The Unlikely Chances Of AI Autonomous Car Makers Sharing Their Wares

By Lance Eliot, the AI Trends Insider
Some suggest that the makers of AI autonomous cars ought to share openly with each other and freely reveal their proprietary wares, doing so to enable heightened progress in achieving true self-driving cars and presumably therefore obviating the 40,000 car crash related deaths each year in the United States alone and an estimated 1.3 million or more fatalities that occur worldwide annually via car accidents.
The sooner autonomous cars are put onto our roads, the sooner it is said that we will start saving precious lives and reducing car crash induced injuries.
In a kind of presumed kumbaya moment, akin to at wartime having everyone suddenly lay down their arms, wouldn’t it be wonderful if the automakers and self-driving tech firms would divulge everything that they know and are arduously doing toward creating a self-driving car, and then the resulting synergy of this massive “open source” approach might speed-up the process?
The point being that today there is an existent winner-beats-all mindset, of which each automaker is striving on their own to craft a true autonomous car, but wouldn’t we all be winners as a society if the automakers just opened-up the kimono and bared all for everyone else to see their self-driving car efforts.
Presumably, they ought to showcase the proprietary algorithms that they’ve devised for self-driving capabilities and post their voluminous AI code in a public forum for all to peruse.
They ought to release the data that they’ve collected from their roadway trials, providing a treasure trove of data that could allow others to employ Machine Learning and Deep Learning to ferret out ways to best drive a car.
For those using simulations to do testing of their AI driving systems, they ought to allow others to log into the simulation and see what kinds of parameters and settings are being used, along with allowing anyone else to utilize the simulation for the furtherance of their driverless car tech.
Furthermore, one of the biggest hurdles in devising self-driving cars involves figuring out so-called edge cases, involving seemingly unusual or oddball driving circumstances and being able to prepare the AI driving system to cope with those situations.
Rather than each automaker having to figure out edge cases on their own, perhaps it would be best if a large-scale database of known edge cases was formulated and provided access to anyone interested. Think of how such a collective set would aid others that hadn’t yet discovered various edge cases and thus they would not have to reinvent the wheel, so to speak, and could simply refer to the open database instead.
In short, the assumption being that today’s rather fragmented and disjointed approach involving singular companies attempting to each develop AI-based self-driving cars could be turned on its head, allowing a grand collective of all such...