Articles

Deep learning is an intelligent machine's way of learning things.

It’s no longer the big beating the small, but the fast beating the slow.

Classical computing has come a long way, from solving simple mathematical problems to using additional resources to solve highly complex tasks. However, the limitations of classical computing prevent it from solving the much more complex challenges the world faces today, and that's where quantum computing steps in. 

The explosive growth of data and the demand for public cloud offerings have contributed to several new large data centers being planned or constructed across the globe. The onset of the COVID-19 pandemic has coerced numerous companies to look for options to ensure business continuity, leading to data centers growing faster than ever. 

If you use a smartphone, you probably have come across narrow AI.

Every transaction that we make creates data. From swiping your card while going grocery shopping, to closing a billion-dollar merger, each transaction creates several data points across the digital ecosystem. Although this is unstructured data, it's how we use these billions of data points to create and derive information that forms the underlying structure of data management and data science. Data value needs to be delivered to businesses as soon as possible, and converting this value into actionable insights is critical.

Day in and day out, HR managers are inundated with requests.

What is parallel processing? Parallel processing is defined as an architecture where processes are split into separate parts and each part is run simultaneously. By running the processes on multiple processor cores instead of a single one, the time taken to execute tasks is much lower. The main goal of parallel computing is to ensure that complex tasks are broken into simpler steps for easier processing driving better performance and problem-solving capabilities.

Putting all your eggs in one basket doesn’t always work out well. We’ve all done it, and when done in a business context (e.g., Cloudflare’s July outage that briefly tanked numerous web-based businesses), the consequences can be far-reaching and dire.

Not all clouds are created equal, at least not in terms of security.