Future of Scientific Research Lies in Hands of AI and Cloud Computing

by October 7, 2019 0 comments

AI and Cloud Computing

The hype created by AI is hard to ignore as in most of cases it proves to be right. Voluminous datasets and a great amount of computing are the apt blending for deep learning underpinned with algorithms that have mastered the innovations of today.

As it stands now, with access to such huge datasets, breakthroughs supporting image and speech recognition and machine translations benefit a big portion of the population.

Amidst this, not to forget the services of cloud which is also growing at a fast pace. People are submitting a considerable amount of data on virtual drives enabling ease at sharing and create a backup of information. The transfer of information onto virtual drives facilitates us with new opportunities in both office and personal space.

But is there any significance of ML and Cloud Computing together, specifically in scientific research? Do they have the capability to help researchers manage and operate the voluminous datasets generated by extremely sophisticated detectors and experiments?

Datasets that used to stream at megabits per second are now hundreds of times faster at scientific facilities. Sometimes they are even faster due to upgradation of detectors come online and new instruments are installed. Well, undoubtedly, this gives rise to a lot of data that needs to be analyzed and verified.

Subsequently, scientific discoveries are accelerating as a multidisciplinary endeavor which is clearly transforming the way scientists work together. The combination of AI and cloud computing can help researchers discover fast and get answers that they are looking for 1000 times faster than by depending upon in-house hardware.

The amalgamation has the potential to transform communication and collaboration between research teams. Although most of the scientists are quite protective about their experiments yet collaboration and having all the data store at the cloud makes it easier for them to unleash to act upon it through AI.

Another concern with data is the security across any networked system irrespective of where it is stored – on cloud or a physical drive. But due to the emergence of AI as support, cloud services are way too secure than other methods. The files are password protected and possibly stored at a minimum of three locations so that if any cascade failure happens, the data will still be secured.

However, AI and cloud computing are not new concepts but their implications have evolved with the advancing times and technologies. As most of the companies are adopting AI, they are also shunning down the in-house data storage and moving towards AI-fueled and well-encrypted cloud services.

The scientists can make discoveries faster using cloud storage paired with parallel processing, machine learning and AI itself.  In current times both the technologies are at rising and have turned out to be the most valued tools across organizations, henceforth it will be interesting to see what is next in the bucket to innovate the world.

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