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
Tesla FSD (Supervised) is about to go on “widespread” release
In a comment last October, Elon Musk stated that FSD V14.2 is “for widespread use.”
Tesla has begun rolling out Full Self-Driving (Supervised) V14.2, and with this, the wide release of the system could very well begin.
The update introduces a new high-resolution vision encoder, expanded emergency-vehicle handling, smarter routing, new parking options, and more refined driving behavior, among other improvements.
FSD V14.2 improvements
FSD (Supervised) V14.2’s release notes highlight a fully upgraded neural-network vision encoder capable of reading higher-resolution features, giving the system improved awareness of emergency vehicles, road obstacles, and even human gestures. Tesla also expanded its emergency-vehicle protocols, adding controlled pull-overs and yielding behavior for police cars, fire trucks, and ambulances, among others.
A deeper integration of navigation and routing into the vision network now allows the system to respond to blocked roads or detours in real time. The update also enhances decision-making in several complex scenarios, including unprotected turns, lane changes, vehicle cut-ins, and interactions with school buses. All in all, these improvements should help FSD (Supervised) V14.2 perform in a very smooth and comfortable manner.
Elon Musk’s predicted wide release
The significance of V14.2 grows when paired with Elon Musk’s comments from October. While responding to FSD tester AI DRIVR, who praised V14.1.2 for fixing “95% of indecisive lane changes and braking” and who noted that it was time for FSD to go on wide release, Musk stated that “14.2 for widespread use.”
FSD V14 has so far received a substantial amount of positive reviews from Tesla owners, many of whom have stated that the system now drives better than some human drivers as it is confident, cautious, and considerate at the same time. With V14.2 now rolling out, it remains to be seen if the update also makes it to the company’s wide FSD fleet, which is still populated by a large number of HW3 vehicles.
News
Tesla FSD V14.2 starts rolling out to initial batch of vehicles
It would likely only be a matter of time before FSD V14.2 videos are posted and shared on social media.
Tesla has begun pushing Full Self-Driving (Supervised) v14.2 to its initial batch of vehicles. The update was initially observed by Tesla owners and veteran FSD users on social media platform X on Friday.
So far, reports of the update have been shared by Model Y owners in California whose vehicles are equipped with the company’s AI4 hardware, though it would not be surprising if more Tesla owners across the country receive the update as well.
Based on the release notes of the update, key improvements in FSD V14.2 include a revamped neural network for better detection of emergency vehicles, obstacles, and human gestures, as well as options to select arrival spots.
It would likely only be a matter of time before FSD V14.2 videos are posted and shared on social media.
Following are the release notes of FSD (Supervised) V14.2, as shared on X by longtime FSD tester Whole Mars Catalog.
Release Notes
2025.38.9.5
Currently Installed
FSD (Supervised) v14.2
Full Self-Driving (Supervised) v14.2 includes:
- Upgraded the neural network vision encoder, leveraging higher resolution features to further improve scenarios like handling emergency vehicles, obstacles on the road, and human gestures.
- Added Arrival Options for you to select where FSD should park: in a Parking Lot, on the Street, in a Driveway, in a Parking Garage, or at the Curbside.
- Added handling to pull over or yield for emergency vehicles (e.g. police cars, fire trucks, ambulances.
- Added navigation and routing into the vision-based neural network for real-time handling of blocked roads and detours.
- Added additional Speed Profile to further customize driving style preference.
- Improved handling for static and dynamic gates.
- Improved offsetting for road debris (e.g. tires, tree branches, boxes).
- Improve handling of several scenarios including: unprotected turns, lane changes, vehicle cut-ins, and school busses.
- Improved FSD’s ability to manage system faults and improve scenarios like handling emergency vehicles, obstacles on the road, and human gestures.
- Added Arrival Options for you to select where FSD should park: in a Parking Lot, on the Street, in a Driveway, in a Parking Garage, or at the Curbside.
- Added handling to pull over or yield for emergency vehicles (e.g. police cars, fire trucks, ambulances).
- Added navigation and routing into the vision-based neural network for real-time handling of blocked roads and detours.
- Added additional Speed Profile to further customize driving style preference.
- Improved handling for static and dynamic gates.
- Improved offsetting for road debris (e.g. tires, tree branches, boxes).
- Improve handling of several scenarios, including unprotected turns, lane changes, vehicle cut-ins, and school buses.
- Improved FSD’s ability to manage system faults and recover smoothly from degraded operation for enhanced reliability.
- Added alerting for residue build-up on interior windshield that may impact front camera visibility. If affected, visit Service for cleaning!
Upcoming Improvements:
- Overall smoothness and sentience
- Parking spot selection and parking quality
The Tesla Model X has always been one of the company’s most loved vehicles, despite its low sales figures, which can be attributed to its high price tag.
However, the Model X has been a signature item on Tesla’s menu of cars, most notably recognized by its Falcon Wing Doors, which are aware of its surroundings and open according to what’s around it.
But recent improvements to the Model X were looking slim to none, but it appears most of the fixes actually happened under the body, at least according to Tesla’s Vice President of Powertrain, Lars Moravy.
In a recent interview with Car and Driver, Moravy detailed all of the changes to the 2026 iteration of the vehicle, which was about 400 pounds lighter than it was originally. The biggest change is a modification with the rear motor, switching from an induction-type motor to a permanent-magnet design and optimizing the half-shafts, which shed about 100 pounds.
Tesla also got “almost 80 pounds out of the interior bits and pieces,” which “included making parts thinner, different manufacturing process choices, and incorporating airbag-deployment requirements into the headliner fabric,” the report said.
Additionally, the standard five-passenger, bench seat configuration saved 50 pounds by ditching pedestal mounting. This also helped with practicality, as it helped the seat fold flat. Engineers at Tesla also saved 44 pounds from the high-voltage wiring through optimizing the wiring from the charge-port DC/DC converter and switching from copper to aluminum wiring.
Tesla makes a decision on the future of its flagship Model S and Model X
Tesla also simplified the cooling system by reducing the number of radiators. It also incorporated Nürburgring cooling requirements for the Plaid variant, which saved nearly 30 pounds.
Many Tesla fans will be familiar with the megacastings, manufactured in-house by presses from IDRA, which also saves more than 20 pounds and boosts torsional stiffness by around 10 percent. Tweaks to the suspension also saved 10 pounds.
People were truly disappointed with what Tesla did with the Model S and Model X, arguing that the cars needed a more severe exterior overhaul, which might be true. However, Tesla really did a lot to reduce the weight of the vehicle, which helps increase range and efficiency. According to Grok, every 200 pounds removed adds between 7 and 15 percent to range estimations.
This makes sense considering the range estimations both increased by 7 percent from the Model X’s 2025 configuration to the 2026 builds. Range increased on the All-Wheel-Drive trim from 329 miles to 352 miles, while the Plaid went from 314 miles to 335 miles.
Tesla FSD (Supervised) is about to go on “widespread” release
Tesla FSD V14.2 starts rolling out to initial batch of vehicles
