 The term algorithm is currently making a massive rise to fame. An ancient Greek term that was previously confined to the world of mathematics and software engineering is making its way into the mainstream, as people are increasingly recognising the material impact on society that algorithms are having today. Algorithms that used to be buried away inside of computer program files that were used to find a derivative of a slope or to find the shortest path between two locations have today expanded to affect almost all areas of human activity. Algorithms for determining the value of a basketball player based upon a computerised analysis of their performance last season. Algorithms that analyse the incoming customer service calls and route them to the most appropriate agent. Algorithms determining the likelihood of a convict reoffending. They are analysing insurance claims for coordinating the nightly maintenance on a mass transit system for driving cars, identifying symptoms. Algorithms to determine which candidate a company should hire, who should be recommended as a friend on social media, or what films, books or music someone would like. And of course algorithms have taken over financial markets, now making up 70% of trades as stock markets have become layers upon layers of algorithms. An algorithm is a set of instructions for performing a certain operation. An algorithmic system takes an input and transforms it through a set of operations to create an output. Cooking a loaf of bread may be seen to follow an algorithm where we take in inputs such as flour, water, salt etc and perform a set of operations on them such as mixing, kneading, baking etc to create an output which is the cook loaf of bread. Algorithms are almost as old as human civilisation itself. Euclid's algorithm being one of the first examples dating back some 2300 years. But what we're doing with them today is very different from what we did in the past, which was largely strict formal mathematical operations and limited statistical analysis. Algorithms are being transformed from the mechanistic linear forms of the past where we specified all the rules and hard coded them with the end result looking like cogs in a gearbox. Today, where algorithms take a more networked form, they're more self-organising as they learn from data. These new forms of algorithms take many different names, from cognitive systems to artificial intelligence to machine learning. Fei-Fei Li of Google Cloud describes some of the factors involved in this transformation. In 2010, around that time, thanks to the convergence of the maturing of statistical machine learning tools, the convergence of big data brought to us by the internet and the sensors, and the convergence of computing, the Moore's Law carried us to much better hardware. These three pillars came together and lifted AI from their in vitro stage to what I call their in vivo stage AI. In vivo, is where AI is making a real impact on the world, it's just the beginning. Every single industry is going through a transformation because of cloud, because of data, because of AI and machine learning, and this is what I see as the historical moment, but I also want to say that this is just the beginning. These advanced algorithms, unlike the static mechanistic models of the past, are adaptive in nature, they may learn as information changes, and as goals and requirements evolve, they may resolve ambiguity and tolerate unpredictability, they may be engineered to feed on dynamic data in real time or near real time, they are amenable to the processing of unstructured data, the processing of millions of parameters and complex patterns, such as speech recognition, sentiment analysis, face detection, risk assessment, fraud detection, behavior recommendations, or sentiment analysis. This means these advanced analytical methods are no longer confined to strict mathematical operations, but can handle more unstructured human like activities, such as many basic services. The idea of a computer is really just an abstract model for a system that stores and manipulates data according to a set of instructions called the algorithms. The implementation of this model can take many forms, we're used to thinking of it as the personal computer on our desktop, but with the rise of mobile computing, the internet and cloud computing, this computing is becoming pervasive, but also integrated through these cloud platforms. Cloud computing platforms have been a key innovation over the past decades, although a relatively straightforward idea of centralizing computer resources in a data center and then delivering them as a service over a network, the outcomes of doing this though are extremely impactful. These new forms of advanced algorithmic methods that we'll discuss in coming modules are very compute intensive, the demand for computational resources does not scale linearly with the size of the data, but scales quadratically or cubically with the size of the data being operated on, and when you're talking about billions of data points that causes new computational problems and we need new computing platforms to mitigate it. Throughout human history, computing power was a scarce resource, and until the past few years, high-end computer processing and storage offerings were out of the reach of all except the largest organizations and then at the cost of millions of dollars. However, with the advent of global hyperscale cloud computing, high-end computing is now available to organizations of almost all size at low cost and on demand. The arrays of billion-dollar scale data centers owned and operated by Amazon, Google and Microsoft are now at the fingertips of many. Many of the largest applications on the internet today run on this cloud computing infrastructure. Take for example Airbnb that now coordinates an average of half a million people's accommodation each night in 65,000 cities, with this platform running almost entirely on Amazon's web services cloud. Likewise, each month, Netflix delivers a billion hours of video streaming globally by running on Amazon cloud. Indeed, Amazon's web services is so widely used that when it doesn't work right, the entire internet's in jeopardy. A basic driver behind many of the recent disruptions in a wide range of industries is the transformation of computing resources from a scarce to an abundant resource. Combining cloud computing with advances in algorithms and mobile computing, we get machine learning platforms that are able to coordinate and run ever larger and more complex service systems. This allows an increasing swath of human activity to be captured by algorithms, which allows it to be split apart, transformed, altered, recombined and automated. These platforms bring about an ever-growing integration between technology and services as data and information processing become more pervasive and computation becomes embedded with virtually all systems. Traditional divides are going to become ever more blurred, information technology and socioeconomic organization will become ever more integrated and inseparable. As the saying goes, every company will become a technology company, and this will fundamentally change the structure and nature of these organizations. What is happening today is the convergence of these cloud computing platforms, new algorithms and the rise of the services economy. In years, have seen the emergence of physical products that are digitally networked with other products and with information systems to enable the creation of smart service systems which are coordinated via algorithms. What is happening as we move into the services economy is that products become commoditized. People stop wanting to own things. What they want is to be able to push a button on their smartphone and the thing delivered as a service, an app for food services, an app for transport services, an app for accommodation etc. and of course all of these services are delivered on demand via a cloud platform which is coordinated via advanced analytics. Services are not like products, whereas products are mass produced. Services have to be personalized. Products were static once-off purchases. Services are processes. Products were all about things. Services are about functionality and value. Service systems are all about the coordination of different components around the end user specific needs. To do that you need lots of data about the user. You need advanced analytics and cloud computing. We can already see the data-driven services organization in the form of Uber, Alibaba or DD which don't own anything, they just use data and advanced analytics within their platforms to coordinate resources towards delivering a service. Service companies like DD would be impossible without data. Dematerialization is one of the key aspects of the information age. Material products become commoditized. Data and information are used to strip physical technologies down to their most basic material requirements. Value added shifts to the organization of systems rather than the production and ownership of physical assets. This is seen with the rise of platforms over the past decades, which are really large networks that use data and analytics to optimize systems. As the venture capitalist, Steve Jefferson put it, in the past, the thing mattered. Now it's all about the software and services there. Reduce the physical thing to its minimalist thing for a container for software and code and that's what's happening in more and more products and services. The thing that every business makes is becoming a software product. In the long run, everything will cost a dollar a pound for things and what people will pay for and value is the software and services that come around it. It's what makes every product magic. I think what you're seeing as common practice in the IT centric industries of today in software and computers. What was the telecom transition of years past will be the case for every industry. The key question is when and in what sequence. Some like agriculture and healthcare are in the middle or early phases of that transition but every industry will inevitably compete on how they process information. That's how they'll win or lose and the transition will not be easy for some. What will differentiate one company from another is not how fancy their product is but how seamless and integrated their service system is and this is done through their capacity to master data and analytics. Organisations will become platforms and will compete based on their intelligence which will be contained in their algorithms and people. In short, the physical technologies of the industrial age are being converted into services and connected to cloud platforms where an advanced analytics coordinate them. As Matt Turk of First Mar puts it succinctly, everything becomes data, your physical activities, traffic, purchases and the data gets moved to the cloud but it gets processed and compared with other devices. It's no longer just what you do but what everyone else also does which keeps making the system smarter and smarter. This is the essence of the process we're going through today. Datification, converting everything into data, cloud platforms for aggregating and running the machine learning for processing it and iterating on that. Through serviceisation and dematerialisation, organisations become differentiated based on their data and algorithms as algorithmic systems extend to coordinate more and more spheres of human activity and we move further into this unknown world of the information age.