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AI and Connected Cars 3.15 MB Forget the Sci-Fi and Embrace STRATEGIES the Engineering #connectedcar AI in Automotive Adaptivity, connectivity and artificial intelligence Adaptivity, connectivity and artificial intelligence Many auto-manufacturers have already made extensive use of AI and invested in machine learning for connected Many auto-manufacturers have already made extensive use of AI and invested in machine learning for connected cars and autonomous driving. cars and autonomous driving. However the race is on to make the smartest vehicle technology IN 30 SECONDS However the race is on to make the smartest vehicle technology • Today we can design systems to Situation respond to unplanned yet known The automotive industry is transforming as data and events, but humans struggle to cope connectivity bring new with the challenges provided by opportunities for using AI in completely unexpected situations infotainment, self-driving cars and learning from vehicle data Solutions • Understand the kinds of AI • OEMs need to find the right prob- tools and techniques, know lems to solve and the right types of Complications what kinds of data and services and what specialist AI is in its early stages of AI to solve them expertise is required development and there are a plethora of solutions doing • Find the right problems to • Understanding how data and AI dierent things. AI also means solve and pair them with the can be used will help you to differ- dierent things to dierent right kinds of AI entiate your business people • Find opportunities to use AI internally and in customer- facing products and services • Set expectations: be prepared to Challenges to innovate with AI to fail - and to succeed - in unexpected Dierent kinds of AI with leapfrog the competition dierent applicabilities, ways idiosyncrasies, strengths and weaknesses, and when AI doesn’t deliver expectations and illusions are shattered Source: BearingPoint Institute Introduction Advances in computer power and the development of machine 2 umanity has been fascinated by learning offer huge potential for automation, prediction, and Hartificial intelligence since it has generation of insights from patterns in the data that humans been able to conceive of the idea. An fail to see. Ancient Greek myth imagined “Talos”, a STRATEGIES #connectedcar giant bronze automaton, built to protect the Cretan town of Europa from pirates. Wolfgang von Kempelen built “The Turk” Introduction in the 1700s, which he claimed was a But can we build machines that will deal Applications for the automotive sector mechanical man able to play chess. It with unexpected circumstances? You are exciting. Market research specialist Automotive AI in practice could indeed play chess – and win – but can design a system to respond to a Gartner now expects there to be 250 there was a real man hiding inside. number of unplanned yet known events million connected cars on the road by that might arise, but to cope with the 2020. Those connected cars will be Barriers to AI adoption Today we have chat bots we can talk completely unexpected is a challenge generating a high volume of data that to, robots that are taught by engineers many humans struggle with. Fully will be used to generate insights into Ambition with reality to build cars, and cars that can drive autonomous cars will come in time, but customer behavior; insights that can themselves (to some degree). But much work has to be done before they inform new product design, as well as while you can ask Alexa, Siri, Cortana, Conclusion can safely be put into situations that improvements and add-ons that can be Google Assistant, and other digital cannot be controlled. provided as part of Software Over The Academic perspective agents questions - or tell them to Air (SOTA) updates. Forrester Research control your lights or heating - try to We have come on in leaps and predicts “Artificial intelligence will drive Key takeaways hold a conversation with them and bounds, but we must be able to trust the insights revolution”2 and that “those most autonomous chat bots are lost for autonomous vehicles with our lives. So, that are truly insights-driven businesses words. About the author while to some it is magical and mystical will steal $1.2 trillion per annum from that machines can do such things, we Still, while we are a long way from their less-informed peers by 2020”. need to understand the technology we building anything that would be Notes and bibliography are dealing with: there is no room for As well as generating insights for what mistaken for human intelligence, we do admiring the magic – this is engineering, products to create, at least one attempt have versatile automated machines, pure and simple. has been made to “grow the actual not least in the automotive sector. product” by creating an autonomous car Navigation systems can learn your Advances range from a leap forward in based on a neural net that learned how preferred route. Cars can automatically computer power to the development of to drive by “observing” human driving respond to the environment through machine learning, in which big data can behavior3. mechanisms such as adaptive cruise be used to train neural nets and deep- control, where automobiles travel at learning, cognitive algorithms. These In fact, AI in automotive is just one the required speed but slow down if the offer huge potential for automation, part of a technology revolution with vehicle in front gets too close; some will prediction, and generation of insights the potential to transform the world in even overtake to maintain the desired from patterns in the data that humans which we live, changing the nature of speed. fail to see. our societies. As Gerlind Wisskirchen, vice-chair for multinationals at the As one might expect, there is fear relating to AI, from both 3 International Bar Association Global Employment Institute has explained, safety and work perspectives. “Jobs at all levels in society presently undertaken by humans are at risk of being reassigned to robots or AI, and STRATEGIES #connectedcar the legislation once in place to ‘protect the rights of human workers’ may be no longer fit for purpose”. Introduction It may even be that legislation is Automotive AI A second application of AI is the Automotive AI in practice required to ensure human beings get creation of new insights from big data: their “fair share of jobs”, alongside the in practice automotive manufactures source huge robots. Automation and AI can reduce The automotive sector is already making volumes of data from vehicles on the Barriers to AI adoption costs and improve productivity, boosting extensive use of AI technologies, with 7 road that it is difficult for humans the competitiveness of industries and million systems installed in vehicles by to comprehend. The connected car Ambition with reality economies, but there will be downsides 2015 (according to IHS Technology). As can provide a constant stream of to manage, including the prospect of communication networks improve, this information about how and where it is Conclusion widespread unemployment. number will increase rapidly, as extra being driven, and how it is performing. bandwidth becomes available from 4G Machine learning provides a powerful Academic perspective Moreover, amid the excitement, tool in the ongoing struggle to see the pragmatism is required. and 5G technologies as well as advances in Software Over The Air (SOTA). patterns within the data and to make Key takeaways As one might expect, there is fear sense of it. relating to AI, from both safety and work Many of these systems are dedicated to delivering infotainment and driver Manufacturers such as BMW have About the author perspectives. The reality of AI capability already begun using this data in new today, however, is nowhere near that interaction services, from smarter traffic and mapping services to voice and ways. One early application is predictive Notes and bibliography described in sci-fi novels. The potential gesture recognition, built on natural maintenance – the ability to anticipate for human-machine partnerships far faults at very early stages so they can outweighs the likelihood that people’s language processing capabilities and pre-trained neural-nets. GM, be corrected before breakdowns occur, jobs will be taken by machines. In the reducing cost and inconvenience. automotive sector, the challenge is to for example, is working with IBM to find AI applications that work, both incorporate its Watson AI technology, Increasingly, manufacturers are also technically and commercially. It’s easy made famous in 2011 by beating two incorporating data and analytics tools to get carried away by the potential former winners of the US TV show into their production technologies, for AI in connected cars, but imagining Jeopardy in a head-to-head version of using the insights gleaned from in-car the future is the stuff of science fiction the quiz (and winning $1m as a reward). data to power next-generation design – in realizing this vision, automotive IBM Watson will be built into GM’s in-car and engineering. For example, the Los manufacturers face engineering “cognitive mobility platforms”; these will Angeles-based start-up Hack Rod aims challenges. essentially be digital assistants capable to create the first ever car engineered of following drivers’ instructions and with AI that has been designed in a anticipating their needs. virtual environment. Then there is the essential role of Increasingly, manufacturers are also incorporating data and 4 AI in powering the advanced driver- assistance systems (ADAS) that will analytics tools into their production technologies, using the eventually turn fully autonomous insights gleaned from in-car data to power next-generation vehicles into a mainstream reality. ADAS design and engineering. incorporates tools such as camera-based STRATEGIES #connectedcar machine vision systems and radar- based detection units, but is ultimately powered by intelligent software capable Introduction of making instantaneous decisions on the basis of the complex information set Automotive AI in practice with which it is presented.
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