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Tesla’s Elon Musk will be hosting an AI hackathon party at his house
Elon Musk announced that Tesla will be hosting an AI hackathon, together with the company’s artificial intelligence and autopilot team, at his house in four weeks’ time.
The Tesla chief announced his plans via Twitter on Sunday. Despite impressive numbers revealed during the Q4 2019 earnings call and update, Musk and his Tesla team are not resting on their laurels and remain focused on pursuing advancements to its neural network, which is in the center of Tesla’s goal of achieving a full self-driving vehicle.
During the recent Q4 earnings call, an investor asked the Tesla chief executive for updates on FSD.
“I think that’s looking like maybe it’s going to be couple of months from now. And what isn’t obvious regarding Autopilot and Full Self-Driving is just how much work has been going into improving the foundational elements of autonomy,” Musk said.
Tesla will hold a super fun AI party/hackathon at my house with the Tesla AI/autopilot team in about four weeks. Invitations going out soon.
— Elon Musk (@elonmusk) February 2, 2020
Musk continued to explain how the Tesla team is making great strides in labeling efficiency.
“…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. For those who know about this, it’s extremely fundamental, so that’s really great progress on that,” Musk said.
Tesla vehicles rely on a custom chip that boasts of 144 tera operations per second (TOPS) for its self-driving capabilities. This two-chip FSD computer works in tandem with LPDDR4 RAM modules that come with a peak bandwidth of 68 GB/s. There are also two neural network accelerators that work in tandem to process as much as 1TB of data per second. This setup is roughly three times faster, about 80%, and about 1.25 times more power-efficient than the previous hardware. It is also able to process about 2,300 frames per second compared to the 110 frames per second processed by Tesla’s Hardware 2.5.
In his series of tweets on Sunday, Musk also mentioned Tesla’s “Dojo” supercomputer, which is speculated to be capable of processing vast amounts of data to train the company’s neural network. Through active learning, Tesla curates the most useful video clips from its fleet of connected cars and train the neural net to recognize things that it did not previously know.
“Our networks learn from the most complicated and diverse scenarios in the world, iteratively sourced from our fleet of nearly 1M vehicles in real-time. A full build of Autopilot neural networks involves 48 networks that take 70,000 GPU hours to train. Together, they output 1,000 distinct tensors (predictions) at each timestep,” Tesla wrote on the Autopilot AI section of its website.
“At Tesla, using AI to solve self-driving isn’t just icing on the cake, it the cake” – @lexfridman
Join AI at Tesla! It reports directly to me & we meet/email/text almost every day. My actions, not just words, show how critically I view (benign) AI.https://t.co/iF97zvYZRz
— Elon Musk (@elonmusk) February 2, 2020
The last major software update rolled out by Tesla allowed its vehicles to visualize more things while driving in inner-city streets. Teslas now render stoplights, stop signs, traffic cones, traffic pylons, and more.
With the upcoming AI hackathon, Tesla will get together with developers to seek out more efficient algorithms and overall improvements to the core logic for its Full Self-Driving suite through a time-boxed event. With fresh eyes working with the existing AI and autopilot team of Tesla, the carmaker may be able to accelerate the timeline and rollout of its full-featured Full Self-Driving suite sooner.
Further advances in FSD and its Autopilot feature will widen the gap between Tesla and its competitors and solidify the company’s position as one of the leading automakers in the world. These improvements will also take Tesla a step closer to the possibility of Robotaxis that they can deploy at scale.
The hackathon will also allow Tesla to fish for new AI talents to join the team. On Sunday, Musk also mentioned that the electric carmaker is looking for world-class chip designers and C++/C engineers for vehicle control and other functions of Tesla vehicles.
Musk reiterated that educational attainment is not important when joining Tesla but rather a clear understanding of how AI and neural networks function and the ability to build useful applications using that knowledge.
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Tesla Cybercab gets crazy change as mass production begins
Tesla has officially kicked off mass production of its groundbreaking Cybercab robotaxi at Giga Texas, and the first units rolling off the line feature a striking transformation that’s turning heads across the EV community.
Tesla Cybercab has evidently received a pretty crazy change from an aesthetic standpoint, as the company has made the decision to offer an additional finish on the vehicle as mass production is starting.
Tesla has officially kicked off mass production of its groundbreaking Cybercab robotaxi at Giga Texas, and the first units rolling off the line feature a striking transformation that’s turning heads across the EV community.
VIN Zero—the very first production Cybercab—showcases a vibrant champagne gold exterior with a high-gloss finish, a dramatic departure from the flat, matte-wrapped prototypes that debuted at the 2024 “We, Robot” event.
Presenting VIN Zero — the very first production Cybercab built at Giga Texas. pic.twitter.com/8bXo4CJAlr
— TechOperator (@TechOperator) April 23, 2026
This glossy sheen is a pretty big pivot from what was initially shown by Tesla. The company has maintained a pretty flat tone in terms of anything related to custom colors or finishes.
A specialized clear coat or process delivers the deep, reflective gloss without conventional painting. The result is a premium, mirror-like shine, and it looks pretty good, and gives the compact two-seater a more luxurious and futuristic presence than the subdued matte prototypes.
Photos shared by Tesla community members reveal VIN Zero in a showroom-like setting at Giga Texas, highlighting refined panel gaps, large aero wheel covers, and the signature no-steering-wheel, no-pedals interior optimized for full autonomy.
The open frunk in some images offers a glimpse of practical storage, while the overall build quality appears more polished than that of test mules.
This glossy evolution aligns with Tesla’s broader production ramp. After the first unit in February 2026, the company has shifted to volume manufacturing, with dozens of units already spotted in outbound lots. CEO Elon Musk and the team aim for hundreds per week, paving the way for unsupervised FSD robotaxi networks that could slash ride costs to pennies per mile.
The Cybercab holds Tesla’s grand ambitions of operating a full-service ride-hailing service without any drivers in its grasp. Tesla has yet to solve autonomy, but is well on its way, and although its timelines are usually a bit off, improvements often come through the Over-the-Air updates to the Full Self-Driving suite.
News
Tesla confirms Cybercab with no steering wheel enters production
Tesla has confirmed today that its steering wheel-less and pedal-less Cybercab, the vehicle geared toward launching the company’s autonomous ride-hailing hopes, has officially entered production at its Giga Texas production facility outside of Austin.
The Cybercab is a sleek two-door, two-passenger coupe engineered from the ground up as an electric self-driving vehicle. It features no steering wheel or pedals, relying instead on Tesla’s advanced vision-only Full Self-Driving system powered by multiple cameras and artificial intelligence.
Purpose-built for autonomy
Cybercab in production now at Giga Texas pic.twitter.com/Y9qG3KyWBa
— Tesla (@Tesla) April 23, 2026
The minimalist cabin centers on a large display screen that serves as the primary interface for passengers, creating an open, futuristic space optimized for comfort during unsupervised rides. A compact 35-kilowatt-hour battery pack delivers exceptional efficiency at 5.5 miles per kilowatt-hour, providing an estimated 200-mile range.
Additional innovations include inductive charging compatibility and a lightweight design that enhances aerodynamics and performance.
Production at Giga Texas builds on earlier prototypes and initial units completed earlier in 2026. The facility, already a hub for Model Y and Cybertruck assembly, now ramps up dedicated lines for the Cybercab.
This shift to volume manufacturing reflects Tesla’s strategy to scale affordable autonomous vehicles rapidly.
By focusing on a dedicated platform rather than adapting existing models, the company aims to keep costs low while prioritizing safety and reliability through continuous AI improvements.
The Cybercab’s debut in production carries broad implications for urban mobility. As the cornerstone of Tesla’s Robotaxi network, it promises on-demand, driverless rides that could slash transportation expenses, reduce traffic accidents caused by human error, and lower emissions through its all-electric powertrain.
Accessibility features, such as space for service animals or assistive devices, further broaden its appeal. Regulators and cities worldwide will soon evaluate its deployment, but the vehicle’s design already addresses key hurdles in scaling unsupervised autonomy.
Challenges persist, including full regulatory clearance and building charging infrastructure. Yet this production launch signals momentum. With Cybercabs poised to roll out in increasing numbers, Tesla edges closer to a future where personal ownership meets shared fleets of intelligent vehicles.
The start of Cybercab production is more than just a new vehicle entering mass manufacturing for Tesla, as it’s a signal autonomy is near. Being developed without manual controls is such a massive sign by Tesla that it trusts its progress on Full Self-Driving.
While the development of that suite continues, Tesla is making a clear cut statement that it is prepared to get its fully autonomous vehicle out in public roads as it prepares to revolutionize passenger travel once and for all.
News
Tesla Summon got insanely good in FSD v14.3.2 — Navigation? Not so much
There were two new lines of improvements in the release notes: one addressing Actually Smart Summon (ASS), and another that now allows drivers to choose a reason for an intervention via a small menu during disengagement.
Tesla Full Self-Driving v14.3.2 began rolling out to some owners earlier this week, and there are some notable improvements that came with this update.
There were two new lines of improvements in the release notes: one addressing Actually Smart Summon (ASS), and another that now allows drivers to choose a reason for an intervention via a small menu during disengagement.
Overall operation saw a handful of slight improvements, especially with parking performance, which has been the most notable difference with the arrival of FSD v14.3. However, there are still some very notable shortcomings, most notably with region-specific signage and navigation.
Tesla Assisted Smart Summon (ASS) improvements
There are noticeable improvements to ASS operation, which has definitely been inconsistent in terms of performance. Tesla wrote in the release notes for v14.3.2:
“Unified the model between Actually Smart Summon, FSD, and Robotaxi for more capable and reliable behavior.”
As recently as this month, I used Summon with no success. It had pulled around the parking lot I was in incorrectly, leaving the range at which Summon can be operated and losing a signal while moving in the middle of the lot.
This caused me to sprint across the lot to retrieve the vehicle:
It was pouring when I left the gym so I tried to Summon my Model Y
It turned the opposite way and drove out of range, stopping here and forcing me to walk even further across the lot in the rain for it 🤣
One day pic.twitter.com/iD10c8sriB
— TESLARATI (@Teslarati) April 5, 2026
Unfortunately, Summon was not dependable or accurate enough to use regularly. It appears Tesla might have bridged the gap needed to make it an effective feature, as two tests in parking lots proved that Summon was more responsive and faster to navigate to the location chosen.
It also did so without hesitation, confidently, and at a comfortable speed. I was able to test it twice at different distances:
🚨 Tesla FSD v14.3.2 ASS testing part 1
This was a significant improvement than recent tries using ASS. The parking lot was pretty empty but getting it to come to my location in one singular motion and maneuver was encouraging. https://t.co/vF7TS48GGV pic.twitter.com/sYt8tyHgNn
— TESLARATI (@Teslarati) April 23, 2026
Tesla Full Self-Driving v14.3.2 ASS testing part 2 https://t.co/lxfWfnLUxf pic.twitter.com/2R0r3ohI3M
— TESLARATI (@Teslarati) April 23, 2026
I plan to test this more thoroughly and regularly through the next few weeks, and I avoided using it in a congested parking lot initially because I have not had overwhelming success with Summon in the past. I wanted to set a low baseline for it to see if it could simply pull up to the place I pinned in the Tesla app.
It was two for two, which is a big improvement because I don’t think I ever had successful Summon attempts back-to-back. It just seems more confident than ever before.
New Disengagement Categories
This is a really good idea from Tesla, but there are some issues with it. The categories you can select are Critical, Comfort, Preference, and Other.
I think the reasons why people choose to take over would be a better way to prompt drivers, like, “Traveling Too Fast,” “Incorrect Maneuver,” “Navigation Error,” would be more beneficial.
I say this because it seems that how we each categorize things might be different. For example, I shared a video of an intervention because the car had navigated to an exit to a parking lot and put its left blinker on, despite left turns not being allowed there.
I disengaged and chose Critical as the reason; it’s not a comfort issue, it’s not a preference, it’s quite literally an illegal turn, and it’s also dangerous because it cuts across several lanes of traffic and is 180 degrees.
I chose to label this Navigation error as “Critical” while testing FSD v14.3.2
Here’s why:
✅ This intervention wasn’t “preference,” as the maneuver FSD routed was illegal
✅ If a police officer saw this maneuver, it would result in a ticket https://t.co/znhHb4haAo pic.twitter.com/bZOiLwWmQa— TESLARATI (@Teslarati) April 23, 2026
Some said I should not have labeled this as Critical, but that’s the description I best characterized the disengagement as.
Categorizing interventions is a good thing, but it’s kind of hard to determine how to label them correctly.
Inconsistency with Regional Traffic Patterns
Tesla Full Self-Driving is pretty inconsistent with how it handles regional or local traffic patterns and road rules. The most frequent example I like to use is that of the “Except Right Turn” stop sign, which has become a notorious sighting on our social media platforms.
In the initial rollout of v14.3, my Model Y successfully navigated through one of these stop signs with no issues. However, testing at two of these stop signs yesterday proved it is still not sure how to read signs and navigate through them properly.
🚨 Tesla FSD v14.3.2 attempts the “Except Right Turn” stop sign: https://t.co/W5MjAybaNK pic.twitter.com/P6oeUsk4PN
— TESLARATI (@Teslarati) April 23, 2026
Off camera, I approached another one of these signs and felt the car coming to a stop, so I nudged it forward with the accelerator pedal pressed.
This helped the car go through the sign without stopping, but I could feel the bucking of the vehicle as the car really wanted to stop.
Musk said on the earnings call earlier this week that unsupervised FSD would probably be available in some regions before others, including a state-to-state basis in the U.S.
“It’s difficult to release this like to everyone everywhere all at once because we do want to make sure that they’re not unique situations in a city that particularly complex intersection or — actually, they tend to be places where people get into accidents a lot because they’re just — perhaps there’s — and like I said, an unsafe intersection or bad road markings or a lot of weather challenges. So I think we would release unsupervised gradually to the customer fleet as we feel like a particular geography is confirmed to be safe.”
This could be one of those examples that Tesla just has to figure out.
Highway Operation
Full Self-Driving is already pretty good at routine roadway navigation, so I don’t have too much to report here.
However, I was happy with FSD’s decision-making at several points, including its choice not to pass a slightly slower car and remain in the right lane as we approached the off-ramp:
🚨 Tesla FSD v14.3.2 highway operation: generally happy with the performance here, especially behavior near the exit
Love that the car got over in the right lane after its final pass, and stayed there as the off ramp was approaching https://t.co/qVRVhg6XGR pic.twitter.com/1ELwHf2XKS
— TESLARATI (@Teslarati) April 23, 2026
Better Maneuvering at Stop Signs
Many FSD users report some strange operations at stop signs, especially four-way intersections where there is a stop sign and a line on the road, and they’re not even with one another.
I experienced this quite frequently and found that FSD would actually double stop: once at the stop sign and again at the line.
This created some interesting scenarios for me and I had many cars honk at me when the second stop would happen. Other vehicles that had waved me on to proceed through the intersection would become frustrated at the second stop.
FSD seems to have worked through this particular maneuver:
🚨 Tesla FSD v14.3.2 with a singular stop at the correct spot
No double stopping anymore in my experience https://t.co/Wd0TaNjc1R pic.twitter.com/CdQPvJHaAM
— TESLARATI (@Teslarati) April 23, 2026
FSD should know to go to the more appropriate location (whichever provides better visibility), and proceed when it is the car’s turn to move. The double stop really ruined the flow of traffic at times and generally caused some frustration from other drivers.