Tesla to Introduce New Paint Options for New Model Y in North America

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Tesla introduced the Refreshed Model Y in North America with just four colors - Stealth Grey, Pearl White Multi-Coat, Ultra Red, and Quicksilver. While those are likely some of the most popular colors - many have been asking - what about new color options?

Actually - what even happened to Deep Blue Metallic - one of the most popular Tesla color choices? Well, thanks to an interview between Tesla Owners Club Silicone Valley and some of Tesla’s vehicle engineers, we now have more details.

New Paint Options

More paint options are around the corner for the new Model Y, but they won’t be available just yet. In fact, they’ll likely be available once the Launch-Series wraps up - as those vehicles are shipping in May.

One of Tesla’s latest colors, Glacier Blue, debuted in the Asia-Pacific market, but for now, North America remains limited to a select set of options. Deep Blue Metallic continues to be one of Tesla’s most popular choices, and black is also a favorite, though it is currently unavailable for new Model Y orders.

In a recent interview, Tesla’s engineering team confirmed that new colors are already being developed. However, the key factor delaying their availability is production ramp-up. Just as scaling vehicle production takes time, expanding paint production capacity is a gradual process. Tesla is prioritizing a smooth production ramp before adding more color options to the lineup.

New Color Hints

The engineering team also mentioned that if you “put two and two together” while browsing the website, it will be pretty evident which colors are coming. This suggests that the new colors will not be completely new but will be colors that are available on other models or in other regions. The primary candidates are Glacier Blue, which is available in Asia, and Deep Blue Metallic and Black, which are available for the now, last-gen Model Y.

It seems like once production ramps up, Tesla will be ready to introduce some new paint options. Maybe they’ll introduce them alongside the expected refreshed Model Y Performance? If you’re in the market for a paint option that isn’t available in North America just yet - it could be best just to wait a few months.

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Tesla Increases Price of Model S and Model X; Adds Incentives

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Tesla vehicle prices always fluctuate for a variety of reasons, including demand, currency adjustments, production, and other reasons. However, out of the blue, Tesla has now raised the price for the Model X and Model S in North America and Europe.

Price Changes

The Model X recently hit one of its lowest prices, with the Long Range variant priced at $79,990—just below the federal EV tax credit threshold. This meant eligible buyers could claim an additional $7,500 rebate, making it an even more attractive deal.

Now, it’s a double blow: Tesla has increased the Long Range Model X price to $84,990, pushing it above the tax credit limit. As a result, some buyers could see an effective price hike of $12,500, making the vehicle significantly more expensive.

The Model X Plaid sees even more of an increase, with it going from $89,990 to $99,990. The increases aren’t just in the U.S., but also affect Canada and most of Europe as well. Just two weeks ago, Canada raised their vehicle prices of the Model S and X by $4,000 CAD to account for currency fluctuations.

Here are the price changes before taking into account any tax rebates or taxes.

American Price Changes

Canadian Price Changes

European Price Changes

Free Supercharging & Premium Connectivity

Although these price changes are disappointing for anyone in the market, Tesla is adding a few incentives. Every Model S and Model X now come with Lifetime Free Supercharging, something Tesla was previously going away from to prevent Supercharger congestion.

Tesla is also including free Premium Connectivity, which normally costs $10/month or $99/year. So there are certainly some savings to be had by buying the now more expensive model.

It’s worth noting that even with free Supercharging, owners are not exempt from congestion or idle fees. Those fees are there to prevent drivers from blocking Superchargers for extended periods of time, so they apply to everyone.

Why the Price Adjustment

It’s not clear where this change is coming from. The Model S and Model X have dwindling sales, partly due to the Model 3 and Model Y offering more of the features that used to be exclusive to the Model S/X, like ventilated seats. However, the Cybertruck is likely also causing sales to dip for the Model X, as they’re both larger vehicles.

All Model S and Model X vehicles are produced in Fremont, California, so the price increase outside of the U.S. isn’t as surprising since Tesla likely wants to fill demand in the U.S. first, where it’s cheaper for them to get cars to their final destination.

With Tesla selling just 84,133 Model S, Model X, and Cybertruck vehicles in all of 2024, it’s certainly possible that Tesla is planning to phase these vehicles out to reduce logistics and make room for new models at their existing factories. For comparison, Tesla sold 1.7 million Model 3 and Model Y vehicles in 2024.

As Tesla sales slump in January, we’ll have to see how these new prices affect sales.

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How Tesla Will Automate Data Labeling for FSD

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In our continued series exploring Tesla’s patents, we’re taking a look at how Tesla automates data labeling for FSD. This is Tesla patent WO2024073033A1, which outlines a system that could revolutionize how Tesla trains FSD.

We’ll be approaching this article the same way as others in the past, by breaking it down into easily digestible portions.

If you missed out on previous articles, you can dive into how FSD works or look at Tesla’s Universal Translator.

The Challenge of Data Labelling

Training a sophisticated AI model like FSD requires a tremendous amount of data. But all of that data needs to be labeled - and traditionally, this process has been done manually. Human reviewers have to go in and categorize and tag hundreds of thousands of data points across millions of hours of video. 

This isn’t just laborious and rote work, it's time consuming, expensive, and prone to human error. The perfect job to hand off to AI.

Tesla’s Automated Solution

Tesla’s patent introduces a model-agnostic system for automated data labeling. Just like their previous patent on the Universal Translator, this will function for any AI model - but FSD is really what it is for.

The system works by leveraging the vast amounts of data collected by Tesla’s fleet to create a 3D model of the environment, which is then automatically used to label new data.

Three Step Process

This process has three steps, so we’ll look at each individually.

High-Precision Mapping

The system starts by creating a highly accurate 3D map of the environment. This involves fusing data from multiple Tesla vehicles equipped with cameras, radar, and other sensors. The map includes detailed information about roads, lane markings, buildings, trees, and other static objects. 

It's like creating a digital twin of the real world, and this is exactly the simulation data that Tesla uses to rapidly test FSD. The system continuously improves its accuracy as it processes more data and also generates better synthetic data to augment the training dataset.

Multi-Trip Reconstruction

To refine the 3D model and capture dynamic elements of the environment, the system analyzes data from multiple trips through the same area. This allows it to identify moving objects, track their trajectories, and understand how they interact with the static environment. This way, you have a dynamic, living 3D world that also captures the ebb and flow of traffic and pedestrians.

Automated Labelling

Once the 3D model is sufficiently detailed, it becomes the key to automated labeling. When a Tesla vehicle encounters a new scene, the system compares the real-time sensor data with the existing 3D model. This allows it to automatically identify and label objects, lane markings, and other relevant features in the new data. 

Benefits

There are three simple benefits to this system, which is what makes it so valuable.

1. It is far more efficient. Automated data labeling drastically reduces the time and resources required to prepare training data for AI models. This accelerates development cycles and allows Tesla to train its AI on much larger datasets.

2. It is also scalable. This system can handle massive datasets derived from millions of miles of driving data collected by Tesla's fleet. As the fleet grows and collects more data, the 3D models become even more detailed and accurate, further improving the automated labeling process.

3. Finally, it is accurate. By eliminating human error and bias, automated labeling improves the accuracy and consistency of the labeled data. This leads to more robust and reliable AI models. Of course, human review is still involved, but that’s only to catch and flag errors.

Applications

While this technology has significant implications for FSD, Tesla can use this automated labeling system to train AI models for various tasks.

Object detection and classification: Accurately identifying and categorizing objects in the environment, such as vehicles, pedestrians, traffic signs, and obstacles.

Kinematic analysis: Understanding the motion and behavior of objects, predicting their trajectories, and anticipating potential hazards.

Shape analysis: Recognizing the shapes and structures of objects, even when partially obscured or viewed from different angles.

Occupancy and surface detection: Creating detailed maps of the environment, identifying occupied and free space, and understanding the properties of different surfaces (e.g., road, sidewalk, grass).

These different applications are all used by Tesla - which uses different AI subnets to analyze all these different things before feeding them into the greater model that is FSD, which means things like pedestrians, lane markings, and traffic controls are all labeled on-vehicle.

In a Nutshell

Tesla's automated data labeling system is a game-changer for AI development. By leveraging the power of its fleet and 3D mapping technology, Tesla has created a self-learning system that continuously improves its ability to understand and navigate the world.

Imagine a world where self-driving cars can label and understand the world around them without human help.  This patent describes a system that could make that possible. It uses data collected from many Tesla vehicles to create a 3D model of the environment, which is like a virtual copy of the real world.  

This 3D model is then used to label new images and sensor data, eliminating most needs for human intervention. The system can recognize objects, lane markings, and other important features, making it easier to train AI models.

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