Connect with us

News

Tesla 3D labeling is the next big leap for Autopilot

Tesla Autopilot (Source: Elon Musk | Twitter)

Published

on

Tesla’s 3D labeling efforts are integral to the development of its Full Self-Driving suite. Using over 2.2 billion miles of real-world driving data from its electric vehicle fleet, the electric car maker has a treasure trove of information about how human drivers behave.

Elon Musk recently confirmed that Tesla is finishing work on Autopilot core foundation code and 3D labeling, and once these are done, users can expect the electric carmaker to roll out more functionalities in a potentially more efficient manner. More advanced features such as Reverse Summon will also be rolled out.

Tesla 3D Labeling: The Next Big Thing

The Tesla CEO has tagged 3D labeling as the next big thing for the company’s efforts to achieve full self-driving. “In terms of labeling, labeling with video in all eight cameras simultaneously. This is a really, I mean in terms of labeling efficiency, arguably like a three order of magnitude improvement in labeling efficiency where Tesla vehicles use all of its eight cameras simultaneously, and that the company has improved significantly in terms of labeling efficiency,” Musk said during the Q4 2019 earnings call.

During Autonomy Day last year, Tesla’s AI head Andrej Karpathy gave the electric vehicle community an idea of how labeling is done. He said annotating data is a very expensive process that initially involved people processing data, but Tesla has also been using information from its fleet to automate the process of labeling using different mechanisms.

For example, in predicting cut-ins, Tesla taps into its fleet for data on such incidents. This information is then automatically annotated and used to train the neural network, which in turn learns from recognizable patterns. This information is then spun until the neural network is trained enough. Improvements in the neural network can then be rolled out as an update for Autopilot.

The same is true according to Karpathy when it comes to object detection. Tesla sources data from its fleet to learn more about different objects and anomalies on the road. With automated 3D labeling, the neural network can more efficiently process the information and learn even about the rarest things one can encounter on the road.

Advertisement
-

Karpathy and Musk explained how annotations from its fleet help with path prediction. Using trajectories collected from the real-world, the neural network can improve its driving behavior, say while approaching a corner that it doesn’t actively see. This smarter neural network is perfectly demonstrated by an older Model X with early-gen Autopilot negotiating a muddy rural backroad recently, after a storm in the United Kingdom.

All of these things form part of the equation to achieve Full Self-Driving capabilities. Likely through 3D labeling improvements in the past year or so, Tesla has immensely improved driving visualizations in vehicles equipped with Hardware 3, which now identify traffic lights, garbage cans, and detailed road markings, among others. Thus, Elon Musk’s explanation about rewriting the Autopilot foundational code and 3D labeling could be a way of emphasizing that Tesla owners’ investment in the company’s Full Self-Driving suite would be proven worth it and more soon.

Tesla’s FSD computer and autonomy software will transform how humans travel. The company’s vehicles will be smart enough to drive like humans and eventually make the roads a few times safer for everyone. This may also pave the way for Robotaxis and help achieve Musk’s vision of Teslas earning for their owners while they are busy with work or even while relaxing at home. Tesla Robotaxis would be an attractive form of transportation as they will be more cost-efficient compared to driving personal cars, as predicted by ARK Invest.

Autonomy As Key To Profitability

Autonomy will spell profits for Tesla, as Elon Musk explained during the company’s Q4 2019 earnings call. In order to achieve sustained profitability, Tesla needs to produce high volume units with high margins. Musk appears to consider autonomy as key to Tesla’s high margins as well.

“As we’re close to Full Self-Driving, that is just going to become more and more compelling. So that’s for our financial standpoint, that’s the real mind-blowing situation is high-volume, high-margin because of autonomy,” Musk said.

With FSD capabilities, Tesla adds more value proposition that can help sway even more customers to purchase its electric vehicles from the Model 3, Model Y, Model S, Model X, or the Cybertruck. Depending on regulations in specific regions, Tesla can tap into most of its earnings potential, which bodes well since the company has current plans to expand its presence worldwide with Gigafactories in multiple regions.

Advertisement
-

Tesla’s path to autonomy is only one of the aspects that make it the leader in the electric vehicle industry. Add to that its advancements on car connectivity and battery technology and one will complete the equation why legacy carmakers with the deepest of pockets can only watch in amazement as a relatively young electric car maker dominates the emerging EV industry.

A curious soul who keeps wondering how Elon Musk, Tesla, electric cars, and clean energy technologies will shape the future, or do we really need to escape to Mars.

Advertisement
Comments

Investor's Corner

Tesla has a Cybercab problem nobody saw coming

Tesla’s Cybercab line now builds robotaxis faster than Tesla can deploy them, Lars Moravy says.

Published

on

By

Tesla’s Cybercab line in Texas can now build the two seat robotaxi faster than the company can put it into service, according to Lars Moravy, Tesla’s Vice President of Vehicle Engineering. “We don’t run every day because the line can run so fast. It’s currently outpacing our deployments,” Moravy said in a new Cybercab deep dive from Munro Live. “So, it’s a bit of a race right now. Who’s going to go faster? Right now the manufacturing line’s ahead.”

Tesla’s official Robotaxi account shared a Cybercab analysis video on X on Monday, calling it a “Cybercab engineering deep dive.” Moravy’s comments go further than what he told analysts on the Q3 earnings call last week, when he said the Cybercab line’s listed capacity of more than 125,000 units a year undersells what it can actually run.

The tour shows where that speed comes from. Tesla’s unboxed process splits the Cybercab into front, rear, side and center modules that are built and tested on their own before they meet on a short final line. That final line has just 25 fully automated stations, which Tesla’s team estimated is a fifth to a tenth of what a Model Y needs. The full line is about 78% automated, the framing line is already at 100%, and the layout uses roughly 50% less floor space per vehicle. The stated goal is “100% automation in 10 second cycle time,” or one finished Cybercab every 10 seconds.

Tesla also deleted the paint shop. Only the side modules are coated, and the exterior panels get their color inside the molding machine. Engineers said the car is designed to run at least 500,000 miles, which matters for a vehicle that will spend most of its day carrying riders.

The battery got the same treatment. The Cybercab uses an 88S6P pack of 4680 cells in a steel enclosure, a first for Tesla, with each module potted separately so a single failed module can be swapped instead of the whole pack. Wireless battery management boards replace a wiring harness, and new contactors are fast enough to drop the pyro fuse entirely. Tesla’s battery director graded the pack an A minus, compared with a D for the Model Y structural pack and a B minus for Cybertruck. Up front, the drive unit runs an 11:1 gear ratio versus roughly 9:1 on most Teslas, since the Cybercab does not need a high top speed.

Advertisement
-

The deployment side is now the bottleneck Moravy described. Tesla had more than 50 Cybercabs working the Formula 1 weekend in Austin, and Texas records show 463 Cybercabs registered. Tesla said on its earnings call that Cybercab service will launch in Dallas next month, and Moravy said the company is aiming to get Cybercabs to customers by the end of 2026. Every unit built so far has gone into Tesla’s own fleet since the line moved into volume production in April.

Munro Live also asked when it could get a Cybercab to tear down. Tesla’s answer: “Not yet.”

Continue Reading

Elon Musk

How SpaceX Is raising Raptor’s sea-level thrust while holding engine mass steady

Published

on

Credit: SpaceX

SpaceX’s Raptor engine family has steadily increased sea-level thrust while simultaneously reducing mass, turning iterative engineering gains into substantially higher performance for the Super Heavy booster. CEO Elon Musk shed more light on how powerful Raptor 4 will be, and it’s pretty crazy.

Raptor 1 delivered 185 metric tons of thrust at roughly 2,080 kilograms, while Raptor 2 raised that to 230 tons while cutting mass to about 1,630 kilograms. SpaceX data for Raptor 3 lists a target of 280 tons at 1,525 kilograms (with further reductions in associated vehicle hardware), while operational flight ratings have been cited near 250 tons.

This morning, Elon Musk stated that Raptor 4 is expected to reach 300 tons of sea-level thrust at roughly the same mass as Raptor 3. Across these versions, thrust has risen by more than 60 percent from the first engines while engine mass has fallen, producing a sharp improvement in thrust-to-weight ratio. This is a true testament to how great SpaceX engineering has been:

With 33 engines on SuperHeavy, the jump from earlier versions to a 300-ton Raptor 4 would produce roughly 9,900 metric tons of total liftoff thrust, nearly three times the Saturn V’s approximately 3,400 metric tons from its five F-1 engines.

This is not just a larger number on a data sheet, either, as sea-level thrust is the force available the moment the vehicle leaves the pad. This is when it is heaviest and still deep in Earth’s gravity well and dense atmosphere.

Higher levels of sea-level thrust directly improves the initial thrust-to-weight ratio of the full stack. A higher ratio produces faster acceleration off the pad, which shortens the time the rocket has to spend fighting gravity, and gravity losses during the first minute or two of the flight are a major drain on total available delta-v. Every second shaved off of that early climb preserves more propellant energy for reaching orbital velocity or for carrying extra payload.

Because Super Heavy’s engine count is constrained by vehicle diameter and packing density, increasing thrust per engine is the most straightforward way to raise total liftoff performance without redesigning the booster structure or design.

The same-mass target for Raptor 4 is equally important. Holding engine mass roughly constant while raising thrust improves the engine’s own thrust-to-weight ratio and reduces the structural and propellant mass fraction that must be carried solely to support the engines.

Earlier Raptor iterations also simplified or eliminated extensive vehicle-side hardware such as heat shields. These gains compound: more force for less installed mass leaves additional capacity for propellant, payload, or operational margins such as engine-out capability.

For Starship’s architecture, the practical effects are large. Greater liftoff thrust supports heavier vehicles, larger propellant loads, and higher payloads to low Earth orbit, figures SpaceX has targeted in the 100-plus-ton reusable range. That capacity underpins orbital refueling, lunar missions, and eventual Mars cargo and crew flights.

Continued growth in sea-level thrust therefore tightens the gap between theoretical rocket performance and the high flight rates and reusability needed to make large-scale space transport practical.

Continue Reading

News

Tesla Assisted Driving expands to tenth EU country

Published

on

Tesla has expanded its Tesla Assisted Driving (TAD) suite to its tenth European country, as Latvia joined a growing list of European Union member states authorizing the company’s advanced driver assistance technology.

Tesla Europe announced this morning that the system is now approved in Latvia, with a software rollout to begin soon.

The approval and rollout follow recognition of a provisional European type approval originally granted by the Netherlands’ RDW authority on April 10.

Latvia’s Road Traffic Safety Directorate (CSDD) evaluated the Dutch documentation, coordinated with the other national authorities, and reviewed updates from Tesla. These included tightened limits on speed offsets, automatic resets of any manual speed adjustments after each trip, and stronger driver monitoring.

In Europe, the feature is marketed as Tesla Assisted Driving after a recent rule change that labeled the name “Full Self-Driving” as misleading.

Tesla starts showing how FSD will change lives in Europe

The system remains an SAE Level 2 driver assistance tool, not unsupervised autonomy. It can control speed, steering, braking, lane changes, and intersections while following a navigation route. Drivers need not keep their hands on the wheel at all times, yet they must continuously monitor the road and be prepared to intervene immediately.

The sequence of EU recognitions began with the Netherlands in April and continued through Lithuania, Estonia, Denmark, Belgium, Slovenia, Czechia, Croatia, and Slovakia. Most have relied on mutual recognition of the single Dutch provisional approval rather than independent national testing.

These national clearances do not yet constitute bloc-wide authorization. An EU-wide decision requires a qualified majority in the Technical Committee on Motor Vehicles: at least 15 of 27 member states representing 65 percent of the EU population. Larger markets, like Germany, France, and Italy, remain under review, and a vote is expected this December.

However, for Latvian Tesla owners with compatible vehicles and software, the imminent rollout expands access to the supervised system while underscoring that attentive human oversight remains essential.

Continue Reading