.
3. Cost Efficiency With AI server rental options, you can achieve high performance without making hardware investments.
Define Project Requirements
Compare Cloud and Physical Servers
Research Support and Service Services Consider the quality of technical support and service times offered by companies that provide server services.
PlusClouds offers cloud server services optimized for artificial intelligence projects. With high-performance server infrastructures and flexible rental models, it provides the following advantages:
1. High-Performance GPUs and CPUs
2. Flexible Rental Models
3. Cloud Services
4. Easy Access and Setup Thanks to our AI-powered tool, even if you have almost no knowledge of the subject, you can access the panel and instruct it with simple commands like, “Set up a server with xxx features and x capacity”. Our AI tool can handle all your operations for you.
With this panel at your fingertips and our support team providing services from Turkey, you can quickly and easily take care of all your tasks.
If you are unsure of how to benefit from artificial intelligence in your business, want to learn about the process, or are looking to bring your artificial intelligence project to life, you can reach out to us.. Artificial intelligence and cloud services are just a click away from you.
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