Comment by bfeynman | Hacker News Reader

Comment by bfeynman | Hacker News Reader

I feel bad that people have to read this. It's complete puffery, made up for clicks, and the biggest thing is the pure bravado with which a company says, "Hey, let's just waste a ton of money, all for a potential blog and marketing piece." This is not really automated in any fashion. I was dubious at first, but then I saw the screencaps showing the devs interacting with Luna via a Slack workflow with a human in the loop — meaning they're literally just proxying their own behavior through an LLM. This is no different than anyone who consults AI for any decision with context. To get even more technical on the fallacy: this is not automation, as there is data leakage at every step where there is a human in the loop. A broken clock is right twice a day; an LLM could cycle through 100 guesses to pick a number, but don't market that as an oracle. Aside from that, you could just look at the pictures and context (retail in SF) and assume making a profit here would be near impossible. An actual AI ceo would probably have immediately cancel the lease.

> I was dubious at first, but then I saw the screencaps showing the devs interacting with Luna via a Slack workflow with a human in the loop — meaning they're literally just proxying their own behavior through an LLM. This is no different than anyone who consults AI for any decision with context.

A human can be in the loop if the human is exactly executing the orders of the AI. It's still the AI making all the decisions, which is the purpose of the experiment - not to see whether agents can handle every interaction necessary to run a business (pick up the phone and place orders, etc.). That's also why Luna hired humans.

that is ... not correct? This is classic example of data leakage, the yes/no things are signals feeding back to the model influencing (and here, basically guiding) future decisions.

It's not data leakage.

If the experiment is to see how the AI behaves on its own, then of course it needs to know the outcomes of its decisions (either automatically, or fed to it by a human), which of course influence its next decisions. This is providing the AI with retained memory, which is essential to the experiment. It's similar to an AI writing code which it then runs and parses the logs to see the outcome and make improvements to it. (It is not _retrained_ on those outcomes, and neither is that the case here; but it can reference them in stored memory.)

How is it not analogous to data leakage? The claim is that the system works autonomously, or at minimum could, but there is effectively signal via human in the loop feedback. That's leakage into test time evaluation. Also the coding analogy is malappropriated, in that the llm is using its own signals autonomously in the environment. Using a kalman filter on a ICBM with its own sensors is analogous to the coding agent and is autonomous. A system where a human is course correcting based on signals/sensor data is what's presented here, that is not autonomous.

> A system where a human is course correcting based on signals/sensor data

the human isn't course correcting; the agent is course correcting based on the feedback data; the human is just inputting the feedback data to the agent in cases where the agent isn't able to access that data itself (due to the tooling not yet being in place for such)

data leakage would be the following:

  - agent makes a prediction for problem A based on training data 
  - feedback from the result is fed back to the agent 
  - agent regenerates a prediction for problem A, incorporating the feedback

but in this case:

  - agent makes a decision on Problem A based on training data 
  - feedback from the decision is fed back to the agent 
  - agent makes a decision for Problem B (not revisiting Problem A), a new Problem that is dependent on the outcome of Problem B

A stopped clock is right twice a day; a broken one can be wrong forever. Just saying.

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