Google Cloud Platforms: A Mini Primer
Editorial Intern for The Indian Learning (e-ISSN: 2582-5631)
Indian Society of Artificial Intelligence & Law
Cloud computing, Artificial Intelligence (AI), and Machine Learning (ML) are some of the terms that have become commonplace in our everyday parlance as they become concepts that are not just complicated tech jargons but usable mechanisms that have tremendously improved our daily interaction with our technology and internet as a whole.
Cloud computing especially has taken off at a rapid pace, with everyone from your average user to large institutions being beneficiaries of it. The simple concept and line of thinking behind cloud computing are why would you need to spend a significant amount building and acquiring computing power and storage when they can be accessed virtually from your device for a price that is significantly less? The Covid-19 pandemic has only reinforced the point as to why cloud computing is the future as institutions across sectors have been forced to switch and see the benefits of cloud infrastructure as a majority of the population stay at home and function. While cloud computing has pretty much become a mainstay of our tech ecosystem now, integrating AI and ML algorithms into cloud services seems to be the next frontier that the big players in the industry are targeting.
Fashionably late but with tricks up its sleeve
The cloud infrastructure and platform market space today is made up of the big three, which include tech behemoths Amazon, Microsoft and Google all of whom combined have almost 60% of the entire market. Compared to its illustrious rivals in Amazon Web Services (AWS) and Microsoft Azure, Google was a bit late to jump into the extremely lucrative market space of cloud infrastructure and platform providers. Still, it has been growing rapidly, and experts have opined that its vast previous experience in AI and ML might give it a key edge over its more established rivals in a sector where efficiency and speed are valued above all.
The Google Cloud Platform (GCP) has both had a high rate of growth and bought in considerable revenue for google, something that is considered hard to do in any business field. GCP consist of a suite of cloud computing services that are both commercial but also an open-source to an extent. Google's commitment to making GCP stand out by offering unparalleled features in terms of creativity coupled with productivity and innovation based largely on an open-source ethos while also incorporating AI and ML elements has allowed this rapid expansion in a short span compared to its competitors. At its best, it is estimated that the most successful utilizers of the GCP are able to make 10 dollars for every 1 dollar spent, which is an unbelievable return on investment.
Products such as Dataflow, BigQuery, TensorFlow, and Kubernetes are prime examples of how Google has been able to integrate AI and ML into the GCP in order to execute advanced data analytics, create pre-built ML models and provide instant access to Application Programming Interfaces (API) that are pre-built. We are all familiar with Google's ubiquitous G Suite set of productivity apps and tools which have become part of our daily lives in the form of Gmail, Meet, Calendar, and more, all of which leverage the GCP to offer seamless synchronization and interoperability across devices.
GCP has been able to capture the attention of financial institutions and organizations for its very obvious capabilities to supercharge businesses. It also has been able to make a social impact with its use cases in health care, education, and commitment to environmental protection and sustainability. The bottom line is that cloud platforms like GCP are going to be dominant entities in multiple sectors as we advance. They are better in efficiency, reliability, scalability and all parameters that matter over the traditional on-premise infrastructure model of institutions which is soon becoming a thing of the past.
Impact and Utilization across Sectors
Business and Institutions
GCP has been able to incorporate AI and ML to provide businesses with opportunities to revolutionize their business practices through its speed, data analytics and many other factors which have prompted established institutions as well as startups to transition to the cloud ecosystem of GCP. Startups are now being set up centred around cloud computing and platforms like GCP that have more of an open-source ethos than their competitors are poised to be at the centre of this development.
GCP has some unique characteristics its rivals lack in terms of AI, ML. Combined with its transparent pricy policy and suite of ever-expanding tools, it is fast making it the cloud platform of choice for institutions and businesses. Let us look at the success stories of GCP in this space.
Niantic today are most famously known as the developers behind the extremely successful Augmented Reality (AR) game Pokemon Go which when released in 2016 was a worldwide sensation. Niantic had been using the GCP as its primary storage database and had been completely overwhelmed by a player base far higher than what they had anticipated. However, the scalability that GCP afforded meant that they were able to handle the much higher than anticipated data. Leveraging ML trained models and services like Kubernetes that GCP offered Niantic were able to push out updates without any disruption and also able to fix bugs and glitches that otherwise would have been much more time consuming and disruptive process for its users.
iGenius are an Italian based artificial intelligence startup whose aim is to simplify the search and understanding of the market and financial data through leveraging AI. iGenius has been able to develop a virtual and interactive business advisor named Crystal by leveraging GCP tools such as its translation API, cloud speech API, and prebuilt ML-trained models. iGenius claims that GCP was not only significantly cheaper and thus more affordable to use for a startup, its edge on the AI and ML meant that they were able to create Crystal significantly faster than they would have been able to in alternative cloud platforms.
This is not just in the case of business. Take institutions such as the Manchester City Council, which is one of the largest in the UK. Centring its working model into a GCP and G Suite based one has allowed it to work more efficiently and its employees to collaborate much easier. Costs of software licenses and storage solutions were bought down significantly while also reducing the council's carbon footprint. All of this has meant that it has been able to serve its constituents much easier and efficiently and showing us how GCP has been able to improve the lives of many for the better through cloud computing.
Cloud technology and platforms like the GCP have the potential and the capability to transform education as we know it. The pandemic we find ourselves in today has given us a small taste as to how the future cloud and AI-powered education might be. GCP, in particular, has a specialized G suite for educational purposes that are free of charge and customized to the needs of educational institutions. Educational Tools like Kaggle, which is a tool to learn data analytics and science, have been released as part of the GCP platform that is encouraging interest among students in the field of AI and ML.
What is commendable also is how Google has managed to provide for free a service that, if they monetized, could have bought them billions in revenue from almost 100 million users who use the specialized G Suites for Education. There are plenty of real-world examples of its uses.
Strayer University, for example, is focused on reskilling and education courses for working professionals. Their use of GCP and AI integration is perhaps a glimpse into the future of education. Teaching working professionals has meant that classes are most of the time online and uniform timing is also difficult which makes providing feedback and support to the students a challenge. As a solution, they were by utilizing GCP and one of its ML and AI tools in Dialogflow able to create a virtual assistant called "Irving" which could provide real-time live support and feedback to students 24/7. Its ML capabilities meant that it was able to constantly improve and provide better interactions each time.
Khan Academy is another example of an educational content provider who has leveraged GCP. GCP has allowed this widely known nonprofit organization to store a large amount of data and videos at a reasonable cost, and its utilization of ML tools of the GCP has allowed it to better provide content and get insights to improve their product to its almost 5 million monthly userbases.
Healthcare is another arena in which cloud-based services have slowly started expanding into, and GCP has also been the main benefactor of this development as healthcare spending on technology in the form of AI, data analytics, robotics etc., gradually increases. Cloud computing could play a huge role in data analytics and sharing among medical professionals if it can be properly implemented.
In its GCP tools, Google has a dedicated healthcare tool in Google Genomics that is customized for scientists and researchers in the healthcare sector to analyze and share and collaborate data using its API, which is open source. Google is also rolling out a Healthcare API on GCP to consolidate different types of healthcare data and advance interoperability among healthcare providers. Some of the successful use cases of GCP in healthcare are given below.