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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 is not sparing any expense in ensuring the Cybercab is safe
Images shared by the longtime watcher showed 16 Cybercab prototypes parked near Giga Texas’ dedicated crash test facility.
The Tesla Cybercab could very well be the safest taxi on the road when it is released and deployed for public use. This was, at least, hinted at by the intensive safety tests that Tesla seems to be putting the autonomous two-seater through at its Giga Texas crash test facility.
Intensive crash tests
As per recent images from longtime Giga Texas watcher and drone operator Joe Tegtmeyer, Tesla seems to be very busy crash testing Cybercab units. Images shared by the longtime watcher showed 16 Cybercab prototypes parked near Giga Texas’ dedicated crash test facility just before the holidays.
Tegtmeyer’s aerial photos showed the prototypes clustered outside the factory’s testing building. Some uncovered Cybercabs showed notable damage and one even had its airbags engaged. With Cybercab production expected to start in about 130 days, it appears that Tesla is very busy ensuring that its autonomous two-seater ends up becoming the safest taxi on public roads.
Prioritizing safety
With no human driver controls, the Cybercab demands exceptional active and passive safety systems to protect occupants in any scenario. Considering Tesla’s reputation, it is then understandable that the company seems to be sparing no expense in ensuring that the Cybercab is as safe as possible.
Tesla’s focus on safety was recently highlighted when the Cybertruck achieved a Top Safety Pick+ rating from the Insurance Institute for Highway Safety (IIHS). This was a notable victory for the Cybertruck as critics have long claimed that the vehicle will be one of, if not the, most unsafe truck on the road due to its appearance. The vehicle’s Top Safety Pick+ rating, if any, simply proved that Tesla never neglects to make its cars as safe as possible, and that definitely includes the Cybercab.
Elon Musk
Tesla’s Elon Musk gives timeframe for FSD’s release in UAE
Provided that Musk’s timeframe proves accurate, FSD would be able to start saturating the Middle East, starting with the UAE, next year.
Tesla CEO Elon Musk stated on Monday that Full Self-Driving (Supervised) could launch in the United Arab Emirates (UAE) as soon as January 2026.
Provided that Musk’s timeframe proves accurate, FSD would be able to start saturating the Middle East, starting with the UAE, next year.
Musk’s estimate
In a post on X, UAE-based political analyst Ahmed Sharif Al Amiri asked Musk when FSD would arrive in the country, quoting an earlier post where the CEO encouraged users to try out FSD for themselves. Musk responded directly to the analyst’s inquiry.
“Hopefully, next month,” Musk wrote. The exchange attracted a lot of attention, with numerous X users sharing their excitement at the idea of FSD being brought to a new country. FSD (Supervised), after all, would likely allow hands-off highway driving, urban navigation, and parking under driver oversight in traffic-heavy cities such as Dubai and Abu Dhabi.
Musk’s comments about FSD’s arrival in the UAE were posted following his visit to the Middle Eastern country. Over the weekend, images were shared online of Musk meeting with UAE Defense Minister, Deputy Prime Minister, and Dubai Crown Prince HH Sheikh Hamdan bin Mohammed. Musk also posted a supportive message about the country, posting “UAE rocks!” on X.
FSD recognition
FSD has been getting quite a lot of support from foreign media outlets. FSD (Supervised) earned high marks from Germany’s largest car magazine, Auto Bild, during a test in Berlin’s challenging urban environment. The demonstration highlighted the system’s ability to handle dense traffic, construction sites, pedestrian crossings, and narrow streets with smooth, confident decision-making.
Journalist Robin Hornig was particularly struck by FSD’s superior perception and tireless attention, stating: “Tesla FSD Supervised sees more than I do. It doesn’t get distracted and never gets tired. I like to think I’m a good driver, but I can’t match this system’s all-around vision. It’s at its best when both work together: my experience and the Tesla’s constant attention.” Only one intervention was needed when the system misread a route, showcasing its maturity while relying on vision-only sensors and over-the-air learning.
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Tesla quietly flexes FSD’s reliability amid Waymo blackout in San Francisco
“Tesla Robotaxis were unaffected by the SF power outage,” Musk wrote in his post.
Tesla highlighted its Full Self-Driving (Supervised) system’s robustness this week by sharing dashcam footage of a vehicle in FSD navigating pitch-black San Francisco streets during the city’s widespread power outage.
While Waymo’s robotaxis stalled and caused traffic jams, Tesla’s vision-only approach kept operating seamlessly without remote intervention. Elon Musk amplified the clip, highlighting the contrast between the two systems.
Tesla FSD handles total darkness
The @Tesla_AI account posted a video from a Model Y operating on FSD during San Francisco’s blackout. As could be seen in the video, streetlights, traffic signals, and surrounding illumination were completely out, but the vehicle drove confidently and cautiously, just like a proficient human driver.
Musk reposted the clip, adding context to reports of Waymo vehicles struggling in the same conditions. “Tesla Robotaxis were unaffected by the SF power outage,” Musk wrote in his post.
Musk and the Tesla AI team’s posts highlight the idea that FSD operates a lot like any experienced human driver. Since the system does not rely on a variety of sensors and a complicated symphony of factors, vehicles could technically navigate challenging circumstances as they emerge. This definitely seemed to be the case in San Francisco.
Waymo’s blackout struggles
Waymo faced scrutiny after multiple self-driving Jaguar I-PACE taxis stopped functioning during the blackout, blocking lanes, causing traffic jams, and requiring manual retrieval. Videos shared during the power outage showed fleets of Waymo vehicles just stopping in the middle of the road, seemingly confused about what to do when the lights go out.
In a comment, Waymo stated that its vehicles treat nonfunctional signals as four-way stops, but “the sheer scale of the outage led to instances where vehicles remained stationary longer than usual to confirm the state of the affected intersections. This contributed to traffic friction during the height of the congestion.”
A company spokesperson also shared some thoughts about the incidents. “Yesterday’s power outage was a widespread event that caused gridlock across San Francisco, with non-functioning traffic signals and transit disruptions. While the failure of the utility infrastructure was significant, we are committed to ensuring our technology adjusts to traffic flow during such events,” the Waymo spokesperson stated, adding that it is “focused on rapidly integrating the lessons learned from this event, and are committed to earning and maintaining the trust of the communities we serve every day.”