For quite some time now, computers have been taking over automobiles. Sure, there are thousands of physical parts that make up a modern auto, but many of those parts are controlled by computers. This could be why the definition of “gearhead” has morphed to mean “a person who is very interested in mechanical or technical things (such as cars or computers).” But I digress.
A couple of years ago, IEEE Spectrum wrote a fascinating article called “How Software is Eating the Car,” focused on the shift to self-driving and electric cars. The article surfaced a few facts that really stood out to me:
- About ten years ago, only premium cars contained 100 microprocessor-based electronic control units (ECUs) networked throughout the body of a car, executing 100 million lines of code or more.
- Today, pick-up trucks like Ford’s F-150 top 150 million lines of code.
- Consulting firm Deloitte Touche Tohmatsu Limited estimates that by 2030, about 50% of the cost of a new car will be attributed to semiconductor-based electronic systems.
The increased pace for the need of technology within cars puts tremendous pressure on automakers to deliver not only safe vehicles, but ones that are fun to drive or have advanced features that are now expected by consumers.
Data-Driven or Driven Data?
All that technology that is crammed into cars is, of course, reliant on data and a producer of data – by some estimates, that can be about 25 gigabytes of data per hour! But what type of data are we talking about?
- Think about the music you listen to or directions to where you want to go, or connecting your phone, all displayed on the infotainment system. The data captured can be things like your contacts list or text messages from your phone or routes to your favorite places.
- Most cars today have driving sensors located all over the vehicle. For example, there are sensors for cars nearby as you are driving and want to change lanes. There are backup sensors. Event sensors for when you press the brake or turn the wheel – all of which are capturing data.
- Something that has been in cars for quite some time is diagnostic data that monitors engine performance or battery power or indicates issues within the vehicle.
- With newer cars, we are seeing an increase in another type of data, biometric data. There are sensors (again) that are programmed to check on the driver for impairment, keeping their eyes on the road, hands on the steering wheel, or maybe accessing the vehicle itself.
So, you are driving a connected and integrated database on wheels that is providing you with a new driving experience.
Copiloting AI in the Auto Industry
The massive amounts of data that cars produce is a gold mine for AI and large language models in our AI-powered era. This means that automakers are taking advantage of both data and AI to redefine two key areas: how they operate and what’s next for automobiles.
One such company is Honda. For its internal teams and operations, Honda is bringing Microsoft Copilot into the mix alongside its use of Microsoft (Office) 365. Led by Bob Brizendine, American Honda Vice President IT and CIO, the effort to infuse Copilot into day-to-day work.
“It’s really taken root and is being adopted,” Brizendine said in an article by CIO Dive. “There are some areas of the business [that] are more inclined to use this type of analysis, such as marketing people, product quality people and those in analytics, but we’re really seeing a pretty uniform adoption by everyone.”
He went on to add, “We’ve been very, very clear in our messaging that this technology should enable us to take on new challenges with the staff that we have today. We’re going to keep the human in the loop on AI.”
While that is happening on the internal side of the organization, Honda is actively pursuing AI within the car. In a multi-company collaboration between Sony Honda Mobility and Microsoft, generative AI will a central part of the future
According to Izumi Kawanishi, Representative Director, President and COO, Sony Honda Mobility, “AI plays an essential role in achieving our goal to redefining the relationship between people and mobility, enhancing emotional user experience.”
Now, I’m reading between the lines based on the coverage and goals outlined and based on the current use cases of Copilot across Microsoft Business Applications. Meaning, I can foresee Copilot helping copilot vehicles as a driving aid, enhance the in-car entertainment, and provide the interactions between the car and the driver.
On top of all this, Microsoft has created an autonomous vehicle operations (AVOps) reference architecture for developers. According to Microsoft, this “provides an integrated, end-to-end workflow for developing, verifying, and improving ADAS and autonomous vehicles (AVs).”
The intent of AVOps is to provide a “digital testbed” to help “shorten the time to market” and “optimize operational ADAS and AV workflow coordination and feature development, verification, and validation through:
- DataOps: From edge to cloud, the orchestration of petabytes of data to support parallel workstreams.
- DevOps: Scaling the continuous integration (CI) and continuous delivery (CD) pipeline.
- MLOps: Scaling machine learning pipelines and integrating with CI and CD pipelines.
- ValidationOps: The ability to accurately simulate software and AI updates across all edge cases.”
Closing Thoughts
Something that jumped out in the AVOPs information is the Microsoft intends to “help our automotive customers transform themselves into software and AI companies.” We have seen this shift across many industries. So, it’s no surprise that this is happening in the auto industry.
The Honda and Microsoft partnership truly emphasizes this transformation as Copilot and generative AI are brought to the forefront internally and externally as a driver of innovation. It will be fascinating to see how Honda augments humans in the flow of work and augments the driving experience for the future.
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