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This is a junk paper. The kind of paper where people stake out some combination of keywords so that they get citations in the future but it contributes nothing
by light_hue_1 3y ago
This is a junk paper. The kind of paper where people stake out some combination of keywords so that they get citations in the future but it contributes nothing at all. They know that LLMs will probably be used in the future, but don't know how, and can't think of any practical way to do it.
> We are the first to demonstrate the feasibility of employing LLM in driving scenarios and
exploit its decision-making ability in the simulated driving environment
They demonstrate nothing. Not one driving dataset is used. They don't actually evaluate on HighwayEnv, just show some cherry picked examples.
There is nothing here at all. No new ideas, no demonstration of anything. What a shame.
- deleted 3y ago[deleted]
- Animats 3y agoHarsh, but probably not wrong. This is closer to "good old fashioned AI" than a learning system. The process is * Observe situation * (Miracle happens) * Simple description of situation pops out * Crunch a bit on the simple description to get answer. That's very 1980s, with simple English substituted for predicate calculus expressed as S-expressions. The (miracle happens) step is still a problem. Image interpretation has advanced a lot, but not enough. When you look at videos of Tesla's vision system at work, it regularly fails to recognize cars and people until they're very close. Waymo seems over-sensored, but that's needed to reliably map the environment. "Driving like people" is basically minor tweaks on the hard problem, "driving without hitting stuff".
- famouswaffles 3y agoDon't think a miracle really needs to happen. Maybe the paper doesn't get into that but certainly their are potentially viable methods being worked https://wayve.ai/thinking/lingo-natural-language-autonomous-driving/ https://wayve.ai/thinking/lingo-natural-language-autonomous-...