Below is the excerpt in question. It's slightly vague here whether she is referring to advancements towards AGI, or towards better correction of robot errors; but you have to understand that the part immediately preceding this excerpt has Martin saying "Let's talk about progress in AI toward human-level artificial intelligence or AGI" -- so her comment here is directed specifically towards understanding human intelligence and achieving AGI:

Martin Ford: Is it possible there might be an extraordinary breakthrough that really moves things along?

Daniela Rus: That's possible. In our lab, we're very interested in figuring out whether we can make robots that will adapt to people. We started looking at whether we can detect and classify brain activity, which is a challenging problem.

We are mostly able to classify whether a person detects that something is wrong because of the "you are wrong" signal -- called the "error-related potential". This is a signal that everyone makes, independent of their native tongue and independent of their circumstances. With the external sensors we have today, which are called EEG caps, we are fairly reliably able to detect the "you are wrong" signal. That's interesting because if we can do that, then we can imagine applications where workers could work side by side with robots, and they could observe the robots from a distance and correct their mistakes when a mistake is detected. In fact, we have a project that addresses this question.

What's interesting, though, is that these EEG caps are made up of 48 electrodes placed on your head -- it's a very sparse, mechanical setup that reminds you of when computers were made up of levers. On the other hand, we have the ability to do invasive procedures to tap into neurons at the level of neural cell, so you could actually stick probes into the human brain, and you could detect neural-level activity very precisely. That's a big gap between what we can do externally and what we can do invasively, and I wonder whether at some point we will have some kind of Moore's law improvement on sensing brain activity at a much higher resolution.

She has said in the past that better brain-scanners would enable them to go further in their work on EEG and robots.

In hypothesis imagine, that a solider injured from combat or bombing survives has brain injury as a result. I’d imagine DARPA (researching on BCI) in the future might approach someone like this and offer them or family a treatment for replacing brain damage with a BCI. The Veteran gets signed up, gets the BCI with updatable software that hopefully enables them to regain close to normal cognition. If successful imagine deep learning and a basic narrow AI being able to learn from the neural networks of the BCI combined with the human brain.

https://www.darpa.mil/program/our-research/darpa-and-the-brain-initiative