The algorithm is saving about $10 million as part of an effort to replace the city’s water infrastructure.
To catch you up: In 2014, Flint began getting water from Flint River rather than the Detroit water system. Mistreatment of the new water supply, combined with old lead pipes, created contaminated water for residents.
Solving the problem: Records that could be used to figure out which houses might be affected by corroded old pipes were missing or incomplete. So the city turned to AI. Using 71 different pieces of information—like the age or value of the home—Georgia Tech researchers developed an algorithm that predicted whether or not a home was connected to lead pipes.
The improvement: Before the software was implemented, only 20 percent of the pipes dug up needed replacement. By contrast, the list of lead pipe locations generated by the software has a 97 percent success rate. This huge jump in accuracy is saving the city enough time and money to remediate an additional 2,000 homes.
This artist is dominating AI-generated art. And he’s not happy about it.
Greg Rutkowski is a more popular prompt than Picasso.
What does GPT-3 “know” about me?
Large language models are trained on troves of personal data hoovered from the internet. So I wanted to know: What does it have on me?
An AI that can design new proteins could help unlock new cures and materials
The machine-learning tool could help researchers discover entirely new proteins not yet known to science.
DeepMind’s new chatbot uses Google searches plus humans to give better answers
The lab trained a chatbot to learn from human feedback and search the internet for information to support its claims.
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