The best and possibly, a vague way to understand AI is that it mimics human behaviour and such mimicry is vastly used by organizations around the world to reduce the repetition of tasks. AI is here to stay and has already become mainstream. If you thought AI is about futuristic robots trying to destroy the human race, you might be partially correct. Before processing that thought of yours, we need to understand about three primary types of AI:

Artificial Narrow Intelligence(ANI):

If you know about Google’s RankBrain and Apple’s Siri, you are already accustomed to ANI. Narrow Intelligence means that the intelligence is restricted to narrow parameters and contexts. In other words, Google’s ANI cannot do much beyond ranking pages. Likewise, Siri also operates under a predefined set of functions. Sometimes, we hear people complaining about how even Siri doesn’t understand them. Siri is not to blame, her AI is actually narrow.

Artificial General Intelligence(AGI):

A much better version than ANI, General AI is also known as Human-level AI. The idea of machines replicating the powerful human brain has always been elusive but experts claim that it cannot be ruled out as impractical. Few experts also claim that the intellectual capacity of AGI can be boosted far beyond human capacities by its ability to access and process huge amounts of data at incredible speeds. Fujitsu-built K, one of the world’s fastest supercomputers, taking 40 minutes to simulate a single second of neural activity could be the first step towards AGI.

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Artificial Super Intelligence(ASI):

To consider a machine as ASI, the machine should operate beyond human intelligence in all aspects and not just mimic it. It would take decades to come up with a solid research on Artificial Super Intelligence Machines and hence super powerful robots which we mentioned in the first paragraph of this article, cannot conquer humans for at least a century.

How AI works:

Let’s assume that we assign a task to an AI machine. It will first analyze the input through a neural network. A neural network works like a human brain and comprises many nodes which recognize patterns; which are numerical, contained in vector into which we must translate the data. By inputting a large amount of data, a machine will learn something new every day thus providing us a brief idea about how AI works.


Image Source: Inverse Article

AI and Virtual Machine Backups:

Virtualization has changed so much in IT, and by doing so, it has increased the number of options made available to the backup industry. As companies continue to move from legacy IT towards a modern, software-defined datacenter environment with server virtualization, companies bear the responsibility to modernize their data protection strategies to include more modern backup and recovery approaches. We can assume that machine learning, artificial intelligence and predictive analytics will take over and make backup administrators faster and more productive at their jobs. Systems will become smart enough to know which versions of files and application recovery points to roll back after an attack. AI will leverage predictive learning algorithms and automatically perform proactive recoveries, eliminating outages even before an end user can detect them.

Also, it would be interesting to see how backup data, with an infusion of AI, will not just reside in one place but could also be used for organizational benefits.

The current scenario:

Many experts believe that automation could be a bridge to AI in the backup industry. Automation is the key to operational efficiency in today’s fast-paced world of IT. Virtualization environments today run many VMs with numerous business-critical applications. Protecting these workloads in an automated way will ensure business continuity. Implementing a data protection solution for virtual machine backups, having automated processes and utilizing them for protecting mission-critical applications is very important. Virtual Machine Backup automation features like Automatic Backup Scheduling, Application-aware backup, Retention policy, Automated backup verification and so on, are crucial for a comprehensive automation strategy.


Final Thoughts:

Till we wait for AI in Data Protection, I believe that Automation can keep away the human error aspect out of data protection and allow for a consistent and error-free backup environment. By leveraging an automatic backup solution like Vembu BDR Suite, organizations can successfully implement automation strategies to protect virtual machines.

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