Data is the reason AV companies are racking up miles and miles of testing experience on public roads, recording and stockpiling petabytes of road lore. Waymo, for example, claimed in July more than 10 million miles in the real world and 10 billion miles in simulation. But here's yet another question the industry does not like to ask: Assume that AV companies have already collected petabytes or even exabytes of data on real roads. How much of that dataset has been labeled? Perhaps more important, how accurate is the data that's been annotated?

ANSYS (NASDAQ: ANSS) is collaborating with Edge Case Research to engineer the next generation of autonomous vehicles (AV) with unmatched state-of-the-art hazard detection capabilities. Through a new OEM agreement, Edge Case Research integrates its powerful AV artificial intelligence (AI) perception stress testing and risk analysis system, Hologram, within ANSYS' comprehensive AV simulation solution -- delivering a solution to maximize the safety of AVs. Today's AVs rely on AI perception algorithms that are trained to make safety-critical driving decisions. Though highly advanced, an AV may fail to detect hazardous driving scenarios known as "edge cases" -- because its algorithmic training has not prepared it for the many unusual road situations it will encounter in the real world. To ensure the highest safety of an AV -- and make fully autonomous vehicles a reality, developers need tools to automatically identify these challenging edge cases in a way that is far more scalable than manual data labeling.

"Self-driving cars are here," Dmitri Dolgov told the audience at MIT Technology Review's EmTech Digital event this week. It's a matter of how fast we can grow and how fast we can scale this technology in a responsible manner." Waymo's CTO is right: The outfit that started off as Google's self-driving car project is running a limited robotaxi service in the Phoenix metro area. Dolgov also told the audience that the company has tech yet to crack.) GM Cruise plans to launch a service this year. Uber is testing in Pittsburgh. Lyft and Aptiv have a limited self-driving service in Las Vegas. Nuro's delivery bots are hauling groceries around Texas and Arizona. May Mobility is running robo-shuttles in Detroit. So for the public sharing the roads with these things, a few long lurking questions are now more pressing than ever: How do we know these things are safe? And how can the companies that promise they are prove it to us? One thing is for sure: The way we certify human drivers ain't going ...

For the people who develop self-driving cars--the software engineers, the hardware tinkerers, the welders and the bumper-affixers, the C-Suite execs and the marketing folks paid to sell it all--the rest of the world is bit like like a kid-crowded backseat. Are we there yet? the globe asks. Sometimes, the public is excited, because autonomous vehicles promise to, perhaps, one day banish dangerous drunk, drowsy, and distracted drivers in favor of precise machines. Sometimes, the public is fearful, because loosing new technology on public streets can be frightening. Just last month, a self-driving Uber testing in the Phoenix metro area struck and killed a woman as she crossed the street.

For all its heat, the fire that is Uber in 2017 hasn't scorched everything. While the nigh-apocalyptic past six months have felled founder and CEO Travis Kalanick, and sparked questions about its ability to keep its employees safe, let alone happy, Uber's self-driving car program seems to be doing just fine. It's a rare but vital bit of good news for Uber, for which autonomy is an existential question. If another company figures out how to operate a taxi service without paying drivers and Uber cannot, it's lights out, unicorn. "What would happen if we weren't a part of that future? Kalanick told Business Insider last year. "Then the future passes us by." Now, Uber's self-driving program hasn't been unscathed. It faces a vicious lawsuit from Waymo, Google's self-driving car spinoff, which accuses it of using stolen IP to advance its autonomy research. Last month, Uber fired Anthony Levandowski, its self-driving car lead who allegedly brought that IP over from Google.