It is not the best of times for self-driving car startups.
What makes Waabi qualified for such support?
Those are two key challenges of the self-driving car industry and are mentioned numerous times in the release.
What Waabi describes as its next generation of self-driving technology has yet to pass the test of time.
But its execution plan provides hints at what directions the self-driving car industry could be headed.
Real-road training is costly both in terms of logistics and human resources.
It is also fraught with legal challenges as the laws surrounding self-driving car tests vary in different jurisdictions.
These mounting challenges speak to the limits of current self-driving car technology.
I reached out to Waabi for more details and will update this post if I hear back from them.
The benefit of having a software-heavy stack is the very low costs of updating the technology.
The combination of deep learning, probabilistic reasoning, and complex optimization is interesting, albeit not a breakthrough.
Most deep learning systems use non-probabilistic inference.
End-to-end trainable machine learning models require no manual-engineered features.
Most deep learning models are end-to-end trainable.
Some of the more complicated architectures require a combination of hand-engineered features and knowledge along with trainable components.
Finally, interpretability and reasoning are two of the key challenges of deep learning.
Deep neural networks are composed of millions and billions of parameters.
The closed-loop simulation environment is a replacement for sending real cars on real roads.
Inan interview with The Verge, Urtasun said that Waabi can test the entire system in simulation.
Im a bit on the fence on the simulation component.
Most self-driving car companies are using simulations as part of the training regime of their deep learning models.
Urtasans name appears on many papers about autonomous driving.
But one, in particular, uploaded on the arXiv preprint server in January, is interesting.
Urtasun posted a video on her YouTube that provides a brief explanation of how MP3 works.
Theres also a sizeable gap between academic AI research and applied AI.
Self-driving trucks can transport cargo between cities, while human drivers take care of delivery inside cities.
Waabi also doesnt make any mention of a timeline in the press release.
This also seems to reflect the failures of the self-driving car industry in the past few years.
None of those deadlines have been met.
you’re able to read the original articlehere.
