> Tor Svensson, Chairman CFI.co:
AI Convergence in 4IR Artificial intelligence (AI) and machine learning are gaining a strong foothold across numerous applications, lowering the barriers to the use and availability of data (figure 1). From now on, AI will not only be relevant to just a few large corporations but will form an integral part of most business strategies and is likely to influence our daily lives in more ways than we may recognise (figure 2).
N
ew cloud-based and AI-enhanced enterprise-as-a-service software requires less expertise and lower upfront investment. Companies no longer need to develop their own applications and end users do not need to gain extra knowledge or learn a new interface as AI runs in the background (figure 3).
CFI.co Columnist
As an emerging technology, AI is taking hold as virtual assistants, chatbots, deep learning (see below) autonomous systems (e.g. selfdriving cars), and natural language processing. AI innovation and sophistication is on an exponential growth curve. AI promises a new cognitive partnership between man and machine. From assisted intelligence, the future holds new forms of augmented intelligence and autonomous intelligence. Automation based on robotics and machine learning facilitates functional (and sophisticated) jobs today. Tomorrow, the opportunities will arise from artificial augmentation and the Internet-of-Things powered by 5G connectivity. This is not about single technologies but the convergence of many cognitive enterprise systems all inter-connecting with AI and exponential data at the centre. DIFFERENCE TO MACHINE LEARNING One definition of AI is intelligence demonstrated by machines as opposed to natural intelligence by humans. Thus, AI is the science of engineering
intelligent machines. AI research identifies three types of systems: 1. Analytical (with cognitive learning and decision making) 2. Human-inspired (as above plus emotions) 3. Humanised artificial intelligence (as above plus self-consciousness and self-awareness) AI and machine learning are often used interchangeably. Yet, machine learning can be defined as systems learning and improving (as in ‘Analytical’ above). Thus, machine learning is a specific subset of AI that excludes emotions, self-consciousness and self-awareness – and also human (DNA hardwired) dimensions such as ethics and morals. AI is not confined to biologically observable approaches only. Whilst the world has been able to construct machine learning systems, it still has fallen short of ‘broader’ AI with human aspects as mentioned above. DEEP NEURAL NETWORKS AI and machine learning comprise deep-learning neural networks. Here, ‘deep’ simply means more sophisticated neural networks that have multiple layers which interconnect. Neural networks include new performance offerings with current relevance such as: • Computer vision (e.g. face recognition and visuals for cars) • Natural language processing • Big data predictions and analytics
"AI innovation and sophistication is on an exponential growth curve. AI promises a new cognitive partnership between man and machine." 22
CFI.co | Capital Finance International