Comment by notepad0x90
8 hours ago
There are almost endless reasons why. It's like asking why would you want a self-driving car. Having a drone to transport things would be amazing, or to patrol an area. LLMs can be helpful with object identification, reacting to different events, and taking commands from users.
The first thought I had was those security guard robots that are popping up all over the place. if they were drones instead, and LLM talked to people asking them to do/not-do things, that would be an improvement.
Or an waiter drone, that takes your order in a restaurant, flies to the kitchen, picks up a sealed and secured food container, flies it back to the table, opens it, and leaves. It will monitor for gestures and voice commands to respond to diners and get their feedback, abuse, take the food back if it isn't satisfactory,etc...
This is the type of stuff we used to see in futuristic movies. It's almost possible now. glad to see this kind of tinkering.
You could have a program, not LLM-based but could be ANN, for flying and an LLM for overseeing; the LLM could give the program instructions to the pilot program as a (x,y,z) directions. I mean currently autopilots are typically not LLMs, right?
You describe why it would be useful to have an LLM in a drone to interact with it but do not explain why it is the very same LLM that should be doing the flying.
I'm not OP, I don't know what specific roles the LLM should be using, but LLMs are great with object recognition, and using both text (street signs,notices,etc..) and visual cues to predict the correct response. The actual motor control i'm sure needs no LLMs, but the decision making could use any number of solutions, I agree that an LLM-only solution sounds bad, but I didn't do the testing and comparison to be confident in that assessment.
The point is that you don't need an LLM to pilot the thing, even if you want to integrate an LLM interface to take a request in natural language.
An LLM that can't understand the environment properly can't properly reason about which command to give in response to a user's request. Even if the LLM is a very inefficient way to pilot the thing, being able to pilot means the LLM has the reasoning abilities required to also translate a user's request into commands that make sense for the more efficient, lower-level piloting subsystem.
That’s a pretty boring point for what looks like a fun project. Happy to see this project and know I am not the only one thinking about these kinds of applications.
We don't need a lot of things, but new tech should also address what people want, not just needs. I don't know how to pilot drones, nor do I care to learn how to, but I want to do things with drones, does that qualify as a need? Tech is there to do things for us we're too lazy to do.
There are two different things:
1. a drone that you can talk to and fly on its own
2. a drone where the flying is controlled by an LLM
(2) is a specific instance of the larger concept of (1).
You make an argument that 1 should be addressed, which no one is denying in this thread - people are arguing that (2) is a bad way to do (1).
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I don't think you understand what an "LLM" is. They're text generators. We've had autopilot since the 1930s that relies on measurable things... like PID loops, direct sensor input. You don't need the "language model" part to run an autopilot, that's just silly.
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You want a self driving car
You don't want an LLM to drive a car
There is more to "AI" than LLMs
Waymo is certainly interested in using LLMs/VLMs for this purpose.
https://waymo.com/research/emma/
https://waymo.com/blog/2024/10/introducing-emma
https://waymo.com/blog/2025/12/demonstrably-safe-ai-for-auto...
I don't mind someone trying LLMs to see if they can do better than existing ML solutions.
Both of those proposed uses are bad things that are worse than what they would replace.