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Tesla FSD Beta 10.69 release notes highlight better left turns, smoother driving
Tesla released FSD Beta 10.69 to the first round of testers over the weekend. Read v.10.69’s release notes below to check out the latest improvements.
Stay in your Lanes
- Added a new “deep lane guidance” module to the Vector Lanes neural network which fuses features extracted from the video streams with coarse map data, i.e. lane counts and lane connectivites. This architecture achieves a 44% lower error rate on lane topology compared to the previous model, enabling smoother control before lanes and their connectivities becomes visually apparent. This provides a way to make every Autopilot drive as good as someone driving their own commute, yet in a sufficiently general way that adapts for road changes.
Nothing Like Smooth Driving
- Improved overall driving smoothness, without sacrificing latency, through better modeling of system and actuation latency in trajectory planning. Trajectory planner now independently accounts for latency from steering commands to actual steering actuation, as well as acceleration and brake commands to actuation. This results in a trajectory that is a more accurate model of how the vehicle would drive. This allows better downstream controller tracking and smoothness while also allowing a more accurate response during harsh manevuers.
- Increased smoothness for protected right turns by improving the association of traffic lights with slip lanes vs yield signs with slip lanes. This reduces false slowdowns when there are no relevant objects present and also improves yielding position when they are present.
- Reduced false slowdowns near crosswalks. This was done with improved understanding of pedestrian and bicyclist intent based on their motion.
- Enabled creeping for visibility at any intersection where objects might cross ego’s path, regardless of presence of traffic controls.
- Improved accuracy of stopping position in critical scenarios with crossing objects, by allowing dynamic resolution in trajectory optimization to focus more on areas where finer control is essential.
- Reduced latency when starting from a stop by accounting for lead vehicle jerk.
Chuck’s Left Turn
- Improved unprotected left turns with more appropriate speed profile when approaching and exiting median crossover regions, in the presence of high speed cross traffic (“Chuck Cook style” unprotected left turns). This was done by allowing optimizable initial jerk, to mimic the harsh pedal press by a human, when required to go in front of high speed objects. Also improved lateral profile approaching such safety regions to allow for better pose that aligns well for exiting the region. Finally, improved interaction with objects that are entering or waiting inside the median crossover region with better modeling of their future intent.
Safety is Number 1
- Added control for arbitrary low-speed moving volumes from Occupancy Network. This also enables finer control for more precise object shapes that cannot be easily represented by a cuboid primitive. This required predicting velocity at every 3D voxel. We may now control for slow-moving UFOs.
- Made speed profile more comfortable when creeping for visibility, to allow for smoother stops when protecting for potentially occluded objects.
- Improved speed when entering highway by better handling of upcoming map speed changes, which increases the confidence of merging onto the highway.
- Enabled faster identification of red light runners by evaluating their current kinematic state against their expected braking profile.
Tesla FSD “Brain” Improvements
- Upgraded Occupancy Network to use video instead of images from single time step. This temporal context allows the network to be robust to temporary occlusions and enables prediction of occupancy flow. Also, improved ground truth with semantics-driven outlier rejection, hard example mining, and increasing the dataset size by 2.4x.
- Upgraded to a new two-stage architecture to produce object kinematics (e.g. velocity, acceleration, yaw rate) where network compute is allocated O(objects) instead of O(space). This improved velocity estimates for far away crossing vehicles by 20%, while using one tenth of the compute.
- Improved geometry error of ego-relevant lanes by 34% and crossing lanes by 21% with a full Vector Lanes neural network update. Information bottlenecks in the network architecture were eliminated by increasing the size of the per-camera feature extractors, video modules, internals of the autoregressive decoder, and by adding a hard attention mechanism which greatly improved the fine position of lanes.
- Improved recall of animals by 34% by doubling the size of the auto-labeled training set.
- Increased recall of forking lanes by 36% by having topological tokens participate in the attention operations of the autoregressive decoder and by increasing the loss applied to fork tokens during training.
- Improved velocity error for pedestrians and bicyclists by 17%, especially when ego is making a turn, by improving the onboard trajectory estimation used as input to the neural network.
- Improved recall of object detection, eliminating 26% of missing detections for far away crossing vehicles by tuning the loss function used during training and improving label quality.
- Improved object future path prediction in scenarios with high yaw rate by incorporating yaw rate and lateral motion into the likelihood estimation. This helps with objects turning into or away from ego’s lane, especially in intersections or cut-in scenarios.
Tesla is rolling out FSD Beta v.10.69 in phases, starting with ~1,000 testers over the weekend. Once the update is rolled out for wide release, the price of FSD Beta will increase.
The Teslarati team would appreciate hearing from you. If you have any tips, contact me at maria@teslarati.com or via Twitter @Writer_01001101.
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Tesla Cybercab production begins: The end of car ownership as we know it?
While this could unlock unprecedented mobility abundance — cheaper rides, reduced congestion, freed-up urban space, and massive environmental gains — it risks massive job displacement in ride-hailing, taxi services, and related sectors, forcing society to confront whether the benefits of AI-driven autonomy will outweigh the human costs.
The first Tesla Cybercab rolled off of production lines at Gigafactory Texas yesterday, and it is more than just a simple manufacturing milestone for the company — it’s the opening salvo in a profound economic transformation.
Priced at under $30,000 with volume production slated for April, the steering-wheel-free, pedal-less Robotaxi-geared vehicle promises to make personal car ownership optional for many, slashing transportation costs to as little as $0.20 per mile through shared fleets and high utilization.
Credit: wudapig/Reddit< /a>
While this could unlock unprecedented mobility abundance — cheaper rides, reduced congestion, freed-up urban space, and massive environmental gains — it risks massive job displacement in ride-hailing, taxi services, and related sectors, forcing society to confront whether the benefits of AI-driven autonomy will outweigh the human costs.
Let’s examine the positives and negatives of what the Cybercab could mean for passenger transportation and vehicle ownership as we know it.
The Promise – A Radical Shift in Transportation Economics
Tesla has geared every portion of the Cybercab to be cheaper and more efficient. Even its design — a compact, two-seater, optimized for fleets and ride-sharing, the development of inductive charging, around 300 miles of range on a small battery, half the parts of the Model 3, and revolutionary “unboxed” manufacturing — is all geared toward rapid production.
Operating at a fraction of what today’s rideshare prices are, the Cybercab enables on-demand autonomy for a variety of people in a variety of situations.
Tesla ups Robotaxi fare price to another comical figure with service area expansion
It could also be the way people escape expensive and risky car ownership. Buying a vehicle requires expensive monthly commitments, including insurance and a payment if financed. It also immediately depreciates.
However, Cybercab could unlock potential profitability for owning a car by adding it to the Robotaxi network, enabling passive income. Cities could have parking lots repurposed into parks or housing, and emissions would drop as shared electric vehicles would outnumber gas cars (in time).
The first step of Tesla’s massive production efforts for the Cybercab could lead to millions of units annually, turning transportation into a utility like electricity — always available, cheap, and safe.
The Dark Side – Job Losses and Industry Upheaval
With Robotaxi and Cybercab, they present the same negatives as broadening AI — there’s a direct threat to the economy.
Uber, Lyft, and traditional taxis will rely on human drivers. Robotaxi will eliminate that labor cost, potentially displacing millions of jobs globally. In the U.S. alone, ride-hailing accounts for billions of miles of travel each year.
There are also potential ripple effects, as suppliers, mechanics, insurance adjusters, and even public transit could see reduced demand as shared autonomy grows. Past automation waves show job creation lags behind destruction, especially for lower-skilled workers.
Gig workers, like those who are seeking flexible income, face the brunt of this. Displaced drivers may struggle to retrain amid broader AI job shifts, as 2025 estimates bring between 50,000 and 300,000 layoffs tied to artificial intelligence.
It could also bring major changes to the overall competitive landscape. While Waymo and Uber have partnered, Tesla’s scale and lower costs could trigger a price war, squeezing incumbents and accelerating consolidation.
Balancing Act – Who Wins and Who Loses
There are two sides to this story, as there are with every other one.
The winners are consumers, Tesla investors, cities, and the environment. Consumers will see lower costs and safer mobility, while potentially alleviating themselves of awkward small talk in ride-sharing applications, a bigger complaint than one might think.
Elon Musk confirms Tesla Cybercab pricing and consumer release date
Tesla investors will be obvious winners, as the launch of self-driving rideshare programs on the company’s behalf will likely swell the company’s valuation and increase its share price.
Cities will have less traffic and parking needs, giving more room for housing or retail needs. Meanwhile, the environment will benefit from fewer tailpipes and more efficient fleets.
A Call for Thoughtful Transition
The Cybercab’s production debut forces us to weigh innovation against equity.
If Tesla delivers on its timeline and autonomy proves reliable, it could herald an era of abundant, affordable mobility that redefines urban life. But without proactive policies — retraining, safety nets, phased deployment — this revolution risks widening inequality and leaving millions behind.
Elon on the MKBHD bet, stating “Yes” to the question of whether Tesla would sell a Cybercab for $30k or less to a customer before 2027 https://t.co/sfTwSDXLUN
— TESLARATI (@Teslarati) February 17, 2026
The real question isn’t whether the Cybercab will disrupt — it’s already starting — it’s whether society is prepared for the economic earthquake it unleashes.
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Tesla Model 3 wins Edmunds’ Best EV of 2026 award
The publication rated the Model 3 at an 8.1 out of 10, and with its most recent upgrades and changes, Edmunds says, “This is the best Model 3 yet.”
The Tesla Model 3 has won Edmunds‘ Top Rated Electric Car of 2026 award, beating out several other highly-rated and exceptional EV offerings from various manufacturers.
This is the second consecutive year the Model 3 beat out other cars like the Model Y, Audi A6 Sportback E-tron, and the BMW i5.
The car, which is Tesla’s second-best-selling vehicle behind the popular Model Y crossover, has been in the company’s lineup for nearly a decade. It offers essentially everything consumers could want from an EV, including range, a quality interior, performance, and Tesla’s Full Self-Driving suite, which is one of the best in the world.
The Tesla Model 3 has won Edmunds Top EV of 2026:
“The Tesla Model 3 might be the best value electric car you can buy, combining an Edmunds Rating of 8.1 out of 10, a starting price of $43,880, and an Edmunds-tested range of 338 miles. This is the best Model 3 yet. It is… pic.twitter.com/ARFh24nnDX
— TESLARATI (@Teslarati) February 18, 2026
The publication rated the Model 3 at an 8.1 out of 10, and with its most recent upgrades and changes, Edmunds says, “This is the best Model 3 yet.”
In its Top Rated EVs piece on its website, it said about the Model 3:
“The Tesla Model 3 might be the best value electric car you can buy, combining an Edmunds Rating of 8.1 out of 10, a starting price of $43,880, and an Edmunds-tested range of 338 miles. This is the best Model 3 yet. It is impressively well-rounded thanks to improved build quality, ride comfort, and a compelling combination of efficiency, performance, and value.”
Additionally, Jonathan Elfalan, Edmunds’ Director of Vehicle Testing, said:
“The Model 3 offers just about the perfect combination of everything — speed, range, comfort, space, tech, accessibility, and convenience. It’s a no-brainer if you want a sensible EV.”
The Model 3 is the perfect balance of performance and practicality. With the numerous advantages that an EV offers, the Model 3 also comes in at an affordable $36,990 for its Rear-Wheel Drive trim level.
Elon Musk
Elon Musk’s xAI celebrates nearly 3,000 headcount at Memphis site
The update came in a post from the xAI Memphis account on social media platform X.
xAI has announced that it now employs nearly 3,000 people in Memphis, marking more than two years of local presence in the city amid the company’s supercomputing efforts.
The update came in a post from the xAI Memphis account on social media platform X.
In a post on X, xAI’s Memphis branch stated it has been part of the community for over two years and now employs “almost 3,000 locally to help power Grok.” The post was accompanied by a photo of the xAI Memphis team posing for a rather fun selfie.
“xAI is proud to be a member of the Memphis community for over two years. We now employ almost 3,000 locally to help power @Grok. From electricians to engineers, cooks to construction — we’re grateful for everyone on our team!” the xAI Memphis’ official X account wrote.
xAI’s Memphis facilities are home to Grok’s foundational supercomputing infrastructure, including Colossus, a large-scale AI training cluster designed to support the company’s advanced models. The site, located in South Memphis, was announced in 2024 as the home of one of the world’s largest AI compute facilities.
The first phase of Colossus was built out in record time, reaching its initial 100,000 GPU operational status in just 122 days. Industry experts such as Nvidia CEO Jensen Huang noted that this was significantly faster than the typical 2-to-4-year timeline for similar projects.
xAI chose Memphis for its supercomputing operations because of the city’s central location, skilled workforce, and existing industrial infrastructure, as per the company’s statements about its commitment to the region. The initiative aims to create hundreds of permanent jobs, partner with local businesses, and contribute to economic and educational efforts across the area.
Colossus is intended to support a full training pipeline for Grok and future models, with xAI planning to scale the site to millions of GPUs.
Tesla Cybercab production begins: The end of car ownership as we know it?
Tesla Model 3 wins Edmunds’ Best EV of 2026 award
