The world is changing, and the rate of change is only increasing. At eight years old I remember playing my very first computer game, simple pixels that moved around the screen. I never could have believed that 28 years later I would be involved in building next generation cloud systems, including a cloud DNA analysis solution that has cut law-enforcement crime-scene DNA analysis from two days to just 90 minutes, or building an encrypted cloud communications platform to assist teams evacuating foreign nationals at the height of the Arab Spring.
The Digital Revolution ushered in incredible changes, a lot of which we couldn’t have imagined. From powering the moon landings in 1969, to enabling instant, real-time communication across 4,000 miles with the click of a mouse and tap of a keyboard, thanks to the invention of the Internet.
But instead of seeing this new technology as an untold opportunity, many people feared it. They had an inherent distrust of a technology they didn’t fully understand, and they certainly couldn’t comprehend the potential positive impact it could have on their lives.
Fast forward to 2019 and we are now at the start of the next industrial revolution — the 4th since it all kicked off in Georgian times. We’ve come a long way since the birth of factories and the dawn of the steam engine — we’re now blurring the lines between physical, digital and biological technologies. But we’re still seeing many of the same anxieties and suspicions today that existed during the 18th and 19th century transformations.
Back then it was textile workers fearing the introduction of automated textile manufacturing, whereas now autonomous cars, drones, robots — previously the domain of science fiction — conjure up terrifying images of James Cameron’s Terminator, where intelligent robots are out to destroy the human race. Or even worse, steal our jobs!
However, the reality is that cloud, AI and cyber-physical technologies are in fact solving some of the greatest and most valuable challenges faced by the human race. Deep learning algorithms can now detect potential breast cancer tumours from a mammogram with a 97% accuracy and reduce unnecessary biopsies by 30%¹. Technologies such as DeepMind’s AlphaFold are using deep learning and neural networks to solve the ‘Protein Folding Problem’ and help find a cure for diseases such as Alzheimer’s, Parkinson’s, Huntington’s and Cystic Fibrosis². And it’s not just in the medical field — automation, AI and cyber physical systems are helping us across every industry from business, manufacturing, education, transport and the environment.
Yes, automation will ultimately reshape our labour markets, but historical analysis shows that more jobs are created around these new industries than are lost due to new technologies. However, it’s not the number of jobs available, which are the concern. Rather, whether the workforce has the technological ability to do them — the reality is that as the labour market evolves, many are left behind. While this used to only apply to low-skilled jobs being automated away, the truth is that this now applies across all industries — even ones previously considered high-skilled.
Take the IT industry itself — historically the domain of highly-skilled IT engineers used to building complex physical IT systems. With the dawn of the cloud and the emergence of AI, Big Data and elastically scalable systems distributed across the globe, it’s no longer enough to be an IT Infrastructure Engineer that can build out a physical server infrastructure in a data centre. Modern IT engineers now have to have an understanding of thousands of cloud resources, and know how they go together across multiple cloud providers. Once they have designed a cloud solution from the list of cloud resources, they must then convert this to software code so it can be deployed into the cloud environment of choice.
The reality? There are very few cloud engineers in the IT industry capable of doing this³. This leaves businesses with a huge skills headache⁴ — the very best engineers command the highest salaries but are hard to find and there’s not enough of them to deliver the demand for cloud. And for those who can’t adapt their skills to the cloud, write code and deploy complex solutions, the future is bleak.
The risk of technological change is that we end up in a two-tier world — those with the knowledge, ability and means to access and benefit from the 4th industrial revolution, and those that are left behind. But it doesn’t have to be this way, and in fact the very thing that threatens to disenfranchise so many, has the ability to enable us all. If the power of the cloud, AI and cyber-physical systems can be used to augment our existing skills and capabilities, we can empower everyone.
For instance, imagine a world where the IT engineer can utilise their existing skills, and AI can translate the language of a traditional engineer into the language of the cloud. Or where AI can guide the engineer to a validated cloud solution design and help them create a functional cloud architecture diagram. What if an AI powered translation engine could automatically translate the design to code on any cloud? Imagine a world where the engineer only needs to press a button and AI will do the heavy lifting, deploying the complex cloud solution automatically.
At Cloud Maker we’re not just imagining this world, we’re making it a reality. Our vision is to contribute to a world where assistive AI enables the human race to do more, closing the skills chasm and democratising the cloud for everyone.
If you’re interested in coming on this journey with us, visit us at cloudmaker.ai
: MIT News. Adam Conner-Simons (October 16, 2017)
: DeepMind AlphaFold: Using AI for scientific discovery
: RightScale 2018 State of the Cloud Report
: OpsRamp Cloud Skills Survey