Breaking news

Forterra Says More Than 100 Autonomous Vehicles Have Operated In Ukraine

Forterra, the U.S. autonomous vehicle developer, says more than 100 of its self-driving all-terrain vehicles have been operating in Ukraine’s combat zones over the past nine months. If confirmed, the deployment would represent what the company believes is the largest operational use of autonomous ground vehicles in combat by a U.S. defense technology firm.

“I believe this to be true of every defense technology that’s ever been created—until you hit the realities of combat, you’re just not going to know,” Scott Sanders, Forterra’s chief growth officer and a former U.S. Marine officer, told TechCrunch.

Ukraine Has Become A Testing Ground

Supported by U.S. defense funding, the deployment reflects a broader effort to evaluate emerging military technologies under real battlefield conditions. While much of the war has highlighted the role of aerial drones, it has also exposed growing demand for autonomous ground vehicles capable of transporting supplies and evacuating casualties under fire.

“There’s nowhere to hide,” Sergeant Major Corey Wilkens, who leads a U.S. Army programme focused on autonomous vehicles, told TechCrunch, pointing to the growing threat posed by drones, artillery and mortar fire.

Built For Battlefield Logistics

Ukraine has developed its own uncrewed ground vehicles, but they are generally battery-powered and limited to payloads of around 250 kilograms. Forterra’s Lancer vehicles, built on Polaris all-terrain vehicles, use petrol engines and can carry up to 750 kilograms, making them better suited for frontline logistics.

“The bottom line is that this UGV for logistics… is the most important UGV in Ukraine,” a Ukrainian soldier told TechCrunch. “It’s fantastic, and we are dying to get more.”

Lessons From Combat

Initially, Ukrainian forces viewed the system with some skepticism, but Forterra says adapting the vehicles by adding Starlink satellite connectivity significantly improved their effectiveness on the battlefield.

Since arriving in Ukraine last October, the vehicles have travelled more than 2,500 miles across over 1,100 missions, transported nearly 780,000 pounds of cargo and completed 52 casualty evacuations. Some have been destroyed after becoming immobilised in difficult terrain or exposed to Russian attacks.

The deployment has also provided valuable operational data on electronic warfare, software updates, mobility and vehicle reliability, strengthening Forterra’s position as it competes for future U.S. defense contracts.

Autonomy Still Has Limits

Despite the progress, Ukrainian operators continue to rely heavily on remote control rather than fully autonomous driving during combat missions. Current systems can navigate challenging terrain independently but still struggle to respond to rapidly changing battlefield threats without human intervention.

“We actually need to be able to respond to enemy threats live… which the autonomy doesn’t know how to do yet,” the Ukrainian soldier said.

Forterra is now working to combine its autonomous driving software with generative AI while continuing to rely on more traditional robotics for specialised military tasks.

Competition Is Growing

Forterra is one of several companies developing autonomous military vehicles. Competitors including Scout AI, Field AI and Overland AI are also working with the U.S. military to advance autonomous ground systems. Even so, military officials believe the technology has already proved its potential.

“Ground autonomy is achievable now and we’ve seen it,” Wilkens said.

Cost Remains A Major Challenge

For Ukrainian operators, affordability is becoming as important as capability. Although Forterra’s vehicles benefit from commercially available Polaris platforms, they remain too expensive to lose at the rate that aerial drones are routinely lost in combat.

“Attrition is just a fact of this battlefield,” the Ukrainian soldier said. “We have lost a few… we need more, and therefore we need them cheaper.”

The experience in Ukraine suggests autonomous ground vehicles are moving beyond experimentation. Their next challenge will be becoming affordable and adaptable enough for large-scale battlefield deployment.

Meta Unveils Muse Wonder Models In A Bid For Frontier AI Leadership

Meta has introduced two new AI models, Muse Wonder and Muse Wonder Full, signalling a more ambitious move into frontier AI. The releases build on Muse Spark but target more demanding tasks, including coding, while placing greater emphasis on long-term memory and personalised assistance.

Larger Models Target More Demanding Tasks

Unlike Muse Spark, which was designed for low latency and lightweight use, Muse Wonder and Wonder Full are significantly larger and, according to Meta, more capable. The company reports stronger benchmark performance and improvements on demanding workloads, including coding.

According to Meta’s model card, both models achieved benchmark results comparable to Fable 5.1 and GPT-6 Astra in the company’s internal testing. Meta described the release as “the next step on our scaling ladder and a major leap toward personal superintelligence” in its announcement.

Pricing Reflects Meta’s Frontier Ambitions

The models’ pricing places them in the premium AI segment. Through the Meta Model API, Muse Wonder will cost $4 per million input tokens and $20 per million output tokens, putting it in a similar pricing tier to GPT-6 Sol and Opus 5.5.

Muse Wonder Full, by contrast, will not be offered through the API. Meta says it will be exclusive to Muse Code subscribers, tying access to its most advanced model to a premium product. Both models will also power the Muse agent.

Long-Term Memory Takes Centre Stage

Meta is increasingly positioning its AI strategy around assistants that can support users over time rather than respond only to individual prompts. A central part of that approach is what the company calls “active memory”: the ability to retain, organise and synthesise information provided by users across extended periods.

Meta points to the MemoryBench benchmark, which evaluates systems designed for continual learning and memory construction. The company says Muse Wonder now outperforms Fable, Opus and Astra on this measure.

“We put a tremendous amount of effort into making sure your model can remember what’s important to you over days, weeks, months, and beyond,” research scientist Kavya Kopparapu said in a launch video.

New Models Follow Meta’s AI Reorganisation

The launch is also significant within Meta’s broader AI strategy. It is the company’s first frontier-model release since Scale AI founder Alexandr Wang reorganised its AI operations in August 2025. Meta has since introduced Muse Spark and the Muse agent, while making fewer high-profile model announcements than competitors such as OpenAI and Anthropic.

The new models were trained at Meta’s Prometheus data centre in central Ohio, which came online earlier in 2026, according to the company. The facility highlights the growing importance of infrastructure in the race to develop advanced AI systems, where performance depends not only on algorithms and data but also on computing capacity, data-centre investment and access to capital.

As competition intensifies, Muse Wonder and Wonder Full represent a broader bet on larger models, persistent memory and premium AI products. Their longer-term significance will depend on how their reported capabilities translate into real-world performance and whether users find enough value to pay for access.

The Future Forbes Realty Global Properties
Aretilaw firm
eCredo
Uol

Become a Speaker

Become a Speaker

Become a Partner

Subscribe for our weekly newsletter