News
Quantum ‘compass’ technology aids in navigation without use of GPS satellites
Scientists from Imperial College London and M Squared, a photonics and quantum technology company, have created a portable quantum accelerometer which enables location tracking without the aid of GPS satellites. As demonstrated at the National Quantum Technologies Showcase 2018 in London, the device utilizes ultra-cooled atoms and lasers to measure position with precision made possible by quantum mechanics. The system is currently designed to be used for navigating large vehicles such as ships and trains, but smaller-scale devices will be available as the technology develops.
Quantum accelerator in the lab. | Credit: Imperial College London
The reliance on global navigation satellite systems such as GPS has a few significant shortcomings that the quantum accelerometer would overcome. Satellite signals can be blocked or jammed, interfering with the systems that rely on the data being provided. Threats such as electromagnetic pulse (EMP) attacks on a massive scale, now closer to reality with nuclear capability developments around the world, would cripple any technology relying on satellite systems.
The financial burden of GPS failure is also a serious consideration driving the innovation behind this device. In M Squared’s press release announcement, it was estimated that each day without GPS services in the United Kingdom would cost the country 1 billion pounds. Since it’s a self-contained system not reliant on external signals, a quantum accelerometer would not be at risk for these types of security or financial fallouts.
A close up of the quantum accelerator. | Credit: Imperial College London
Even without the consideration of electronic attacks and satellite failures, a much smaller version of this technology could overcome day-to-day problems with regular GPS use. Anyone who has ever used a map application in a city environment has likely experienced blockages from the buildings disrupting satellite signals. A quantum accelerator would calculate its position based on its high precision velocity measurements rather than GPS information, thus eliminating never-ending “recalculating” type errors that current mapping devices are prone to receive.
General accelerometers are already found in common devices like cell phones and video game controllers. Overall, they function by calculating changes in the velocity of an object (phone, controller, etc.) and that data is used for whatever its intended purpose. For location-driven applications, however, the measured position loses accuracy without feedback from external sources such as GPS. For example, after a few street turns (or less), a mapping application would need to confer with a satellite to recalculate the new position of the car in motion. The high precision of a quantum accelerometer does not have this limitation, thus eliminating the need for a GPS signal.
When atoms are cooled to ultra-cold levels, their quantum behavior emerges and can then be measured by a laser beam acting as a ruler. The team behind the quantum accelerometer device had already been developing other commercial quantum technologies prior to the current one, so when the need for arose for measuring and cooling atoms, a solution was already in place via the team’s universal laser system developed for gravity measurements. This laser both cools and measures the atoms involved in the accelerometer’s device’s movement calculations.
This quantum device is representative of the transition of quantum mechanics from the science laboratory to real-world applications. Besides navigational solutions, Professor Ed Hinds, Director of the Centre for Cold Matter at Imperial College London, described gravity measurements, mapping gravitational forces to look for minerals, and looking inside vehicles to diagnose problems as a few suggestions for other applications. “[The potential applications] …all come from the fantastic sensitivity and reliability that you can only get from these quantum systems.”
Watch the video below to see the quantum team tell more about the device.
News
Nvidia CEO Jensen Huang explains difference between Tesla FSD and Alpamayo
“Tesla’s FSD stack is completely world-class,” the Nvidia CEO said.
NVIDIA CEO Jensen Huang has offered high praise for Tesla’s Full Self-Driving (FSD) system during a Q&A at CES 2026, calling it “world-class” and “state-of-the-art” in design, training, and performance.
More importantly, he also shared some insights about the key differences between FSD and Nvidia’s recently announced Alpamayo system.
Jensen Huang’s praise for Tesla FSD
Nvidia made headlines at CES following its announcement of Alpamayo, which uses artificial intelligence to accelerate the development of autonomous driving solutions. Due to its focus on AI, many started speculating that Alpamayo would be a direct rival to FSD. This was somewhat addressed by Elon Musk, who predicted that “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.”
During his Q&A, Nvidia CEO Jensen Huang was asked about the difference between FSD and Alpamayo. His response was extensive:
“Tesla’s FSD stack is completely world-class. They’ve been working on it for quite some time. It’s world-class not only in the number of miles it’s accumulated, but in the way it’s designed, the way they do training, data collection, curation, synthetic data generation, and all of their simulation technologies.
“Of course, the latest generation is end-to-end Full Self-Driving—meaning it’s one large model trained end to end. And so… Elon’s AD system is, in every way, 100% state-of-the-art. I’m really quite impressed by the technology. I have it, and I drive it in our house, and it works incredibly well,” the Nvidia CEO said.
Nvidia’s platform approach vs Tesla’s integration
Huang also stated that Nvidia’s Alpamayo system was built around a fundamentally different philosophy from Tesla’s. Rather than developing self-driving cars itself, Nvidia supplies the full autonomous technology stack for other companies to use.
“Nvidia doesn’t build self-driving cars. We build the full stack so others can,” Huang said, explaining that Nvidia provides separate systems for training, simulation, and in-vehicle computing, all supported by shared software.
He added that customers can adopt as much or as little of the platform as they need, noting that Nvidia works across the industry, including with Tesla on training systems and companies like Waymo, XPeng, and Nuro on vehicle computing.
“So our system is really quite pervasive because we’re a technology platform provider. That’s the primary difference. There’s no question in our mind that, of the billion cars on the road today, in another 10 years’ time, hundreds of millions of them will have great autonomous capability. This is likely one of the largest, fastest-growing technology industries over the next decade.”
He also emphasized Nvidia’s open approach, saying the company open-sources its models and helps partners train their own systems. “We’re not a self-driving car company. We’re enabling the autonomous industry,” Huang said.
Elon Musk
Elon Musk confirms xAI’s purchase of five 380 MW natural gas turbines
The deal, which was confirmed by Musk on X, highlights xAI’s effort to aggressively scale its operations.
xAI, Elon Musk’s artificial intelligence startup, has purchased five additional 380 MW natural gas turbines from South Korea’s Doosan Enerbility to power its growing supercomputer clusters.
The deal, which was confirmed by Musk on X, highlights xAI’s effort to aggressively scale its operations.
xAI’s turbine deal details
News of xAI’s new turbines was shared on social media platform X, with user @SemiAnalysis_ stating that the turbines were produced by South Korea’s Doosan Enerbility. As noted in an Asian Business Daily report, Doosan Enerbility announced last October that it signed a contract to supply two 380 MW gas turbines for a major U.S. tech company. Doosan later noted in December that it secured an order for three more 380 MW gas turbines.
As per the X user, the gas turbines would power an additional 600,000+ GB200 NVL72 equivalent size cluster. This should make xAI’s facilities among the largest in the world. In a reply, Elon Musk confirmed that xAI did purchase the turbines. “True,” Musk wrote in a post on X.
xAI’s ambitions
Recent reports have indicated that xAI closed an upsized $20 billion Series E funding round, exceeding the initial $15 billion target to fuel rapid infrastructure scaling and AI product development. The funding, as per the AI startup, “will accelerate our world-leading infrastructure buildout, enable the rapid development and deployment of transformative AI products.”
The company also teased the rollout of its upcoming frontier AI model. “Looking ahead, Grok 5 is currently in training, and we are focused on launching innovative new consumer and enterprise products that harness the power of Grok, Colossus, and 𝕏 to transform how we live, work, and play,” xAI wrote in a post on its website.
Elon Musk
Elon Musk’s xAI closes upsized $20B Series E funding round
xAI announced the investment round in a post on its official website.
xAI has closed an upsized $20 billion Series E funding round, exceeding the initial $15 billion target to fuel rapid infrastructure scaling and AI product development.
xAI announced the investment round in a post on its official website.
A $20 billion Series E round
As noted by the artificial intelligence startup in its post, the Series E funding round attracted a diverse group of investors, including Valor Equity Partners, Stepstone Group, Fidelity Management & Research Company, Qatar Investment Authority, MGX, and Baron Capital Group, among others.
Strategic partners NVIDIA and Cisco Investments also continued support for building the world’s largest GPU clusters.
As xAI stated, “This financing will accelerate our world-leading infrastructure buildout, enable the rapid development and deployment of transformative AI products reaching billions of users, and fuel groundbreaking research advancing xAI’s core mission: Understanding the Universe.”
xAI’s core mission
Th Series E funding builds on xAI’s previous rounds, powering Grok advancements and massive compute expansions like the Memphis supercluster. The upsized demand reflects growing recognition of xAI’s potential in frontier AI.
xAI also highlighted several of its breakthroughs in 2025, from the buildout of Colossus I and II, which ended with over 1 million H100 GPU equivalents, and the rollout of the Grok 4 Series, Grok Voice, and Grok Imagine, among others. The company also confirmed that work is already underway to train the flagship large language model’s next iteration, Grok 5.
“Looking ahead, Grok 5 is currently in training, and we are focused on launching innovative new consumer and enterprise products that harness the power of Grok, Colossus, and 𝕏 to transform how we live, work, and play,” xAI wrote.
Nvidia CEO Jensen Huang explains difference between Tesla FSD and Alpamayo
Elon Musk confirms xAI’s purchase of five 380 MW natural gas turbines
