An interesting post in the Chinese news reveals that GM just topped a driverless competition.
The Ningbo station’s route was extremely challenging. The biggest difference from previous competitions was that the route was completely hidden before the race, equivalent to a closed-book exam. The entire route spanned 29 kilometers, passing through 28 traffic lights, 5 waypoints, and 8 test points, examining the participating vehicles’ city NOA intelligent driving capabilities in traffic scenarios including narrow community roads, roundabouts, blind spot U-turns, artificial obstacles, U-turns, village roads, right-turn U-turns, and rural roads.
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According to the judging panel, the top three finishers in the Second Smart Driving Competition Ningbo Station City NOA Race were:
Champion: Buick GL7!
Second place: Yangwang U7!
Third place: Zeekr 9X
The GM story is actually that using Momenta’s R6 generation of autonomous driving AI is version 1.0, yet winning against Tesla latest version (13? 14?). The Buick gets the award, yet Momenta is the secret sauce doing the heavy lifting. I mean their new system shows why Tesla fell almost all the way out of the top ten, squeaking in a ninth place.
Traditional approaches wanted to copy human drivers. Reinforcement learning (RL) systems however, such as Momenta’s “Flywheel” platform, can potentially handle edge cases better than humans because they can be exposed to scenarios millions of times in simulation. Edge cases become expected and known. Rather than separate modules for perception, planning, and control (Tesla’s approach until recently), the Momenta RL also integrates everything into one neural network that learns holistically.
Here’s what all that meant in competition: At one test point—a basic protected U-turn that any beginner human should handle—nine vehicles required human takeover, including multiple premium Chinese EVs and the Tesla. The Buick GL7 sailed through. It had already “practiced” that exact scenario ten million times in simulation, learning not just what to do, but when hesitation creates danger and when aggression does.
It’s basically the exact opposite of Tesla.
As great as this sounds, we’re looking at the next frontier in automotive litigation. When an RL-powered vehicle crashes, the “why” isn’t in if-then rules you can read—it’s in billions of neural network weights shaped by reinforcement learning.
You can’t depose a neural network. You can’t cross-examine an algorithm that “learned” through trial-and-error in simulation. The traditional questions that expose Tesla as a fraud—”What did the system detect? When did it decide to brake? What rule did it follow?”—become meaningless when the decision-making process is a black box of interconnected weights.
The manufacturer will say: “Our system was trained on 3 billion kilometers of A and passed rigorous testing of B.” Your expert will need to ask: “Ok, but what reward function shaped its learning? Did it prioritize smooth rides over collision avoidance? Can you reconstruct why it made this specific decision?”
Blade Runner where are you? If the machine can’t explain itself, can it be trusted with safe operation? We need the Voight-Kampff test…
On top of its track performance, the new Buick GL7 costs just $25K—roughly half what a Tesla Model 3 with Full Self-Driving costs in China. Momenta achieves better performance at lower cost with an optimized sensor suite: 11 cameras, 1 radar, 1 LiDAR.
Not the fanciest hardware, but the smartest software.
This is the “good enough” disruption of great engineers playing out in real time. Tesla blew years and billions into a vertical integration that barely works. Momenta built a platform that any automaker can license, achieved far superior performance, and did it at low cost. Their version 1.0 just made every Tesla look like it runs version oh no.
Tesla built a mythology.
Momenta built a product.
Buick just dominated the track.