Cloud and AI

The potential of Cloud Computing technology is immense, and it has already made an impact on various businesses by providing data storage, infrastructure and balancing workloads. Though Cloud Technology is one of very few cutting edge modern technologies and is making significant impact worldwide, we still need to sit and think how best can we leverage Cloud Computing capabilities.

The dream of gifting a machine with intelligence has been a long-chased dream but today it is a profound reality. A reality that has surpassed human being’s wildest imagination. Even movies and writings of eminent thinkers, poets have given instances where viewers are baffled to see what an intelligent machine who behaves as human brain could achieve. Noteworthy among them being Mery Shelly’s Frankenstein, Stanley Kubrick’s 2001: A Space Odyssey, Star Wars and many more. Still we are yet to create a machine which would possess supreme power like humans do but the mission has already started.

“The union of AI and Cloud will accelerate change and also be a source of innovation” - IBM

Significant investments are being made on execution of AI in Cloud platforms. Technology-giants like Google, Amazon and Microsoft are now guiding the whole world towards embracing AI abilities on cloud. Post analysis of present day scenarios, we come up with two divisions:

     i.        Cloud Machine Learning (ML) Platforms: Cloud platforms like AWS ML, Azure ML and the Google Cloud ML use a specific technology that is powering the creation of Machine Learning models on Cloud. Separate, segregated AI hardwares and infrastructures endure huge cost which is now being mitigated with simulation mechanisms running on cloud which would give the same behavior.

ii.        AI Cloud Services: Businesses that support AI platforms like IBM Watson, Google Cloud Vision, Microsoft Cognitive Services or Natural Language Processing (NLP) can now make use of AI algorithms and techniques via already implemented managed API calls. Gone are those days of cost effective AI infrastructures.

Can AI power Cloud technology?

Cloud Technology market these days are majorly ruled by IT companies like Google , Amazon , etc. AI can give birth to next generation of Cloud Computing platforms. But as time progresses, AI implementation would need more robust programming algorithms and an enhanced computing infrastructure. A generation of widely enhanced and cognitive cloud platforms powered by AI is what’s next. We are now on the verge of entering an era of “CloudAI”

What is the result of AI – Cloud Computing merger?

The training, test and validation data sets to be leveraged on various algorithms to generate ML models should be maintained in Cloud environment. More the data, more accurate would be the model. For example, for models which identify cancerous cells in human body, thousands of biopsy reports may have been used to train the model. The data used as input can come as raw data, both structured and unstructured data. These are best stored and leveraged from Cloud infrastructures.

Various ML and DL algorithms or Neural Networks need advanced computation methods which would require power from CPU’s and GPU’s are now provided by incredibly fast VM’s with powerful GPU’s.

This chemistry of Cloud and AI will give user a vast networking interface which is capable of storing amount of data beyond imagination but with an advantage given by AI to learn and improve accuracy automatically as we proceed. IBM Watson is a brilliant example of an AI – Cloud merger.

AI Services for Cloud Computing:

Without creating beautiful handcrafted yet pain-stricken ML models, the service or the same can now be provided by Cloud driven AI systems. E.g: Speech and Text Analysis, Vision API’s, and Transition Learning models that are now accessible to developers who can pilot their own projects according to their customized needs.

Let’s analyze what Machine Learning service of GCP has to offer. The flexible and well-harnessed interface provided by GCP offers Data Scientists and Data Engineers an opportunity to write robust models with better accuracy and testing methodology. For example, the weather forecasting feature of Google AI is making almost accurate weather predictions during the period despite not having a Deep Learning implementation.

Impact in SMB (Small and Medium-Scale Business) and Enterprise industries:

Cloud Platform is an important factor for AI frameworks to thrive more. The data sets used by organizations would not be accessed elsewhere other than Cloud infrastructures. SO it’s only cloud that can provide the amazing scale of user experience required by providing with data concentrated services to limitless customers with optimized pricing.Now despite the fact that AI is progressing like rocket still SMB’s and many businesses are not being able to leverage the best of the services provided, reason being lack of infrastructure and people within the organizations who can program the same. That’s why despite this uncontrollable zeal of implementing AI within business, they are not able to get the outcome that they cherish for. Some startups have already established this deadly combination of AI and Cloud to flourish in business and their undertakings. 

Ultimatum:

Cloud computing leveraging AI will be playing a pivotal role in years to come. It’s more of a transformation mechanism vastly on the business side where newly developed technologies are being adopted. For some it has been a seamless integration where existing architectures have been re-used to integrate thereby saving more time both for developers and end-users. For the next five years, we can hopefully see the business industries on various domains thriving with AI leveraged Cloud computing taking the front seat while the leaders and tech giants convey the usefulness of AI to the entire mass. It’s absolutely one win-win situation to vouch for.