Companies that need AI infrastructure have two options. The first one is to create their own IT environment, and the second one is to use ready-made cloud technologies. Let’s consider both options.
AI infrastructure: A list of essentials
Infrastructure is all those solutions and technologies that create the conditions for AI to work. In this case, it means data storage, processing, and protection.
- Data storage. When choosing the amount of storage, you should consider not only the current state of the project but also its growth prospects. Experts advise buying drives that are at least twice as large as the data you plan to store. This often means equipment that can support petabytes and exabytes of data.
- Computing capabilities. This is the responsibility of the central processing unit or graphics processor. The CPU is good for data input, storage, and output, but for more complex processes, such as deep learning, you should also use the GPU.
- Data scrubbing and management. You’ll need cleaning tools to get rid of incorrect, duplicate, or unnecessary data.
- Network. It should have high bandwidth and low latency to be able to transfer information quickly within the organization.
- Security. The end-to-end security solution shows itself in the best way. Implement firewalls, identity, and access management, encrypt the data, and limit the use of VPN.
- AI of Things. AI can involve receiving data from a variety of sensors, devices, etc.
There are things that are not related to infrastructure but are essential for successful AI deployment. These include data management policies and qualified staff, such as analysts, cybersecurity specialists, etc.
AI infrastructure from G-Core Labs
G-Core Labs’ services allow companies to eliminate the need to build an AI infrastructure from scratch. G-Core Labs offers an artificial intelligence cloud that allows you to add the most advanced machine intelligence compute on demand. You get AI full-lifecycle tools for ML and AI solutions; data receiving and processing; development, exploration, and visualization tools; several programming languages and data platforms.
G-Core Labs solutions will help train and compare models or custom code training, and the data will be stored in one central model repository. The service is suitable for various business areas, from manufacturing to research.
