7 prompts drive autonomous vehicles and machine learning skill sets
A driverless car moves smoothly through morning rush hour traffic. Its occupants are relaxed. They’re checking their email, listening to music, or catching up on their favorite television shows. It sounds like science fiction, but for lots of companies – not just in the auto industry – it will soon be reality: the dream of autonomous driving. Already today, driving assist systems increasingly support the performance of multiple driving tasks. They park our cars for us, keep us a safe distance from the vehicle in front, signal to other cars our whereabouts or change lanes automatically. According to many experts, just a few years from now we’ll be able to rely entirely on autonomous systems to drive along certain stretches of highway or maneuver into parking spaces.
Technological advancements coupled drastic price compression, researchers are investigating how cars using data from cameras and radar devices in place of drivers can be made safe. How will this impact the future of work and the talent necessary to accelerate in this tech-driven landscape? Right now software engineers are working on solutions ranging from mobile connecting workers to cloud applications to testing experimental autonomous technologies under real conditions on a test track. Several driving factors are exacerbating the talent gap in so much that employers, customers, and social trends impact the future of mobility.
Non-traditional prompts are driving workforce changes, all the while attempting to provide greater efficiency and cost-savings to employers operating models.
- Connected Autonomous Vehicles – quickly approaching is the daily use of the connected autonomous car that will provide ample transportation in an efficient manner to travelers all the while providing them music from their favorite genre and warming their coffee for the relaxed ride to work. This may provide less workforce stress in daily commutes.
- Artificial Intelligence – otherwise known as, AI has been utilized successfully in varies administrative functions that include call center, scheduling and payroll processing. Sophisticated algorithms supported by high speed connectivity will enable AI to advance from highly-repetitive tasks to more talent focused tasks such as scientific lab and research work.
- Machine Learning – robots teaching robots or robots replicating tasks are driving efficiency and effectiveness at exponential growth rates. This will enable performance to be consistent and measurable based on real-time analytics. Fanuc, one of the world’s largest industrial robot companies is developing capabilities to allow robots to learn simultaneously and in parallel from each other.
- Integrated Guiding Systems – Training via tech-driven virtual reality is providing productivity gains within the workforce while making the decision to choose humans over automation more appealing. According to Wallace Hopp, associate dean of learning design at University of Michigan, “productivity gains are the only avenue to boost economic growth overall.”
- Mobility Apps – linking work tasks with top talent performers to accelerate the delivery of goods and services to the marketplace will provide for comparative advantages to operational execution in meeting customer’s demands. Mobile Apps look to become an enhanced problem solving, analytics, monitoring and measurement technology tool to ensure work expectations are being achieved.
- Wearables – Through virtual reality, the headset for gaming may give way to the use of wearables for highly detailed electronic assembly, microscopic repairs in human tissue and become a standard piece of equipment for repair people in confined conditions.
- Conversational Interfaces – Voice interaction with computers is driving new applications for order taking, operational assistance, and home monitoring. Home automation provided by Amazon’s Echo or Google’s Nest allow for on-demand adjustment of lighting, energy consumption and security. Amazon believes in the near term that speech recognition will be advanced to detect signs of emotion in the voice.
Future moving, employers will have several strategic decisions to make as to human augmentation, fully-automated applications or a blended-model of workforce solutions to find repeatable efficiencies to performing necessary tasks and strengthen the company’s economic stability.
Have you seen any of these technological advancements in action, please share your experiences.