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Tesla’s Elon Musk will be hosting an AI hackathon party at his house

Tesla Autopilot (Source: Elon Musk | Twitter)

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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.

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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.

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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.

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.

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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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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.

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Tesla improves Dashcam playback with awesome addition

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Image Credit: The Kilowatts/Twitter

Tesla has improved Dashcam playback with an awesome new addition, as the company has launched a web-based version that is potentially easier to navigate and operate.

The tool is available at dashcam.tesla.com and will be enabled as your vehicle receives the 2026.20 Software Version. Clips that are captured by your Tesla will be available on the Online Dashcam Clip Viewer once the files on your car’s storage drive are encrypted.

Not a Tesla App first noticed the new feature, and states that once your Tesla updates to 2026.20, the car will automatically protect the clips with an encryption key that is uniquely tied to your owner account.

The web-based viewer should be easier to operate for most. All you will do is head over to dashcam.tesla.com and log in using your account credentials.

Ensure your vehicle is updated to 2026.20 in order for the web-based viewer tool to fetch your vehicle’s saved dashcam clips.

Currently, only a small percentage of owners are updated to this, so it may be a couple of weeks until a majority of owners in the fleet are able to access this feature.

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Watching Dashcam clips on the Tesla smartphone app is quick and convenient, as they can also be easily downloaded and stored right on your smartphone.

However, the clips are sometimes tougher to navigate, and in order to get details like self-driving activation, speed, and turn signals, owners have to screen record the Tesla app and crop out the rest of the screen.

It could also be a massive storage saver as you’ll be able to download the Dashcam clips from the online viewer and save them to your laptop, desktop, a flash drive, or even an external hard drive. This will keep all your clips in one place.

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Tesla Full Self-Driving attempts 150-mile stress test: the good and the bad

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Credit: TESLARATI

I recently took my Tesla Model Y running Full Self-Driving (Supervised) v14.3.3 over 150 miles on the Pennsylvania Turnpike in an effort to truly put the system under a stress test. There were a lot of good moments, and some bad, but overall, Full Self-Driving impressed me.

Last Thursday, I decided it was time to visit the Flight 93 National Memorial near Shanksville, PA. I go a few times a year, and it was a beautiful day. Others have taken some pretty lengthy drives using FSD, but I haven’t had the opportunity to really do something lengthy in quite a few months on an older version. I decided it was the perfect opportunity to try some things out.

I recorded the entire ride there on a GoPro, edited to highlight the crucial moments, and shared them on our social media accounts. If you want to watch them, I’ll share them throughout the piece, but I did not get to do a real breakdown of what I felt about its performance.

Overall Thoughts

I realize it is probably better to do a summation of its performance toward the end of the piece, but I feel like it is also reasonable to lead with this because I was overly impressed with how well it handled everything. The only moments where I felt a little bit of reason to touch the wheel, at least while traveling on the Turnpike and Rt. 30, were due to other drivers and their behaviors.

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I have taken many drives to the Memorial over the past several years, and although it’s not incredibly long, it is a tiring drive. It’s about five hours both ways, close to 300 miles, and I think most of the exhaustion comes from the toll of sitting in the car and then visiting something that is pretty heavy to take in.

This was the first time I’ve ever taken the ride and not felt like I needed to avoid my vehicle after I got home. In the past, I could not even think about driving after I finally arrived at my house, but this was simply different.

It was nice to have something else take the drive for me, while I still had the freedom to take over if I chose to. It made the entire trip more enjoyable.

Full Self-Driving Recognizes Lane-Ending Arrows on Road

After traveling in the fast lane for a little while, FSD noticed the arrows on the road indicating the lane was coming to an end ahead. The car was also in the process of making a pass on a slower vehicle in the middle lane, but aborted this maneuver and backed off to get behind the vehicle.

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I was really impressed by this because I thought that the car would absolutely try to make the pass, only to get in front of the other car, and then slow back down to 75 MPH:

Full Self-Driving Notices Veering Tractor Trailer, Adjusts Lane Positioning

My two rules of the road are never cruise in the fast lane and never drive next to a tractor-trailer. This clip is a perfect example as to why.

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FSD v14.3.3 recognized this tractor-trailer attempting to change lanes while we were still next to it. The car shifted its lane positioning to the shoulder slightly to make room for the merging semi, executed the pass safely, and on we went.

I will admit this one made me a little nervous, but more so because of the 18-wheeler, and not because of the Tesla:

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Full Self-Driving Follows the Rules of Tunnel Travel

Many people who are not familiar with Full Self-Driving and its capabilities are pretty limited in what they know about the really simple things it does well. Part of supervising FSD is being aware of things it might make mistakes with, and anticipating maneuvers it might want to make at the wrong time.

Entering the Blue Mountain Tunnel on the Turnpike, I was ready for FSD to attempt to get back into the right lane after making a pass on a tractor-trailer, but I was pleasantly surprised. Several signs outside the tunnel advise drivers to stay in the lane they’ve chosen while driving through the tunnel; this eliminates the possibility of an accident caused by lane changes, which would impede traffic on a crucial logistics route.

I was happy to see that Tesla Full Self-Driving v14.3.3 did not make this mistake:

Full Self-Driving Navigates Toll Plazas with Ease

I was interested to see how FSD would handle toll plazas, including the speed at which it would travel through them, and whether it would stop on the Turnpike at these booths, which have since been transitioned to a “Toll by Plate” system, which mails you a bill.

It was flawless:

Full Self-Driving Still Struggles with Parking from Time to Time

Since I took delivery in late August, I’ve never had a single instance of my Tesla struggling to park at a Supercharger. Other spots at the mall, market, or gym are another story.

This was the first time it did such a terrible job of backing into a spot. This required me to take over and manually park at another charger:

Full Self-Driving Gets Confused After Arriving at Its Destination

This was the first time I have ever experienced FSD getting confused and just circling the lot. The navigation continued to reroute to try to resolve the issue, but after four laps, I decided it was time to overtake the car’s controls and park manually:

This was a baffling behavior that I truly couldn’t explain. Other owners communicated that they have also experienced this issue.

Final Thoughts

I am so incredibly impressed by FSD that it has really made traveling stress-free. The two issues related to parking were not ideal, but to be fair, I usually take over when arriving at parking lots. However, this shortcoming is something Tesla has to make some serious progress with, because parking has truly stumped FSD at times.

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Solving that will be a major breakthrough for autonomy, but Tesla has struggled with it for some time.

All in all, FSD v14.3.3 is unbelievably accurate and handles many of the more stressful maneuvers with ease, one of them being avoiding merging traffic on highways, which was shown above.

Some things that would be great to see improvements on are parking, Speed Profiles, which are relatively tough to adjust (I stayed in Standard for the duration of this drive), and, of course, navigation.

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SpaceX’s amended S-1 is sparking a major Tesla merger conversation

A single line in SpaceX’s amended S-1 just sent Tesla stock down 5% in one day.

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A single line buried in SpaceX’s amended S-1 filing is doing more to move Tesla’s stock price than anything Tesla itself has announced in months. The clause, disclosed as SpaceX prepares for what could be the largest IPO in Wall Street history, states that the company “may issue a significant amount of equity in connection with future transactions.” While this may be seen as boilerplate language in S-1 filings, the historical ties between SpaceX and Tesla, and with Elon Musk reportedly discussing a possible merger with close colleagues, investors are interpreting it as something closer to a signal.

The concern among institutional investors like Gary Black, managing director of The Future Fund, pointed directly to the amended filing on X, saying it “strongly suggests more SPCX equity will be issued,” which could potentially be used to acquire Tesla. He estimated such a deal could be 28% dilutive to Tesla shareholders since SpaceX would likely command a significantly higher valuation multiple. Black added that institutional investors he knows hate the idea of a combination because they prefer pure plays over conglomerates, which he said “nearly always gravitate to the lowest common multiple.”

The Tesla and SpaceX merger everyone is talking about is quietly building

The bull case runs the math differently. Tesla influencer and retail shareholder advocate AleXandra Merz pushed back on what she called a widespread misunderstanding of how merger-of-equals deals actually work. Rather than simply splitting the difference between two market caps, a merger exchange ratio is negotiated based on relative fair market values, meaning the lower valued company typically sees its stock reprice upward toward the deal value.

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Under her model, SpaceX enters at a $2.5 trillion valuation and Tesla at $1.6 trillion, producing a combined entity worth $4.1 trillion split evenly between both shareholder groups. That implies Tesla’s side of the deal would be valued at $2.05 trillion, a gain of roughly $450 billion from its current market cap. She cited Dow-DuPont and CBS-Viacom as historical examples of how markets reprice both companies toward the announced exchange ratio after a deal is unveiled.


The SpaceX S-1 amendments also revealed just how much financial infrastructure already binds the two companies together. As Teslarati has reported, SpaceX purchased $697 million in Tesla Megapacks, $131 million in Cybertrucks, and the two companies have shared supply chain resources, and semiconductor fabrication plans since well before any merger conversation became public. A retail poll by Tesla influencer Sawyer Merritt is finding that 36% of respondents do not plan to buy SpaceX shares at IPO and 15.3% saying their decision depends on the valuation.


Whether the merger happens or not, the amended filing is seemingly moving markets and sharpened a debate that is no longer theoretical. SpaceX is weeks away from trading publicly, and Tesla shareholders are now watching every word of every filing for clues about what Musk plans to do next.

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