In his most recent book 21 Lessons for the 21st Century, the author Yuval Noah Harari adds his voice to other scientists and thinkers who identify Artificial Intelligence (AI) as one of the most important technological advances of our time, inviting us to reflect on the challenges that will face humanity in the near future.
The theory that serves as a foundation for AI dates back to 1950. However, only in recent decades has it gained a broader practical applicability with machine learning, and it is accelerating as convergent factors increase in scale: Increasing amount of available data, computing power and sophistication of algorithms and training methods.
The current wave of innovation in the field of AI does not really bring us intelligence, but a critical component of intelligence: prediction, argue the authors of Prediction Machines: The Simple Economics of Artificial Intelligence. Prediction is the process of filling in missing information. The prediction picks up the available information (data) and uses it to generate information that we do not have. Although it looks like magic, it’s just about data science and programming, and its practical application is already available in a lot of everyday situations. From protecting our credit card to detecting spam in our email. It is at the heart of services like those of Google or Facebook and of virtual assistants like Siri.
As we apply AI to more complex problems, the authors argue that the potential for disruption is enormous and they illustrate this with a case that may involve the deep transformation of a well-known company’s strategy. They propose: For example, if Amazon can accurately predict what buyers want, it can pivot from the current buy-after-shipping model to a shipping-after-purchase model, making us reach home products even before the terms are requested. This fundamental change could transfigure not only entire business models but also the entire transport and logistics structure as we know it.
“If the blockchain could be the operating system where the future of logistics and mobility runs, AI will be the main tool, which promises to create numerous opportunities to improve operations, generate new sources of business and reduce costs.”
It is not by chance that the automotive industry, in this case, Daimler make one of its approaches to AI in the field of logistics in order to respond to the growth of e-commerce and door-to-door deliveries. Recently the team responsible for thinking about the future of transport in Mercedes-Benz Vans has launched a proof of concept in which it presents a new system of organisation and recognition of cargo. This equips the new Sprinter with a series of cameras that track orders automatically as they enter and leave the vehicle. Powered by computer vision and AI, the system identifies and records orders as they are brought into the vehicle and recommends the ideal storage position based on the size and final destination of the package. The system continuously monitors the load space along the route and tracks any changes to an order’s location. At each delivery point, the system automatically looks for the customer’s order and directs the driver to the package by means of LEDs installed on the shelves and throughout the cargo space, allowing for faster and more efficient operations.
However, the automobile industry’s initiatives in this field do not stop here. The growing tendency for a vehicle to cease to be a disconnected personal transport mode, to become a hyper-connected intelligent node in a complex mobility ecosystem, makes it absolutely necessary to explore the potential of AI, which is still in its infancy. It is exciting to be able to watch the appearance of the first intelligent personal assistants to support the driver, but the most interesting is yet to come. This technology will have application and will bring benefits to many areas of logistics and mobility, but we cannot fail to highlight the amazing technological leap that is the autonomous vehicle project. This is only possible because AI begins to allow the reliable recognition and mapping of objects around the vehicle and because machine learning is building predictive models based on the observation of our own real-life driving experience.
If the blockchain could be the operating system where the future of logistics and mobility runs, AI will be the main tool, which promises to create numerous opportunities to improve operations, generate new sources of business and reduce costs.
Reference:
Harari, Y.N. (2018). 21 Lessons for the 21st Century. Spiegel & Grau
Agrawal, A., Gans, J. and Goldfarb, A. (2018). Prediction Machines: The Simple Economics of Artificial Intelligence. Harvard Business Review Press
Mercedes-Benz Vans (2018). Introducing CoROS – The Future of Cargo Logistics. Available at: https://www.vans.mercedes-benz.com/us/en-us/future-transportation/coros [Accessed Nov. 2018]
** Opinion article originally published in Fleet Magazine paper and online edition /November 2018 **
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