Entering The Era Of Intelligent Devices
The next leap forward will see a multitude of intelligent and connected devices complementing human intelligence to augment industrial production
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We are at the threshold of Industry 4.0. The past decade has seen extensive economic, social and technological changes driven by the digital revolution. We are about to enter the next phase of unprecedented transformation.
Rapid increase in computing power, coupled with the convergence of emergent technologies such as IoT, 5G, Cloud and Edge computing is bolstering businesses by integrating physical production with information and communication technologies. The next leap forward will see a multitude of intelligent, connected devices driven by data and Artificial Intelligence, complementing and aiding human intelligence to augment industrial production. Deployment of customized robots in manufacturing is on the rise. In 2016 China, South Korea and Japan supplied 167000 units of industrial robots worldwide.
This wave of exponential technologies is creating new opportunities in industry. The global artificial market intelligence market size was USD 20.67 billion in 2018 and is projected to reach USD 202.57 billion by 2026- a CAGR of 33.1%.
AI has evolved rapidly in recent years from an experimental technology to a deployable one. It is now ready to deliver step-change benefits and true value to businesses by offering greater efficiency, considerable commercial advantages, and ultimately, a better customer experience. Understanding the potential and impact of these technologies will be a fundamental leadership requirement to stay competitive. In a KPMG survey, 50 per cent respondents said they expect to be using AI/Machine Learning at scale within the next three years.
Greater processing power
The AI revolution has been advanced largely by the exponential progress of technology. Continuing advances in semiconductor technology and the shrinking size of transistors within processors have given us immense processing power, making it possible to apply complex AI algorithms to data. In 2018, OpenAI found that the amount of computational power used to train the largest AI models had doubled every 3.4 months since 2012. Newer architectures and AI-specific microprocessors enable faster AI calculations and are proving to be highly efficient for training neural networks at the Edge or in the Cloud.
The convergence of IoT and AI would not have been possible without an enabling platform. Cloud and Edge computing provide an environment that supports deep learning, neural networks and computer vision algorithms. The hybrid cloud is a convergence of the Edge and Cloud layers, allowing distributed computing. Cloud computing services are backed by 'Analytics as a Service' offerings and allow users to quickly develop and run AI applications.
The Edge, located where data is collected, combined with the cloud, creates the Edge-Cloud hybrid, ideally suited to organizations that have a unique technology landscape. The hybrid Cloud is both a disruptive technology and a business opportunity at the same time and is being harnessed to train AI models in the Cloud while delivering ubiquitous AI at the Edge.
Data has been the other big influencer. Over the past decade data volumes have increased by several orders of magnitude. Connected devices, smart objects, wearables and human response produce large amounts of data every minute. According to research done by Raconteur, we are likely to reach 463 exabytes of data produced daily by 2025. This volume of data is not only good input for AI, it is also an opportunity.
Artificial Intelligence has a broad range of applications across diverse verticals such as Energy, Healthcare, Logistics, Financial Services, and areas such as product and process engineering, production management and marketing. Predictive AI is improving plant utilization by anticipating demand and matching production. Outages are being minimized by predicting faults.
Proliferation of Intelligent Technologies
Pushed by global competition, businesses have been compelled to remodel conventional operating processes. Smart manufacturing is employing robotics, automation, wireless technology, intelligent devices and sensors to optimize production and stay competitive. Intelligent devices and AI technologies are being increasingly operationalized in industry. According to a survey by ESG research, 45 per cent of respondents expect to see value from their AI/ML initiatives in less than six months.
While it has become imperative to adopt AI, it is often difficult for businesses to choose and deploy the right solutions. Thirty-five per cent of respondents to an ESG survey cited the cost of IT infrastructure as their biggest hurdle, while 29 per cent cited IT capabilities.
AI is driving aggressive innovation and revolutionizing the way we do and think about business. Intelligent devices, the hybrid Cloud and a host of other emerging technologies are challenging existing business value propositions. Going forward, organizations will need to redefine their business models to stay in step.
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