Google/Alphabet are so vertically integrated for AI when you think about it. Compare what they're doing - their own power generation , their own silicon, their own data centers, search Gmail YouTube Gemini workspace wallet, billions and billions of Android and Chromebook users, their ads everywhere, their browser everywhere, waymo, probably buy back Boston dynamics soon enough (they're recently partnered together), fusion research, drugs discovery.... and then look at ChatGPT's chatbot or grok's porn. Pales in comparison.
How do you know the generated outputs are correct? Especially for unusual circumstances?
Say the scenario is a patch of road is densely covered with 5 mm ball bearings. I'm sure the model will happily spit out numbers, but are they reasonable? How do we know they are reasonable? Even if the prediction is ok, how do we fundamentally know that the prediction for 4 mm ball bearings won't be completely wrong?
There seems to be a lot of critical information missing.
Subtle brag that Waymo could drive in camera-only mode if they chose to. They've stated as much previously, but that doesn't seem widely known.
For shits and giggles, I did stop randomly while crossing the road and acted like a jerk.
The Waymo did, in fact, stop.
Kudos, Waymo
IMO, access to DeepMind and Google infra is a hugely understated advantage Waymo has that no other competitor can replicate.
A power outage feels like a baseline scenario—orders of magnitude more common than the disasters in this demo. If the system can’t degrade gracefully when traffic lights go dark, what exactly is all that simulation buying us?
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(simulations) (real world data) (simulations)
Seems like it, no?We started with physics-based simulators for training policies. Then put them in the real world using modular perception/prediction/planning systems. Once enough data was collected, we went back to making simulators. This time, they're physics "informed" deep learning models.
https://deepmind.google/blog/genie-3-a-new-frontier-for-worl...
Discussed here,eg.
Genie 3: A new frontier for world models (1510 points, 497 comments)
https://news.ycombinator.com/item?id=44798166
Project Genie: Experimenting with infinite, interactive worlds (673 points, 371 comments)
2. No seriously, is the filipino driver thing confirmed? It really feels like they're trying to bury that.
Or the most realistic game of SimCity you could imagine.
[*] https://futurism.com/advanced-transport/waymos-controlled-wo...
Its much easier to build everything into the compressed latent space of physical objects and how they move, and operate from there.
Everyone jumped on the end-2-end bandwagon, which then locks you into the input to your driving model being vision, which means that you have to have things like genie to generate vision data, which is wasteful.
Also we record body position actuation and self speech. As output then we put this on thousands of people to get as much data as Waymo gets.
I mean that’s what we need to imitate agi right? I guess the only thing missing is the memory mechanism. We train everything as if it’s an input and output function without accounting for memory.
Talk about edge cases.
But, what would you do? Trust the Waymo, or get out (or never get in) at the first sign of trouble?
I started working heavily on realizing them in 2016 and it is unquestionably (finally) the future of AI
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