Category Archives: Week 10

The Consumer & The Cloud

Most of the ubiquitous computing we engage with in our everyday lives work in tandem with “the Cloud” – a seemingly abstract technology that some people are perplexed by. What exactly is the cloud? Unlike its illusory name, it is not a fluffy contraption in the sky beaming up all our data and then raining it back down on us when we need it. In de-blackboxed terms, cloud computing is simply storing and accessing data over the Internet, instead of on your specific device – your phone, laptop or smart TV.

The NIST definition of cloud computing consists of 5 characteristics, which help to further deblackbox the technology (Ruparelia, 2016). These characteristics consists of:

Cloud Computing Characteristics

  • Ubiquitous Access
  • On-Demand Availability based on the consumers self-service
  • Pooling of resources
  • Rapid Elasticity
  • Measured Service Usage

An example of cloud computing that consumers may be familiar with is evident in Apple’s iCloud, which is essentially a storage service. As of 2016, the service had 782 million users – an astronomical amount of data (Apple, 2019). Each iCloud account gets 5GB of storage for free, for email, documents, photos and backup data. For more data, such as if you were to have 10,000 photos on your iPhone, you pay a small monthly fee. Another popular example is Google drive, where one can access documents and media files remotely, free of the chains of traditional hardware based storage.

A cloud computing technology I was not familiar with however is Amazon Web Services. AWS is primarily a B2B service, happening beyond the reach of the end user and integral to the functionality of their services. AWS provides web-hosting services for a plethora of Fortune 500 companies. Despite the competitive war between Netflix and Amazon, I was surprised to learn that Netflix is in fact hosted on Amazon Web Services! The vast reach of AWS is further explored in this short clip from Patriot Act, Hasan Minhaj’s weekly stand up show which happens to be on Netflix:

The convergence of these technologies paves the way for a litany of potential social, cultural, ethical and of course technological implications. First, the benefits – there are several positive factors that cloud computing has brought into our lives. On a micro level, individuals such as employees can work remotely or students can now work collaboratively on the same document from multiple locations, increasing efficiency. Large companies can benefit from economies of scale, managing consumer accounts and media services in one platform. A potential privacy concern may emerge from this – who truly owns all this data? In the age of frequent privacy violations such as data breaches this raises large societal questions about data and privacy. Essentially, consumers choosing to use this technology may all be at the mercy of the oligopoly of the “big four”!

Cloud AI

Annaliese Blank

When we unpack the AI Cloud computing the realization here is most technology and big companies use Cloud software. According to Wikipedia, they say that Amazon has the largest public cloud and the internet itself acts as a cloud service. Some virtual assistants I wanted to unpack this week are Alexa, Google-Home, and Siri. Another thing I wanted to understand was how these technologies connect to the cloud in order to operate.

Virtual assistants are a different type of learning machine that always stay on and are always actively listening to you. They look for patterns in your voice and try to make predictions and connections that best identify you as their master operator. Whenever you ask it something, it must run your voice recognition patterns in order to make sure it is you speaking to them. They are friendly devices to other voices other than your own, but in general preference they must do this in order to keep track of what their owner says, wants, or needs to know by asking it a question or task. When you speak to it, the machine sends your recording to the cloud server to record what you say and they predict the best response possible. How do they do this?  

For Amazon Alexa, she mainly operates on the cloud. She is designed for more simple tasks and is able to answer quick or dense questions in a matter of seconds. She uses the cloud to store your questions and save your data. She gets to know you better by doing this.

For google products, they operate on a similar basis but in their own google cloud. Google performs links to your information by creating your own ‘google record’, and by doing this when we create google accounts we are agreeing to fully trust all of our information via their privacy services. Google home does exactly that. When you need certain answers to information and you have already researched your questions via phone or computer on google, Google home already has that saved under your profile which will help lead to an even faster answer. You can remove your search history on the product, or permanently from their Google cloud account on you.

Apple Siri is similar to these but uses their own apple cloud software. They do record the information you search or ask, but they don’t store it to your own personal length. Infact they use it for their own bettering of their company. They like to see who identifies what way and what they mainly search for and how they get the best results. They even say in their privacy statement on their cloud services, “We use personal information to help create, develop, operate, and improve our products, services, content, and advertising” (Apple Privacy, pg.1).

The cloud service is a superior advancement to AI. Its’ abilities are endless. When we unpack these forms of AI, it is important that we understand how the cloud works and what is actually being store privately in the cloud. Keeping information secure and private is the goal, but after learning bits and pieces of what each of these do it is vital that we are careful about what we search and what we say.


The Cost of Cloud Computing

Cloud computing allows for seamless and convenient use of online services that previously required more time, space, and money. For example, when creating a document (thanks to Google Drive) – it is no longer necessary to store the document on your personal computer’s drive, which keeps storage space open. It also reduces the amount of email correspondence necessary when editing a document or working on a group project because Google Drive allows for “sharing” as well as simultaneous editing of the same document. When given the option of protecting data on your own computer vs. using a program like Google Drive or iCloud- the winner is often the most convenient option, unless the user is aware of the disadvantages of using such a tool. 

From our discussions in this course, we recognize that giving away our information in order to receive convenience comes with negative outcomes. A key issue is the lack of clear information on exactly how each cloud service works. This keeps big companies like Amazon and Google in control over the majority of the population, and the more black-boxed technologies continue to emerge, the more control these companies have over the rest of the market. The issue with only a few large tech companies providing these services is that they are not being held accountable by a universal standard or regulation, which keeps us informed as users and therefore unaware of all the consequences that accompany use.

Cloud Computing:

Host companies (Amazon, Google, Microsoft) – own and run the datacentres, servers, hard disks and processors for the computation 

Cloud Service Providers (SaaS) Google Drive, Dropbox – provide online services

Clouders: users of the service at home or business

Key Positive / Negative Consequences

Sharing & Storage Capacity

The ability to easily share large files through services such as Dropbox and Google Drive are a big positive consequence of cloud services. In addition, storing information within a cloud service rather than on a pc drive or external drive, has allowed for created a more minimalistic storage option that individuals and corporations are endlessly benefitting from. 

Saving Energy 

A 2010 Pike Research study (as cited in DeBruin and Floridi, 2017) found that cloud computing can reduce energy consumption by almost 40% – mostly due to “outsourcing computational tasks from inefficient local datacentres (or home and office computers) to the more efficient large datacentres of the hosting companies.” Cloud Computing can therefore be a solution to controlling the amount of energy used for computing by reducing the need for powerful hardware. On the other hand, more information about how many datacentres are needed to support cloud services and what impact they are having on the environment in totality. 

Lack of Transparency/Communication

Terms of service and license agreements are not user-friendly, and create lack of transparency in the industry-client relationship. These are usually created to avoid any legal repercussions rather than intending on informing the client about the service (DeBruin and Floridi, 2017). Although these agreements do include the most information heavy communication, they are not utilized as such from the users of the services due to the length and technical jargon. 

Business Costs

Large businesses benefit from the cloud architecture because they no longer have to pay for software to be installed, configured, and maintained on each computer (DeBruin and Floridi, 2017). The disadvantage is for smaller companies because they might not be able to pay for the services (fees, updates, etc) and therefore are left out of the advantages. Additionally, the services are intended by design for larger companies – which makes using the services more difficult and less tailored to the smaller ones. This is one of the major disadvantages of having the big four services – it automatically favors larger businesses that can afford to pay for and benefit from the cloud architecture. This leads to the question of who is really benefitting from cloud computing and is it contributing to the digital divide rather than closing it? 

“While cloud computing seems to be a boon to a population that cannot afford the computer equipment that is necessary for today’s IT—a very simple laptop is sufficient for cloud computing—it also requires reliable, ubiquitous and high speed Internet connections that are almost entirely absent, and if not absent very expensive, in large parts of the world” (DeBruin and Floridi, 2017). 

Key Takeaway:

“To benefit genuinely from their freedom, people have to know what actions they can choose from and they have to know what the likely consequences of these various choice options are. In other words, they have to know the characteristics of their opportunities (DeBruin and Floridi, 2017) “

“Clouders need to have general knowledge about the advantages and disadvantages of cloud computing; and they need to have specific knowledge about the services they buy and use or consider buying or using” (DeBruin and Floridi, 2017).

This specific knowledge needed is not provided for users in an accessible way, which leaves users dependent on these services. The issue with the convergence of technologies all packages into one service provided by one of the large Cloud service providers – is dependence and loss of privacy, agency, and control. It is also contributing to the digital divide, in that using these services requires high speed internet connection and the ability to cover the costs of service.

Thinking through this has reminded me of the show Mr. Robot, and how computer hacking is equated with “owning” someone or some organization. Access to personal information is incredibly powerful in any setting, and companies are giving access away by trusting their information will be safe in the Cloud. In certain cases, users are unaware that their information is being stored at a third party. Additionally, if anything happens to compromise the date stored in the Cloud, the repercussions could be drastic for large companies. In any case, users of the service need to be aware of what they are agreeing to when they sign up to use a Cloud service.


DeBruin, Boudewijn, and Luciano Floridi. “The Ethics of Cloud Computing.” Science and Engineering Ethics, vol. 23, no. 1, 2017, pp. 21–39.
Derrick Roundtree and Ileana Castrillo. The Basics of Cloud Computing: Understanding the Fundamentals of Cloud Computing in Theory and Practice. Amsterdam; Boston: Syngress / Elsevier, 2014. Excerpts from Introduction and Chap. 2.


Cloud Computing, Principles and Architecture

As Rountree and Castrillo explain, there has been a lot of debate about what the cloud is. Many people think of the cloud as a collection of technologies. It’s true that there is a set of common technologies that typically make up a cloud environment, but these technologies are not the essence of the cloud. The cloud is actually a service or group of services. This is partially the reason that the cloud has been so hard to define.

So, what is cloud computing?

Cloud Computing is a paradigm that allows on-demand network access to shared computer resources.  It is a way for managing, storing and processing data online via the Internet.

Some cloud computing characteristics include:

  • On-Demand Self-Services – A consumer can request and receive access to a service offering, without an administrator or some sort of support staff having to fulfill the request manually
  • Broad Network Access – Using Internet as your medium, it should be easily accessible
  • Resource Pooling – It is based on the fact that clients will not have a constant need for all the resources available to them
  • Rapid elasticity – Describes the ability of a cloud environment to easily grow
    to satisfy user demand
  • Measured Service – Cloud services must have the ability to measure usage

It is also important to mention that there are 4 Cloud Deployment Models:

  • Public – All the systems and resources that provide the service are housed at an external service provider
  • Private – The systems and resources that provide the service are located
    internal to the company or organization that uses them
  • Community – Community clouds are semi-public clouds that are shared between members of a select group of organizations.
  • Hybrid – A hybrid cloud model is a combination of two or more other cloud models

Cloud computing provides different services based on three delivery configurations. When they are arranged in a pyramid structure, they are in the order of SaaS, PaaS, and IaaS:

The Cloud Pyramid

  1. SaaS or Software-as-a-Service — This is the layer the end-users face and it provides the functionality these users demand: social media communication, collaboration on documents, catching a taxi or booking a room for a night. This layer offers a limited set of functionalities and literally no control over the computing resources. Nevertheless, the end users get what they came for — functionality.
  2. PaaS or Platform-as-a-Service — an underlying level of APIs and engines allowing the developers to run their apps. This is a layer where the AWS or Azure users leverage the platform functions (like the latest batch of tech AWS introduced during their re:Invent week 2017). This level of the cloud pyramid allows the developers configure the resources needed to run their apps within the limits set by the cloud platform. This level demands to have some understanding of the processes and structure of your cloud, at least to be able to tick the appropriate boxes in the dashboard of said cloud service provider (CSP).
  3. IaaS or Infrastructure-as-a-Service — the lowest level of the cloud services, where the DevOps engineers work with the tools like Terraform, Docker, and Kubernetes to provision the servers and configure the infrastructures, processes, and environments, enabling the developers to deploy their software, APIs, and services. This layer might work with the hardware provided by cloud service providers like AWS or GCP or with on-prem bare metal Kubernetes clusters running in private or hybrid clouds. This level provides the most capabilities (like load balancing, backups, versioning and restoration of an immutable infrastructure) yet requires the most skills to be operated correctly.

As the Ecourse suggests, here are some companies that offer Cloud Computing services:

iCloud – Cloud from Apple is for Apple products. You can backup and store everything from multimedia to documents online. The content is then smoothly integrated onto your devices.

Amazon’s AWS – When you talk about companies using cloud computing, Amazon Web Services leads the pack. It offers IaaS and PaaS to all their customers.

Google Cloud – This cloud platform is universal for Google’s enormous ecosystem and for other products such as Microsoft Office. It provides storage of data and collaboration along with other services that are included in their cloud computing suite.

Microsoft Azure – Offered by Microsoft, it provides SaaS, PaaS, and IaaS for its software and developer tools. If you have used Office 365, then you have used SaaS.

IBM Smart Cloud – This offers private, public, and hybrid distribution platforms providing a full range of SaaS, PaaS, and IaaS cloud computing services for businesses. The pay as you go platform generates profits for IBM.

Now that we have a better idea of the Cloud, let’s take a look at the architecture and see  how the modules and layers/levels are designed for combination.

According to Organization for the Advancement of Structured Information Standards (OASIS),
the cloud computing reference model is an abstract model that characterizes and standardizes the functions of a cloud computing environment by partitioning it into abstraction layers and cross-layer functions. This reference model groups the cloud computing functions and activities into five logical layers and three cross-layer functions.

Cloud Computing Layers:

Physical Layer 

  • Foundation layer of the cloud infrastructure.
  • Specifies entities that operate at this layer : Compute systems, network devices and storage devices. Operating environment, protocol, tools and processes.
  •  Functions of physical layer : Executes requests generated by the virtualization and control layer.

Virtual Layer

  • Deployed on the physical layer.
  • Specifies entities that operate at this layer : Virtualization software, resource pools, virtual resources.
  • Functions of virtual layer : Abstracts physical resources and makes them appear as virtual resources (enables multitenant environment). Executes the requests generated by control layer.

Control Layer

  • Deployed either on virtual layer or on physical layer
  • Specifies entities that operate at this layer : control software
  • Functions of control layer : Enables resource configuration, resource pool configuration and resource provisioning. Executes requests generated by service layer. Exposes resources to and supports the service layer. Collaborates with the virtualization software and enables resource pooling and creating virtual resources, dynamic allocation and optimizing utilization of resources.

Service Orchestration Layer

  • Specifies the entities that operate at this layer : Orchestration software.
  • Functions of orchestration layer : Provides workflows for executing automated tasks. Interacts with various entities to invoke provisioning tasks.

Service Layer

  • Consumers interact and consume cloud resources via thos layer.
  • Specifies the entities that operate at this layer : Service catalog and self-service portal.
  • Functions of service layer : Store information about cloud services in service catalog and presents them to the consumers. Enables consumers to access and manage cloud services via a self-service portal.

Let’s take a look at the cross-layer functions:

Business continuity

  • Specifies adoption of proactive and reactive measures to mitigate the impact of downtime.
  • Enables ensuring the availability of services in line with SLA.
  • Supports all the layers to provide uninterrupted services.


  • Specifies the adoption of : Administrative mechanisms (security and personnel policies, standard procedures to direct safe execution of operations) and technical mechanisms (firewall, intrusion detection and prevention systems, antivirus).
  • Deploys security mechanisms to meet GRC requirements.
  • Supports all the layers to provide secure services.

Service Management

Specifies adoption of activities related to service portfolio management and service operation management.

Sevice Portfolio Management:

• Define the service roadmap, service features, and service levels

• Assess and prioritize where investments across the service portfolio are most needed

• Establish budgeting and pricing

• Deal with consumers in supporting activities such as taking orders, processing bills, and collecting payments



Vladimir Fedak. The Medium, What is the Cloud Computing Pyramid: The layers of DevOps Services –

Derrick Roundtree and Ileana Castrillo. The Basics of Cloud Computing: Understanding the Fundamentals of Cloud Computing in Theory and Practice. Amsterdam; Boston: Syngress / Elsevier, 2014.

Cloud Computing Services Models – IaaS PaaS SaaS Explained (EcoCourse)

Nayan B. Ruparelia, Cloud Computing (Cambridge, MA: MIT Press, 2016)

Is Cloud Storage more dangerous than Physical Storage?

The advent of cloud computing has drastically improved the capabilities of computing including the management and processing of information. Cloud computing also provides organizations with a cheaper and more efficient method for using information which otherwise would be hard to access and track. The semi conglomeration of cloud computing providers, however, leads to many question about who really owns information and what they have the power to do with it. The four main companies that provide cloud computing services are Google, IBM, AWS and Microsoft. These four companies are not solely cloud computing providers, they are also businesses with other products that touch almost every aspect of the digital realm.

The access to information by these organizations is abundant, but as we’ve seen through numerous hacks and reports of misuse, the regulation and security of the data stored by these companies has room to grow. This is not an issue that is exclusive to cloud computing, but to any company that stores information. Unfortunately, it seems that personal information is almost always at risk whether it is stored digitally by Google or stored in hardcopy by Georgetown. I work in an office which deals with the personal files of students and the security of these files often seems lacking to me. This gives me pause, especially when critiquing the security and safety of cloud storage. It seems that the sole way to protect ourselves and our data from misuse is simply by not sharing it. That is difficult in more ways than one, since our physical worlds and digital ones cannot be separated.

Though we face the same risks of information being viewed and abused both digitally and physically, cloud computing offers malicious actors a veil of anonymity and silence. When data is taken from Google or IBM, often times the people who take the data remain unknown to the public. When data is taken from physical files there is often evidence left behind, whether that is a missing file or a person who is acting upon information that they should not have. The digital realm makes information hard to conceptualize, especially when it has been stolen. Knowing that IBM has been using Flickr images without the consent of users, is easy to understand conceptually but the impact of this is wildly misunderstood.

Cloud computing benefits us and the technology we use daily, but the risks of cloud computing can often seem greater than the benefits. I think that the dangers of cloud computing are sometimes made bigger by the media in the same way that AI and the impending doom it enables does. I wonder if cloud computing is safer or more risky than the storage of physical data in a warehouse?

Cloud Computing in Chatbot and Its Shortcoming

Cloud computing is a paradigm that allow on-demand network access to shared computing resources. It is a model for managing, storing, and processing data online via the internet. (Cloud Computing)

Cloud computing is a growing market. According to a study by Forbes, Cloud computing is projected to increase from $67B in 2015 to $162B in 2020 attaining a CAGR of 19%. The examples of cloud computing are everywhere from the messaging apps to audio and video streaming services.

For example, chatbots, such as siri, Alexa and google assistant, all are cloud-based natural-language intelligent bots. Capacity of the cloud enables business to store information about user preferences and provide customized solutions, messages and products based on the behavior and preferences of users. These chatbots leverage the computing capabilities of the cloud to provide personalized context-relevant customer experiences.

Cloud computing is still in its infancy. (The basics of cloud computing) Although cloud computing benefits in both our ordinary lives and business, it can still cause lots of problems if we don’t regulate it in the right way. One of the problems with cloud computing is that technology is frequently light years ahead of the law. There are many questions that need to be answered.

Security and privacy is one of the biggest issue for our data. Does the user or the hosting company own the data? Can the host deny a user access to their own data? Data is kind of valuable asset for both individual and companies. How can the “big four” companies (Google, AWS, IBM, Microsoft) ensure users’ data privacy? In fact, these years more and more news pop up related to data leakage of business and individuals by the Internet companies.

Besides, owing to developing in very short time, lack education in public is also a problem. Cloud computing is a kind of service, not a product, so it is very hard to define and communicate in public. Due to a lack of normal communication between the cloud computing industry and its customers, users have very little control over or even knowledge of who may be sharing the same systems as them and the principle of system charge.

To some extent, regulation of the business customers of the cloud services providers is urgently needed.


Nayan B. Ruparelia, Cloud Computing (Cambridge, MA: MIT Press, 2016). Selections.

Derrick Roundtree and Ileana Castrillo. The Basics of Cloud Computing: Understanding the Fundamentals of Cloud Computing in Theory and Practice. Amsterdam; Boston: Syngress / Elsevier, 2014. 2.

Boudewijn de Bruin and Luciano Floridi, “The Ethics of Cloud Computing,” Science and Engineering Ethics 23, no. 1 (February 1, 2017): 21–39.

Our Heads in the Cloud(s)

Researching cloud computing led me to two different ideas that I wanted to write about, one of which carries over from a course I took last semester, but both deal with the notion of ownership in the digital age of streaming, sharing, and cloud storage.

Outsourcing Memories

I haven’t had available local storage space on my iPhone since 2012. By the time widespread music streaming came about, and I was able to delete the 10-20 GB of my imported/downloaded music library, I still had several years’ worth of apps, photos, videos, texts, documents, software updates and other miscellaneous data clogging up the available storage on my device. iCloud storage was a tremendous relief to those concerns. At 99 cents per month for 50GB of cloud storage, I haven’t had to worry about deleting precious data or memories in several years.

What’s concerning to me about cloud storage for our mobile phones is that so much of our life experiences are mediated through these devices. It becomes a way of outsourcing our memories so that we can better focus our attention and cognition on processing the incessant flow of information that comes pouring across our screens every day. It allows us to reflect in a mediated, visceral way on what we’ve done, where we’ve been, who we’ve met, etc. in a linear, narrative fashion (reading through text histories, reviewing the camera roll, using “Timehop” to see past social media posts and interactions). But if we’re paying a company to store all that information for us in ‘the cloud,’ rather than keeping it stored away in our own heads (impossible) or in some kind of physical scrapbook or memory box (outdated), are those memories still technically ours? If (god forbid) the cloud servers went down for Apple, or Google, or Amazon, etc. we wouldn’t have access to our own precious, private, and personal data. That doesn’t seem like ownership– in the traditional sense, at least– to me. And while I trust that these companies are doing everything they can to protect our information and ensure that it doesn’t fall into the wrong hands or that their services don’t fail us, we’ve seen dozens of examples of massive data breaches and leaks over the past decade that have exposed very personal, private, and often compromising information, images, etc. of countless people around the world.

I guess these are the risks and sacrifices we are willing to make for the convenience of never needing to delete anything. As de Brun and Floridi write in their 2017 paper on “The Ethics of Cloud Computing”:

“We observe that cloud computing suits the interests and values of those who adopt a deflated view of the value of ownership and an inflated view of freedom (De Bruin 2010). This is especially, but not exclusively, Generation X or the Millennials, who care less about where, for instance, a certain photograph is stored and who owns it (Facebook? the photographer? the photographed?) and care more about having the opportunity and freedom to do things with it (sharing it with friends, posting it on websites, using it as a background for one’s smartphone).” (p. 22)

This segues nicely into my next topic, on streaming and remix culture in the age of cloud computing.

Cloud-Based Streaming

All this reading on cloud computing made me think back to Dr. Osborn’s Remix Practices course in the Fall, where we read Remix by Lawrence Lessig (2008). I was amazed that Lessig was able to predict the impending cultural obsession with online, cloud-based streaming platforms like Netflix and Hulu (Netflix started offering streaming services in 2007, and Hulu was created in 2008, the same year this book was published). In his book, Lessig (2008) writes, “In the twenty-first century, television and movies will be book-i-fied. Or again, our expectations about how we should be able to access video content will be the same as the expectations we have today about access to books…in both cases, according to your schedule, not the schedule of someone else” (p. 44). Seven years later, “binge-watch” was named the 2015 Word of the Year by Collins English Dictionary, after “lexicographers noticed that its usage was up 200% on 2014” (BBC News, 2015). These numbers have continued to rise rapidly, with many more streaming services becoming available and encouraging consumers to ‘cut the cord’ of cable television or imported music libraries.

It seems that cloud-based streaming may be the solution that many entertainment companies have turned to in their attempt combat piracy, and it saves a lot of storage space on our devices in the process. Since the videos or music are streamed, there are often no downloadable files to “steal” and store locally, as was made popular by torrenting sites and other file-sharing platforms in the not-so-distant past. However, consumers can still easily obtain the content by screengrabbing photos and videos or recording audio with their own equipment. As we’ve seen, copyright lawyers can be pretty fierce, but how far are they willing to go to stifle the free exchange of content and media in the anarchistic Wild West of the internet?



“Binge-watch is Collins’ Dictionary’s Word of the Year” (5 November 2015). BBC News.

de Bruin, B., & Floridi, L. (2017). The Ethics of Cloud Computing. Science and Engineering Ethics, 23(1), 21–39.


Lessig, L. (2008). Remix: making art and commerce thrive in the hybrid economy. New York: Penguin Press.
Rountree, D., & Castrillo, I. (2014). The basics of cloud computing: understanding the fundamentals of cloud computing in theory and practice. In The Basics. Amsterdam ; Boston: Elsevier/Syngress.

Facial Recognition and Cloud Computing

As we know, facial recognition is based on artificial intelligence and machine learning. Machine learning involves recognizing patterns from a great number of existing data by a set algorithm until it is capable of predicting new data. In machine learning, a Convolutional Neural Network (CNN) is a class of deep artificial neural networks that has successfully been applied to analyzing visual imagery. Facial recognition is one of its applications. To enhance the capability of this technology, cloud-based facial recognition system has emerged.

According to National Institute of Standards and Technology (NIST), cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. It has five desirable characteristics such as on-demand self-service, broad network access, resource pooling and rapid elasticity. In a facial recognition system implemented in cloud infrastructure, the facial recognition engine is located in the cloud, not in the local processing unit (used in the traditional method).

Moving both the facial recognition engine and facial recognition database onto the cloud helps to render a seamless system. This model is employed by several commercial applications to carry out security check. The query face is captured by the user and transmitted to the cloud server for conducting authentication with the gallery faces of the facial recognition database located on the cloud.

The new faces are enrolled through the user interface, or say, user application. In order to carry out the task of Face Tagging, the user interface communicates with the cloud-based web API (application programming interface) that contains the facial recognition engine and a database of faces. The user interface enrolls new faces and encodes the face image, which is then sent to the cloud-based API that processes the image through the facial recognition engine. The facial recognition engine runs a pre-defined facial recognition algorithm. The query face from the user interface is then compared by the facial recognition engine against a gallery of images.  After a conclusive match is determined, the query face will be classified as belonging to a particular individual or not. Then, the result will be sent back to the user interface.

Cloud-based facial recognition systems bring about various benefits coming from inherent characteristics. They have the advantage of real-time processing. On demand self-service allows customers to quickly procure and access the services they want. Moreover, cloud computing allows the system to become broadly accessible in the sense that cloud services provide the capability for quick and reliable integration with other applications. In addition, cloud services facilitate high scalability in order to ensure that the system can be adapted to a wide user base.


Nayan B. Ruparelia, Cloud Computing (Cambridge, MA: MIT Press, 2016). Selections. Read chapters Introduction, 1-3.

Derrick Roundtree and Ileana Castrillo. The Basics of Cloud Computing: Understanding the Fundamentals of Cloud Computing in Theory and Practice. Amsterdam; Boston: Syngress / Elsevier, 2014. Excerpts from Introduction and Chap. 2.

Vinay, A., Shekhar, V. S., Rituparna, J., Aggrawal, T., Murthy, K. N. B., & Natarajan, S. (2015). Cloud based big data analytics framework for face recognition in social networks using machine learning. Procedia Computer Science, 50, 623-630. doi:10.1016/j.procs.2015.04.095

What’s Old is New (and Conglomerated into 4 Mega Corporations)

Cloud computing makes a lot of sense. When you think about all the computational power that is lost Simply because no one is using the system, you begin to see one of the major benefits of cloud computing: more computational power and storage available to more users at a cheaper price point. This idea has deep roots within the history of computation, going as far back as the 1960s with the implementation of time-sharing as a revolution of accessibility to computational power. Timesharing allowed “a central computer to be shared by a large number of users sitting at terminals. Each program in turn is given use of the central processor for a fixed period of time” (Arms). This computational model was efficient when computers were unruly and expensive. Gradually, the minicomputer won out over massive mainframe models, and the personal computer became the de-facto form of computation. However, the benefits of sharing powerful resources are again becoming transparent with the contemporary rise of cloud computational models. For better and worse, cloud computation is contemporarily conglomerated into the “big four:” Google, AWS, IBM, Microsoft.

A positive and negative effect of contemporary cloud computing is the standardization of inputs and outputs that a cloud computing model requires. As Ruparelia says, “to truly deploy a cloud, you need to consider how to standardize your service offerings, make them available through simple portals, track usage and cost information, measure their availability, orchestrate them to meet demand, provide a security framework, provide instantaneous reporting, and have a billing or charging mechanism on the basis of usage“ (Ruparelia, Page 7). This standardization means that users do not have access to full power of the cloud computing system, just a mediated form of it as dictated by the big four companies that create the cloud architecture.

One of the most blatant and obvious negatives of the conglomeration of cloud services is the potential for security breaches and a loss of data privacy. When user data is conglomerated into one database or platform in the cloud (one that has linkable personal identifiable information ready and available), a hacker has a large incentive to steal this data. With the implementation of cloud computing, a hacker doesn’t need to hack hundreds of computers before they stumble upon a juicy target; now, a hacker just needs to pwn a single cloud database to steal thousands of users’ information.

In addition to cloud computing increasing the power and ease of the explicitly malicious actors stealing personal information, conglomerated user data in several cloud platforms – especially cloud platforms that have cross-service terms of service and privacy policies– gives heightened power to collect and sell behavioral data. Most of this data is viewed as payment for free services, but many users do not understand the scope of identification that can occur with such data collection. Having different types of data accessible within a conglomerated cloud service increases the ability and efficacy of corporate surveillance.

Arms, W. (n.d.). The Early Years of Academic Computing. Retrieved March 27, 2019, from The Early Years of Academic Computing website:
Blagdon, J. (2012, March 1). Google’s controversial new privacy policy now in effect. Retrieved March 27, 2019, from The Verge website:
Mack, Z. (2019, March 26). Shoshana Zuboff on understanding and fighting surveillance capitalism. Retrieved March 27, 2019, from The Verge website:
Ruparelia – 2016 – Cloud computing.pdf. (n.d.).
Ruparelia, N. (2016). Cloud computing. In The MIT Press Essential Knowledge Series. Cambridge, Massachusetts: The MIT Press.

Cloud Computing in AWS

Tianyi Zhao

It has been thirteen years since the popularization of cloud computing. Cloud computing has achieved rapid development and dramatic changes, which is another transformation following the one from large-scale computers to the client servers, from the dwindling in size to the cloud in form. Organizations around the world have invested cloud computing and continue to go deep. According to IDG’s Cloud Computing study in 2018, seventy-three percent of organizations have at least one application, or a portion of their computing infrastructure already in the cloud, while 17% plan to do so within the next twelve months. Although cloud computing has been welcomed in the market, the definition of it has not been unified by multi-parties. National Institute of Standards and Technology (NIST) states it as “a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources… that can be rapidly provisioned and released with minimal management effort or service provider interaction.” There is no doubt that the words need more updates as cloud computing evolves.

Amazon Web Services (AWS), officially launched in 2006 and popularized cloud computing, has maintained its leader role as its market share nudged up a percentage point to 34%, remaining bigger than its next four competitors combined (Microsoft, IBM, Google, and Alibaba). AWS keeps its dominance by dealing with wide ranging of cloud computing facilities developing a highly scalable and an on-demand computing platform, providing the full computing stack in the form of virtual resources.

Figure 1. AWS Architecture Diagram


Among the AWS products, Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS) take up the most parts. The users are mainly the system administrators and developers of the enterprises who purchased the services, which help them move faster, lower IT costs and scale. Besides the featured products such as EC2, S3 and RDS, one service called Amazon Transcribe finely leveraged cloud with machine learning. It is an automatic speech recognition service, which takes in audio and automatically generates accurate transcripts, helping developers to add speech-to-text capability to their applications– including customer service, subtitling, search and compliance.

Figure 2. How Amazon Transcribe Works


The figure above shows a general routine that how Amazon Transcribe works.

  • Speech input: to store the file as an object in an Amazon S3 bucket and to specify the language and format of the input file.
  • To identify the individual speakers in an audio clip with speaker identification (between 2 and 10 speakers in an audio clip)
  • Channel identification: to split the audio file into multiple channels and transcribe the channels separately. After finishing transcribing all channels, it merges the transcriptions to create a single transcription.

Additionally, Amazon Transcribe can also transcribe streaming audio in real time and custom vocabularies for higher accuracy. The success of Amazon Transcribe relies on their specific attention on punctuation, confidence score, possible alternatives, time generation, custom vocabulary and multiple speakers. And it is continually learning and improving.


Works Cited

AWS. Amazon Transcribe Developer Guide. 2019.

Tiwari, R., et al. “Project Workflow Management: A Cloud Based Solution-Scrum Console.” International Journal of Engineering and Technology (UAE), vol. 7, no. 4, Science Publishing Corporation Inc, 2018, pp. 2457–62, doi:10.14419/ijet.v7i4.15799.

Ruparelia, Nayan B. Cloud Computing. Cambridge, MA: MIT Press, 2016.

Derrick, Lleana Castrillo. The Basics of Cloud Computing: Understanding the Fundamentals of Cloud Computing in Theory and Practice. Amsterdam; Boston: Syngress / Elsevier, 2014.

2018 Cloud Computing Survey. IDG, Aug. 2018.

Bozicevic, Vedran. “State of Cloud Computing Report 2019: Cloud Spending is on the Rise.” GlobalDots, Jan. 2019.

Bailey, James. “AI-Powered Transcription Services Showdown: AWS VS. Google VS. IBM Watson VS. Nuance.” Armedia, Jan. 2019.