Latam-GPT is new large language model being developed in and for Latin America. The project, led by the nonprofit Chilean National Center for Artificial Intelligence (CENIA), aims to help the region achieve technological independence by developing an open source AI model trained on Latin American languages and contexts.

“This work cannot be undertaken by just one group or one country in Latin America: It is a challenge that requires everyone’s participation,” says Álvaro Soto, director of CENIA, in an interview with WIRED en Español. “Latam-GPT is a project that seeks to create an open, free, and, above all, collaborative AI model. We’ve been working for two years with a very bottom-up process, bringing together citizens from different countries who want to collaborate. Recently, it has also seen some more top-down initiatives, with governments taking an interest and beginning to participate in the project.”

The project stands out for its collaborative spirit. “We’re not looking to compete with OpenAI, DeepSeek, or Google. We want a model specific to Latin America and the Caribbean, aware of the cultural requirements and challenges that this entails, such as understanding different dialects, the region’s history, and unique cultural aspects,” explains Soto.

Thanks to 33 strategic partnerships with institutions in Latin America and the Caribbean, the project has gathered a corpus of data exceeding eight terabytes of text, the equivalent of millions of books. This information base has enabled the development of a language model with 50 billion parameters, a scale that makes it comparable to GPT-3.5 and gives it a medium to high capacity to perform complex tasks such as reasoning, translation, and associations.

Latam-GPT is being trained on a regional database that compiles information from 20 Latin American countries and Spain, with an impressive total of 2,645,500 documents. The distribution of data shows a significant concentration in the largest countries in the region, with Brazil the leader with 685,000 documents, followed by Mexico with 385,000, Spain with 325,000, Colombia with 220,000, and Argentina with 210,000 documents. The numbers reflect the size of these markets, their digital development, and the availability of structured content.

“Initially, we’ll launch a language model. We expect its performance in general tasks to be close to that of large commercial models, but with superior performance in topics specific to Latin America. The idea is that, if we ask it about topics relevant to our region, its knowledge will be much deeper,” Soto explains.

The first model is the starting point for developing a family of more advanced technologies in the future, including ones with image and video, and for scaling up to larger models. “As this is an open project, we want other institutions to be able to use it. A group in Colombia could adapt it for the school education system or one in Brazil could adapt it for the health sector. The idea is to open the door for different organizations to generate specific models for particular areas like agriculture, culture, and others,” explains the CENIA director.

Suyun Ham can’t take his eyes off a scanner. “Lower the sensors a little bit more,” Ham urges an assistant. Then a barrage of data floods in, filling computer screens for a diagnosis.

But Ham isn’t a medical doctor. Nor is his “patient” a living creature. An engineering professor from the University of Texas at Arlington, he is experimenting with a novel approach in bridge inspection.

Ham’s mobile-scanning system is part of efforts to make US infrastructure more heat-resilient. Unlike floods and tornados that can quickly destroy bridges, extreme heat is a silent killer that harms them over time, experts say.

“If temperatures are out of range, bridges can get damaged unexpectedly,” says Ham, who lives in the Dallas-Fort Worth area, where summer temperatures can exceed 100F (38C). “With our “MRI,” we can see what’s inside a bridge quickly.”

Bridge materials expand and contract in response to temperature fluctuations. While most are equipped with features to accommodate that movement, they were designed to withstand historically cooler temperatures, says Paul Chinowsky, a professor emeritus of civil engineering at the University of Colorado Boulder.

When temperatures hit a record high, bridges might behave in ways that engineers didn’t intend them to, he adds.Heat-swollen steel joints can impair the mobility of a swing bridge, making it unable to open or close—at least temporarily. Concrete also expands under heat. Once its expansion goes beyond a bridge’s original design limit, the concrete can crack, exposing it to moisture that can corrode internal metal components.

That’s an increasingly common scene around the world. In China, a concrete bridge broke in half because of brutal heat in 2022. That same year, London wrapped Hammersmith Bridge in giant pieces of foil to prevent it from overheating. And when the blistering sun baked Chicago’s DuSable drawbridge in 2018, its steel joints expanded and got stuck until firefighters hosed the bridge with cold water.

“Bridges are very susceptible,” Chinowsky says. “The hotter it gets compared to what typically it is, the more danger you have.”

‘A lot of headaches’

Hotter temperatures are baking US bridges at a time when their health is already deteriorating. The country has more than 600,000 bridges, almost half of which have exceeded their designed lifespan of 50 years, according to a 2025 report by the American Society of Civil Engineers.

With proper maintenance, many can last much longer, potentially exceeding 100 years, the industry group says. Still, about one in three bridges requires repair or replacement, according to an analysis published this year by the American Road and Transportation Builders Association.

Hussam Mahmoud, a professor at Vanderbilt University who has evaluated the structural integrity of about 90,000 steel-girder bridges across the US, found that many have aged prematurely, due in large part to the heat-accelerated malfunction of their expansion joints.

As the frequency and severity of heat waves increase with climate change, expansion joints, which connect two bridge spans, expand more often. That, coupled with the strain caused by debris or dirt accumulated in the joints over time, adds pressure to the structure, elevating the risk for a bridge to crack or buckle, Mahmoud says.

Although those defects don’t put a bridge in immediate danger of collapse, they need to be fixed to avoid further damage, which can be “a lot of headaches,” says Mahmoud.

With more than 4.9 billion trips taken across US bridges on any given day, bridge closures can take a toll on commerce and the economy, Mahmoud says. More damage also means higher maintenance costs. The US is already facing a $373 billion funding gap over the next 10 years to repair bridges properly, according to the American Society of Civil Engineers.Heat-induced damage can also cause bridges to malfunction at a time when the free movement of people is needed the most.

In June, a swing bridge in South Carolina got stuck for hours due to sweltering temperatures and was unable to open for ships to go through, delaying rescue efforts for a fatal boating accident.

Drive-by inspections

For Ham, better bridge monitoring is key. “Just like it is difficult to heal a human patient with stage-four cancer, it’d be too late to repair a bridge when there are a lot of defects,” he says.Ham, who spent a big chunk of his college time inspecting bridges, learned the limitations of the conventional method firsthand. He used to tap the bridge surface with a hammer and listen for hollow sounds that could indicate problems.

That hammer later evolved into more advanced devices, yet the time-consuming nature of manual inspection remains largely unchanged, Ham says. The conventional method also requires a bridge to shut down some of its lanes for inspection, a big ask for places such as Texas, which has 56,000-plus bridges.

While federal mandates typically require highway bridges to be inspected every two years, Ham and others at the University of Texas’s Smart Infrastructure and Testing Laboratory in Arlington want to help increase that frequency by introducing a new solution: a drive-through inspection.

Ham’s machine—a trailer loaded with dozens of electronics—is hauled by a pickup truck. On a sizzling afternoon in July, as the vehicle pulled the machine across a concrete bridge over a stream bed on the university campus, the tools generate mechanical waves that can propagate through concrete.

Sensors pick up the resulting bridge vibration signals, while a GPS device pins down where each signal comes from. Meanwhile, ground-penetrating radars emit pulses to create images of the structure under the bridge’s deck, and GoPros videotape the surface condition. The end goal, according to Ham, is to collect a wide range of data that enables engineers to identify cracks, voids and other anomalies.

The machine scanned the entire 5-feet-long bridge within seconds. By contrast, it would take hours for inspectors to complete the same job using the conventional method, according to Ham.

“There’s a lot of surface damage,” Ham says, pointing to a number of bright orange dots and stripes scattered across the dark blue background of one computer image generated from the onsite scanning. He also spots a cluster of tiny cracks, highlighted by a red rectangle.

Ham and his team then use artificial intelligence to refine the analysis and filter out “noises”—irregular vibration signals caused by a car driving by during the inspection, for instance. The engineers report their findings to bridge overseers for safety assessment and future repair work.

“It is better for time and efficiency,” says Mark Burwell, a bridge inspection coordinator at the Texas Department of Transportation whose agency has deployed Ham’s technology to inspect dozens of bridges since 2019. As inspectors no longer have to work next to moving traffic on a bridge, the automated inspection also helps put humans out of harm’s way, he adds.

For now, Ham’s “portable MRI” is only available for bridge inspection in the Lone Star state. Ham aims to scale up its deployment. To make that happen, the engineers will have to first perfect the innovation.

There have been many learning moments, Ham recalls. Once, a rough ride knocked off sensors, cutting an inspection mission short. (The machine is now equipped with a lift that lowers and raises it to avoid obstacles on the road.) On another occasion, the software grappled with the complexity of decoding signals from a concrete bridge covered with asphalt patches.

To help the AI better interpret signals, Ham and his team have turned their laboratory into a manufacturing hub of artificial defects. There, engineers soak metal sticks in brine to emulate corrosion. They also drill holes in concrete slabs to mimic cracks. By applying sensors and radars to examine those artificial defects, the engineers can pair different signals with different types of damage.

Even so, the machine is unlikely to catch all the heat-induced problems, according to Ham. For instance, searing temperatures can stress a bridge, but the machine can’t detect it until physical damage occurs.

But data collected from damaged bridges may pave a way for future protection, Ham says. That’s because, by comparing the number of cracks in bridges built with different methods and materials, the technology plays a role in helping regulators determine how to design structures more suitable for a hotter world.

“We’re like a medical doctor,” Ham says. “We can help them make a decision.”

2025 Bloomberg News. Distributed by Tribune Content Agency, LLC.

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