What Are Neural Networks and How Data Centers Enable Them

The proliferation of AI applications gives rise to questions about neural networks and the data centers that enable them.

Even when compared to past technology innovations and the resulting leaps they enabled, AI and ML are quickly disrupting and transforming so many business processes and disciplines. One of the most revolutionary innovations in AI today is the concept of neural networks.

Yet, like so many other quickly evolving technologies, neural networks can often be misunderstood. This is especially true when it comes to what they are and the benefits they can provide. To help, we’ll offer a closer look at neural networks and describe why data centers are uniquely positioned to power them – now and into the future.

What is a Neural Network?

Simply put, a neural network is a series of algorithms inspired by the structure of the human brain. Neural networks identify underlying relationships in data by mimicking certain brain functions. In the same way that we learn from past experiences, neural networks recognize patterns in data, adapt to training and new inputs, and continue to improve over time.

Traditional algorithms follow a deterministic approach – which means they will render the same output for the same input. Unlike traditional algorithms, neural networks work probabilistically. In this case, they integrate randomness, ambiguity, and imprecision into decision-making reasoning that combines probability theory with logic theory to manage uncertainty.

Neural networks can also handle increasingly complex patterns. This is further proof that their sophisticated learning capabilities are superior to other AI counterparts.

The Role Data Centers Play

Data centers can play a vital role in implementing and supporting neural networks with the following characteristics and capabilities:

• Data storage and management: Neural networks require extremely high volumes of diversified, high-quality data. Data centers excel at storing and systematically managing colossal amounts of data, making them a perfect match.
• Compute power: Neural networks also need extensive computing resources for their extremely sophisticated mathematical operations and continuous iterations. Data centers can provide top-tier servers, high speed processes, significant memory capacities, and other capabilities to provide the computing power neural networks need.
• Parallel processing: Graphic processing units (GPUs) in data center servers make parallel processing possible and significantly streamlines neural networks’ training times and processes.
• Data security: Above all else, data must be secure at all times. Data centers provide security and compliance with regulatory requirements, to make sure data is not compromised during any interaction with neural networks.
• Scalability: As any AI or ML models expand, they need additional infrastructure resources. Data centers can offer more capacity and/or cloud computing resources to help any company scale neural networks – at will and on demand.
• High-speed networking: Data centers excel at providing superior networking capabilities. This alone can be a major edge in inter-server training model coordination and data sharing across different locations or systems.
• Proven uptime and reliability: Considering that neural networks need long, uninterrupted computing cycles to train and use neural, they need the proven reliability and consistent uptime hallmarks of the entire data center industry.

When specifically designed for neural networks, data center environments can provide scale and sophistication that exceed conventional on-premises IT environments. Additionally, other variables – high bandwidth networking, GPU-inclusive servers, specialized infrastructure, edge computing, and effective power and cooling options – are ideal in supporting neural networks in the future.

Data Centers: Supporting the Evolution of Neural Networks

Neural networks represent a fundamental shift away from traditional computing and have the potential to create a whole new paradigm of problem-solving. Bridging this gap and enabling such a transformative technology now requires the power, capacity, and versatility of modern data centers.
As AI and ML continue to evolve, so too will the role of data centers in enabling and then sustaining this evolution. It’s an exciting development, and we’re proud of the role our data centers can provide as we all venture further into the age of AI.

Additional Recommended Resources

Navigating the Future: DataBank’s Innovative Approach to HPC Data Center Demands
The Future of Monetizing AI Experiences and the Integral Role of Data Centers
Discover the DataBank Difference