The Impact of Intelligent Automation on Global Data Storage and the Workforce

The widespread adoption of technologies focusing on interconnectivity and automation in industrial environments, as well as recent advances in AI technology, are at the root of the ever-increasing amount of data being generated and processed on a daily basis. We will take an in-depth look at the staggering numbers used to describe these unimaginable amounts of data, as well as the societal challenges and implications of the ongoing technological paradigm shift.

Table of Contents

1.? ? ? Stanis?aw Lem's ?Growing Torrent of Information“

2.? ? ? 2.5 Quintillion Bytes Generated Each Day

3.? ? ? Smart Factories and Their Insatiable Hunger for Data

4.? ? ? The Social Implications of AI and Automation

5.? ? ? The Future of Data Processing

6.? ? ? Conclusion

1. Stanis?aw Lem's ?Growing Torrent of Information“

?Recognizing the quality of information, not accepting completely irrelevant advertising, secondary information that is simply unnecessary for a human being, is a necessary condition for 'staying afloat' amidst a growing torrent of information.“

This quote from renowned Polish sci-fi writer and philosopher Stanis?aw Lem dates back to the essay Informacja o informacji from the early 1990s and is more applicable than ever before. In today’s information age we are downright flooded with data, the amount of information generated every single day is staggering. Over 90% of the information ever created by humanity - books, music, database entries or whatever else you can think of - was created in the last decade and exists almost entirely in a digital form. Filtering and processing this data and discerning valuable data from junk data is a task requiring processing power and data storage far exceeding the capabilities of the human brain.

2.?2.5 Quintillion Bytes Generated Each Day

Humanities data footprint grows larger and larger every day, including pictures of cute kittens, YouTube, Facebook, Instagram and Twitter posts, videos and everything else. Skype alone has three billion minutes of calls per day. Five billion Snapchat videos and photos are shared every 24 hours, 333.2 billion emails are sent in the same period. Every minute people spend one million US dollars online. Around five billion people - or a good 65% of the world population - currently interact with digital information every day. This proportion could increase to 75% by 2025.

The total quantity of data processed globally globally in the year 2018?already amounted to 33 zettabytes - according to the Data Age 2025 study conducted by IDC Global Data Sphere, sponsored Seagate, a big player in the storage industry. One zettabyte written out as a number is a 1 followed by 21 zeroes, one quintillion written out is a 1 followed by 18 zeroes. To truly grasp the enormous amount of data created daily, consider this figure: 2.5 quintillion bytes, written out in full looks like this:

2,500,000,000,000,000,000

Storing this immense amount of data physically would require 33 billion physical drives with a capacity of 1TB each. According to further research conducted by IDC the amount of data processed globally per year will reach an astounding 175 zettabytes by 2025.

3.? ? Smart Factories and Their Insatiable Hunger for Data

Data is the foundation of almost all integral parts of our everyday life. Our most critical infrastructure, such as traffic, transport, energy, telecommunication and emergency services, simply cannot function without data. Smart homes, the Internet of Things, autonomous driving and all other current technology trends are highly data intensive and are driving factors in the expected exponential increase in data usage in the near future.

The industrial sector, a crucial topic for us here at Codelab, is arguably one of the major catalysts in this development. Industrial devices and systems generate massive amounts of information, even when configured in the less data hungry report by exception mode, which has been an industry standard for many years. The data collected is typically related to large machines and includes signals about the current working conditions of a machine, like temperature signatures, engine speed or oxygen content for example. Any given parameter is represented as an electrical signal, which can be stored, transferred and then analysed, in order to find regularities, inconsistencies, similarities and to diagnose problems and anticipate failures. The aggregated data is then used to optimize the efficiency of productional processes and to determine when to proceed with preventive maintenance measures in order to avoid prolonged productions stops and thus increase profitability.

The rise of data-driven smart factories

The digitization study by IDC and Seagate predicts that there will be around 150 billion connected devices on our planet by 2025. We can assume, with a high degree of probability, that a significant percentage of those devices will be deployed in the industrial sector. The fact that all those devices run software using exciting, state of the art technologies and frameworks are the reasons why Codelab decided early on to focus on developing software for the Industrial Internet of Things (IIoT).

Every year the trend of digitization in the industrial sector becomes more apparent and significant. In our modern, digitalized world, more and more factories are being gradually upgraded and transformed into smart factories which differ from traditional non-smart factories in fundamental aspects. One key difference is that their operation is completely data-driven. Smart factories are intended to be semi-virtual spaces with interconnected machines continuously collect data via countless sensors.

The data being accumulated and incorporated into the production process can be split into two groups: external and internal data. The internal data includes all internal company data as well as data gathered from machines inside the factory. As companies have gradually started collecting data about how their products are used, especially technical products, the amount of external data collected is consistently increasing. These days the products themselves usually gather the data, something that had been considered the holy grail of the manufacturing industry for some time. Combining this external data with the internal data resulted in substantial leaps in maximizing efficiency in the production process.

With this new data driven approach, manufacturers can significantly extend product lifespan and reduce product failure by evaluating its performance in the field based on behaviour profile data from end users. Such an approach also has the potential to spark a fundamental change in the context of the further customization of production assortment.

The Role of Data Centers in the Factories of the Future

Data centers are indispensable when it comes to the processing of these enormous amounts of data and as such data centers are an integral part of both public and private clouds. Data centers are essential for factories of the future as they are used for providing decentralized storage and archiving, service delivery, extensive analytics and command and control. As more and more processes are being digitized, both inside and outside of factories, none of them would be able to work as a single separated entity. This is due to a fundamental shift in how global production and supply networks operate. Whether a factory is responsible for core operations or just executive elements, it has to communicate with many different external systems. The topic of data processing transcends far beyond the automation of traditional manufacturing and industrial practices, like large-scale machine-to-machine communication (M2M or the Internet of Things (IoT). Extensive digital data analysis offers many great opportunities to further increase its usefulness and could be used to implement a more organic approach - managing energy resources and raw materials in a more circular way and on a larger scale. Digitization and automatization paired with big data analysis are part of the unstoppable automation age, which comes with both previously unimaginable opportunities and consequential implications.

4.? ? The Social Implications of AI and Automation

Another important aspect of the development of the factories of the future is the processing of? these large amounts of data, which would not only require simultaneous effective communication and data analysis but also active, strategic planning predicting trends. Traditionally these functions were occupied by human workers, something that may be about to change soon, as the amounts of data are currently way too large to be analysed effectively by human entities. Inference speed is another area in which computers and AIs are far superior to humans. If we extrapolate, it is safe to assume that the wide-spread use of AI systems in the factories of the future is inevitable due to the sheer amount of data being amassed. Studies conducted in this field show many jobs traditionally performed by humans are already performed by autonomous systems. Numbers are rising every year, leading to fundamental changes in the labour market. For further reading on this topic please refer to Mind Children: The Future of Robot and Human Intelligence by Hans Moravec and specifically the ‘The Landscape of human competence’ graphic.

5.? ? The Future of Data Processing

It is still a matter of debate whether it is possible to construct an Artificial General Intelligence (AGI) that would be capable of reproducing generalized human cognitive abilities in software. This theoretical AGI would be able to find solutions for complex unfamiliar problems, much like a human would. The development in this field is still in its infancy and it could take decades or even centuries until AGIs are widely adopted. There are many great resources widely available for more in-depth information on this topic, for example Life 3.0: Being Human in the Age of Artificial Intelligence by Max Tegmark. Currently AGIs are not crucial for the further automation of factories, which currently rely on Artificial Intelligence (AI). Depending on future technical advancement AGIs might never be successfully deployed, or AI systems being trained on a much narrower field of expertise, might turn out to be more than enough to meet the requirements of the factories of the future. Please consult this article about the distinction between AGI and AI. Whether future industrial atomization will be driven by AGI or AI technology is currently impossible to predict, but one thing we know for sure is that we as humans will need more extensive support from our semi-autonomous or fully autonomous systems and their artificial counterparts.

6.? ? Conclusion

Will the factories of the future be completely automated and able to function without any human workers? While predictions with a 100% accuracy regarding this question are clearly impossible, prominent trends are evident and there is no turning back to outdated production models. This leads us to the more general conclusion that data is one of the cornerstones of The Fourth Industrial Revolution (4IR) or Industry 4.0, something we explored previously in a separate article which covers the importance of Industry 4.0 for the manufacturing industry.

Data is changing the world. The flood of data is becoming increasingly more ubiquitous and influences more and more aspects of our lives. Whatever the future holds in the context of technological development, the challenge lies not only in handling the astonishing amount of data but also the subsequent drastic social changes. We can only be certain of one thing: we certainly live in the age of information.

Tomasz Brzozowski - Author

Tomasz is a team manager at Codelab with an extensive in software development and project management. He has extensive experience in managing teams for industrial development projects, leveraging his expertise in cutting-edge technology to deliver successful outcomes for clients. With a curious and analytical mind, Tomasz is always on the lookout for emerging trends and enjoys sharing his insights through writing. Outside of work, he values time with his family and stays current on the latest technology through gaming and other interests.

Mads Carstensen - Consulting, text revision, additional research:

Mads is the Marketing Manager at Codelab responsible for all sales related marketing activities. Since he was a child he has been fascinated by IT and the English language. After having spent a year abroad in Northamptonshire, UK, Mads began his career in marketing in Berlin in 2009 at a prominent start-up in Berlin. He has since been honing his marketing skills in the IT and industrial fields. When he's not working, Mads enjoys going to concerts and spending time fiddling with computer parts, DAWs, DJ controllers or guitars.

About Codelab

Codelab is a valued partner for software development and digitalization for companies in the automotive, industrial, and enterprise sectors. The core business of Codelab focuses on services and solutions in the realm of embedded systems, IoT, full-stack development, and consulting. The 250 employees are located in Berlin and two technology centers in Szczecin and Wroclaw. Codelab is a subsidiary of the publicly-traded Beta Systems Software AG and has been operating in over 40 countries for 35 years.

Find out more about how we are helping businesses tackle digitalization and development bottlenecks at www.codelab.eu.

Any remarks, suggestions, thoughts, feedback or corrections can be sent to [email protected].

This article was first published on the Codelab Blog on : The Impact of Intelligent Automation on Global Data Storage and the Workforce.

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