AI Weekly Digest

presented by Louis (What's AI) Bouchard
 

Hi again! As you may already know, there were broken links in yesterday's iteration. Here is the right version with all the correct links for the article and video.
Sorry for the inconvenience, and happy listening/reading!

Have you ever tuned in to a video or a TV show and the actors were completely inaudible, or the music was way too loud? Well, this problem, also called the cocktail party problem, may never happen again. Mitsubishi and Indiana University just published a new model as well as a new dataset tackling this task of identifying the right soundtrack. For example, if we take the same audio clip we just ran with the music way too loud, you can simply turn up or down the audio track you want to give more importance to the speech than the music.

The problem here is isolating any independent sound source from a complex acoustic scene like a movie scene or a youtube video where some sounds are not well balanced. Sometimes you simply cannot hear some actors because of the music playing or explosions or other ambient sounds in the background. Well, if you successfully isolate the different categories in a soundtrack, it means that you can also turn up or down only one of them, like turning down the music a bit to hear all the other actors correctly. This is exactly what the researchers achieved. Read more here...

From a philosophical standpoint, I think what's relevant here is not the noise or the quality of the signal but the selective nature of attention.
Consider all audio signals we perceive every day. When we focus on something, our brain filters out what it takes for irrelevant, repetitive or boring. My geography teacher's voice, for example, or literally everything out of my daydreaming when I was an adolescent in love. 

I started thinking our brain acts like a biological spam filter. Through adaptation and evolution, we fine-tuned the process for maximizing surviving chances. For example, we can easily distinguish particular sets of frequencies as the roars of predators or the cries of a baby and almost instantaneously fall into a state of alert when we hear a high volume, high pitch sound that resembles a scream. To what extent are we in control of the anti-spam measures? How accurate is it? Could we outsmart the process to make it more efficient for our times, goals and health?

What if we could smartly automatize the anti-spam process through a Brain-machine interface that can:
- filter or suppress the undesired audio signals just before neurotransmitters process them,
- amplify the otherwise inaudible signals? 

Volitional attention is deeply connected with consciousness and freedom. Being aware of what's happening around us and inside us is crucial for our autonomy. Focusing for a long time in the pursuit of mastering some domain through practice, nonetheless, involves cultivating more profound freedom. Moreover, paying attention to someone proves our interest, respect, affection, and commitment.

Then, if we wanted to outsmart attention, who might decide what is worth attention and, maybe most importantly, what is not? And how?
Big Tech and Marketing experts know the value of attention; they are already adopting AI to grab and hold attention to the screen, and sounds are a relevant component. See advertising jingles and audio techniques.

If this hypothesis became feasible, the human species would probably evolve into something else. Might it be the first step toward transhumanism? Or toward a no-surprises "Wall-E society" where our expectations are always met?

- Martina

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- Louis Bouchard