Robots (not) in search and rescue, AI influencing pop music, and more!

Last Week in AI #123

Mini Briefs

Why Robots Can't Be Counted On to Find Survivors in the Florida Building Collapse

Following the recent Florida building collapse, many in the robotics world and wondering why aren't there rescue robots being used to assist on-the-ground search and rescue efforts? There are two broad sets of problems. The first is technical. In rubble exploration, the valuable part comes from going into rubbles, autonomously navigating structures, locating victims and surveying surrounding structures. No robot today are rugged and autonomous enough to handle such harsh and unpredictable environments. In addition, localization and wireless comunication is often impossible, and wired tethers are can easily become tangled on obstacles. The second is funding. Large-scale disasters are fortunately rare, but this means that funding interest in such research is very sporadic and tapers off once some time has passed since a disaster. This means it is difficult for researchers to sustain development efforts and also build up enough field experience that would allow such technology to mature.

Robot rock: can big tech pick pop's next megastar?

Internet and social media has enabled music talents to break out in a way that was impossible before - anyone can upload a track to YouTube, SoundCloud, or TikTok, and start amassing an audience. To major record labels and scouting agencies who need to pick out trends and the next stars, this deluge of content is difficult to be parsed by humans. Recently, AI-powered algorithms have been used to make such recommendations and identify potential rising talents. Some algorithms focus on the music itself, analyzing the soundtrack to see how well it fits with certain genres and predicting how popular it might be with certain audience groups. Other algorithms focus on the context - how many listens a track has on a streaming platform, how well connected is the artist's social media profile, etc.

Applying analytics to pick talent is not new - it has been widely documented in sports since Moneyball. However, not everyone is convinced that similar analytics-driven decision making can make sustained impacts in music. Rules in sports rarely change, but objectives and trends in music and pop culture are more dynamic and unpredictable.

AI can’t learn something that it hasn’t been taught,” she says. “It can do pop, indie, trap, UK grime, but if you show it a hybrid of Mongolian throat-singing and electric violin, then it can’t categorise that.

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