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Nvidia is cementing its presence in the autonomous vehicle space by introducing a new artificial intelligence platform designed to help cars make decisions in complex, real-world conditions. The move reflects the company’s broader strategy to take AI beyond digital tools and embed it into physical systems that operate in public environments.
The platform, named Alpamayo, was introduced by Nvidia chief executive Jensen Huang during a keynote address at the Consumer Electronics Show in Las Vegas. According to the company, the system is built to help self-driving vehicles reason through situations rather than simply respond to sensor inputs. This approach is intended to improve safety, particularly in unpredictable traffic conditions where human judgment is often required.
Nvidia says Alpamayo enables vehicles to manage rare driving scenarios, operate smoothly in dense urban settings, and provide explanations for their actions. By allowing a car to communicate what it intends to do and why, the company aims to address long-standing concerns around transparency and trust in autonomous driving technology.
As part of this effort, Nvidia confirmed a collaboration with Mercedes-Benz to develop a fully driverless vehicle powered by the new platform. The company stated that the vehicle is expected to launch first in the United States within the next few months, followed by expansion into European and Asian markets.
Although Nvidia is widely known for the chips that support today’s AI boom, much of the public focus has remained on software applications such as generative AI systems. Industry attention is now shifting toward physical uses of AI, including vehicles and robotics, where decision-making errors can have serious consequences.
Huang noted that Nvidia’s work on autonomous systems has provided valuable insight into building large-scale robotic platforms. He suggested that physical AI is approaching a turning point similar to the rapid rise of conversational AI tools in recent years.
A demonstration shown at the event featured a Mercedes-Benz vehicle navigating the streets of San Francisco without driver input, while a passenger remained seated behind the wheel with their hands off. Nvidia explained that the system was trained using human driving behavior and continuously evaluates each situation before acting, while also explaining its decisions in real time.
Nvidia also made the Alpamayo model openly available, releasing its core code on the machine learning platform Hugging Face. The company said this would allow researchers and developers to freely access and retrain the system, potentially accelerating progress across the autonomous vehicle industry.
The announcement places Nvidia in closer competition with companies already offering advanced driver-assistance and autonomous driving systems. Industry observers note that while achieving high levels of accuracy is possible, addressing rare and unusual driving scenarios remains a major technical hurdle.
Nvidia further revealed plans to introduce a robotaxi service next year in partnership with another company, although it declined to disclose the partner’s identity or the locations where the service will operate.
The company currently holds the position of the world’s most valuable publicly listed firm, with a market capitalization exceeding 4.5 trillion dollars, or roughly £3.3 trillion. It briefly became the first company to reach a valuation of 5 trillion dollars in October, before losing some value amid investor concerns that expectations around AI demand may be inflated.
Separately, Nvidia confirmed that its next-generation Rubin AI chips are already being manufactured and are scheduled for release later this year. The company said these chips are designed to deliver strong computing performance while using less energy, which could help reduce the cost of developing and deploying AI systems.
Security researchers have identified a new category of Android malware that uses artificial intelligence to carry out advertising fraud without the user’s knowledge. The malicious software belongs to a recently observed group of click-fraud trojans that rely on machine learning rather than traditional scripted techniques.
Instead of using hard-coded JavaScript instructions to interact with web pages, this malware analyzes advertisements visually. By examining what appears on the screen, it can decide where to tap, closely imitating normal user behavior. This approach allows the malware to function even when ads frequently change layout, include video content, or are embedded inside iframes, which often disrupt older click-fraud methods.
The threat actors behind the operation are using TensorFlow.js, an open-source machine learning library developed by Google. The framework allows trained AI models to run inside web browsers or server environments through JavaScript. In this case, the models are loaded remotely and used to process screenshots taken from an embedded browser.
Researchers from mobile security firm Dr.Web reported that the malware has been distributed through GetApps, Xiaomi’s official application store. The infected apps are mainly games. In several cases, the applications were initially uploaded without harmful functionality and later received malicious components through software updates.
Once active, the malware can run in what researchers describe as a “phantom” mode. In this mode, it opens a hidden browser based on Android’s WebView component. This browser loads a webpage containing advertisements and a JavaScript file designed to automate interactions. The browser operates on a virtual screen that is not visible to the device owner. Screenshots of this screen are repeatedly captured and sent to the AI model, which identifies relevant ad elements and triggers taps that appear legitimate.
A second operational mode, referred to as “signalling,” gives attackers direct control. Using WebRTC technology, the malware streams a live video feed of the hidden browser to the threat actor. This allows them to perform actions such as tapping, scrolling, or entering text in real time.
Dr.Web identified multiple infected games hosted on Xiaomi’s platform, including titles with tens of thousands of downloads. Beyond official app stores, the malware has also been found in modified versions of popular streaming applications distributed through third-party APK websites, Telegram channels, and a Discord server with a large subscriber base. Many of these apps function as expected, which reduces user suspicion.
Although this activity does not directly target personal data, it still affects users through increased battery drain, higher mobile data usage, and faster device wear. For cybercriminals, however, covert ad fraud remains a profitable operation.
Security experts advise Android users to avoid downloading apps from unofficial sources and to be cautious of altered versions of well-known apps that promise free access to paid features.