Daniel Pelaez first had the idea for what would eventually become Cyvl while working a summer job on a public works road crew in a small Connecticut town. He spent his days there driving around in a pickup truck looking for things to fix.

One day, he asked the foreman if there was a better way to route the crew. “He showed me all these huge six-inch binders behind his desk…a manual audit that a civil engineering consulting firm did seven years ago,” Pelaez said. “After one winter, that data was just out of date.”

Fast-forward several years, and Pelaez’s startup, Cyvl (pronounced “civil”), now has a better way to flag issues like potholes, bad pavement conditions, or broken signs. It involves cars outfitted with lidar, consumer-grade cameras—think GoPros—and 3D-printed sensors that collect data to build a digital model of a town or city. Computer vision models classify elements like signs and sidewalks and scan for cracks or damage.

Cyvl currently counts more than 100 towns and cities as customers, and it’s done work with 300 total, mostly in the United States, according to Pelaez. The company raised $14 million in Series A funding this month in a round led by Sentinel Global.

In addition to expanding to more places, Pelaez said the money will help Cyvl to continue building tools across other stages of infrastructure building and maintenance, from planning and construction to operation.

“We’ve sort of mastered the art of putting sensors in the world, digitizing infrastructure, and getting conditions on things,” Pelaez said. “We want to start tackling the rest of…the life cycle of infrastructure.”

Keep reading here.—PK

It’s July 2024. Vice President Kamala Harris just kicked off a blitz run for the White House after a shock switch-up.

Meanwhile, a team of MIT researchers was working to better understand how chatbots perceive this political environment. They fed a dozen leading LLMs 12,000 election-related questions on a nearly daily basis, collecting more than 16 million total responses through the contest in November. Now they’re publishing some conclusions from that process.

As the first big US political race to occur since generative AI went mainstream, the 2024 presidential campaigns happened in a media environment in which the average voter was increasingly looking to chatbots for election information.

The authors wanted to study the impact that shift had on the information voters saw, in the same way that previous research has looked at the role of social media or other emerging mediums.

“Whether and how to impart politically fair information has been a sticking point in discussions about radio, print, social media, and now language models,” lead author Sarah Cen, now an assistant professor of engineering and public policy at Carnegie Mellon University, told us in an email.

Keep reading here.—PK

It’s pretty safe to say that corporate execs are bullish on AI, and if you’re reading this sentence, it means even the detail-oriented copy desk at Morning Brew sees the ones and zeros on the wall.

This summer, MIT’s Media Lab’s Project NANDA found that enterprise organizations have invested between $30–$40 billion in AI—though it would be irresponsible not to mention that the analysis also concluded that 95% of those investments, so far, have not yielded the expected ROI…so yeah.

While AI is top of mind for many in the C-suite, HR pros are more hesitant to welcome the burgeoning technology, according to survey research from employee experience platform Culture Amp.

Culture Amp’s North American people science director, Robert Melloy, told HR Brew that the platform’s found HR pros are more leery of the promise of AI for their function and for employees.

“The primary benefits of AI are to increase your scale, your scope, and your learning,” said Melloy, who also teaches business and organizational psychology. “Increase the amount of things that you’re able to do…increase the types of things that you’re able to do, and then…being able to get feedback faster, to become better over time.”

Keep reading here.—AD