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Rocket Lab successfully launches the ‘Beginning of the Swarm’ mission

Electron launches the Beginning of the Swarm mission from New Zealand (Credit Rocket Lab)

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Rocket Lab successfully launched the “Beginning of the Swarm” mission, its 47th overall yesterday.

Electron took the skies at 10:32 am NZT from Launch Complex 1B on the Mahia Peninsula in New Zealand, sending two small payloads to vastly different orbits.

The launch was originally scheduled for 10:15 a.m. NZT, just 2 minutes before a Falcon 9 mission from Florida, but it held at t – 12 minutes as the Rocket Lab team worked on a ground support system issue. It didn’t take long for teams to work on the issue, and Electron launched safely from LC-1B.

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The primary payload was NEONSAT-1 for the Korea Advanced Institute of Science and Technology and Satellite Technology Research Center. This is the first of an eventual 11-satellite constellation. The satellite features a high-resolution camera that will monitor the Korean peninsula and help with recovery after natural disasters.

NEONSAT-1 was deployed into a 520 km circular orbit 50 minutes after lift-off.

The secondary payload was NASA’s Advanced Composite Solar Sail System (ACS3). This satellite is meant to test new materials for the boom that deploys the sail itself. Once deployed, it is about the size of a small apartment.

ACS-3 was deployed into a much higher orbit than NEONSAT-1 thanks to the abilities of the Electron Kick Stage, which ignited 3 times with one final burn to circularize the orbit and deploy the satellite at 1000 km nearly an hour after the first payload deployment.

While Rocket Lab did not recover the Electron first stage, they confused many viewers when it was revealed that the first stage featured the red and silver look that is used on recovery missions.

However, as Rocket Lab is progressing towards full first-stage re-usability, these Electrons are now in the standard production flow, according to the company. Yesterday’s mission required Electron to be expended.

Next up for Rocket Lab is likely a dedicated launch for Capella Space, which will launch an Acadia synthetic aperture radar (SAR) satellite with a to-be-confirmed launch date.

Disclosure: Richard Angle is not an RKLB shareholder.

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Questions or comments? Shoot me an email at rangle@teslarati.com, or Tweet me @RDAnglePhoto.

Launch journalist, specializing in launch photography. Based on the Space Coast, a short drive from Cape Canaveral and the SpaceX launch pads.

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Elon Musk

Tesla AI Head says future FSD feature has already partially shipped

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Credit: Tesla

Tesla’s Head of AI, Ashok Elluswamy, says that something that was expected with version 14.3 of the company’s Full Self-Driving platform has already partially shipped with the current build of version 14.2.

Tesla and CEO Elon Musk have teased on several occasions that reasoning will be a big piece of future Full Self-Driving builds, helping bring forth the “sentient” narrative that the company has pushed for these more advanced FSD versions.

Back in October on the Q3 Earnings Call, Musk said:

“With reasoning, it’s literally going to think about which parking spot to pick. It’ll drop you off at the entrance of the store, then go find a parking spot. It’s going to spot empty spots much better than a human. It’s going to use reasoning to solve things.”

Musk said in the same month:

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“By v14.3, your car will feel like it is sentient.”

Amazingly, Tesla Full Self-Driving v14.2.2.2, which is the most recent iteration released, is very close to this sentient feeling. However, there are more things that need to be improved, and logic appears to be in the future plans to help with decision-making in general, alongside other refinements and features.

On Thursday evening, Elluswamy revealed that some of the reasoning features have already been rolled out, confirming that it has been added to navigation route changes during construction, as well as with parking options.

He added that “more and more reasoning will ship in Q1.”

Interestingly, parking improvements were hinted at being added in the initial rollout of v14.2 several months ago. These had not rolled out to vehicles quite yet, as they were listed under the future improvements portion of the release notes, but it appears things have already started to make their way to cars in a limited fashion.

Tesla Full Self-Driving v14.2 – Full Review, the Good and the Bad

As reasoning is more involved in more of the Full Self-Driving suite, it is likely we will see cars make better decisions in terms of routing and navigation, which is a big complaint of many owners (including me).

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Additionally, the operation as a whole should be smoother and more comfortable to owners, which is hard to believe considering how good it is already. Nevertheless, there are absolutely improvements that need to be made before Tesla can introduce completely unsupervised FSD.

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Elon Musk

Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD

As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.” 

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Credit: @BLKMDL3/X

Tesla CEO Elon Musk has provided an updated estimate for the training data needed to achieve truly safe unsupervised Full Self-Driving (FSD). 

As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.” 

10 billion miles of training data

Musk comment came as a reply to Apple and Rivian alum Paul Beisel, who posted an analysis on X about the gap between tech demonstrations and real-world products. In his post, Beisel highlighted Tesla’s data-driven lead in autonomy, and he also argued that it would not be easy for rivals to become a legitimate competitor to FSD quickly. 

“The notion that someone can ‘catch up’ to this problem primarily through simulation and limited on-road exposure strikes me as deeply naive. This is not a demo problem. It is a scale, data, and iteration problem— and Tesla is already far, far down that road while others are just getting started,” Beisel wrote. 

Musk responded to Beisel’s post, stating that “Roughly 10 billion miles of training data is needed to achieve safe unsupervised self-driving. Reality has a super long tail of complexity.” This is quite interesting considering that in his Master Plan Part Deux, Elon Musk estimated that worldwide regulatory approval for autonomous driving would require around 6 billion miles. 

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FSD’s total training miles

As 2025 came to a close, Tesla community members observed that FSD was already nearing 7 billion miles driven, with over 2.5 billion miles being from inner city roads. The 7-billion-mile mark was passed just a few days later. This suggests that Tesla is likely the company today with the most training data for its autonomous driving program. 

The difficulties of achieving autonomy were referenced by Elon Musk recently, when he commented on Nvidia’s Alpamayo program. As per Musk, “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.” These sentiments were echoed by Tesla VP for AI software Ashok Elluswamy, who also noted on X that “the long tail is sooo long, that most people can’t grasp it.”

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Tesla earns top honors at MotorTrend’s SDV Innovator Awards

MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.

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Credit: Tesla China

Tesla emerged as one of the most recognized automakers at MotorTrend’s 2026 Software-Defined Vehicle (SDV) Innovator Awards.

As could be seen in a press release from the publication, two key Tesla employees were honored for their work on AI, autonomy, and vehicle software. MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.

Tesla leaders and engineers recognized

The fourth annual SDV Innovator Awards celebrate pioneers and experts who are pushing the automotive industry deeper into software-driven development. Among the most notable honorees for this year was Ashok Elluswamy, Tesla’s Vice President of AI Software, who received a Pioneer Award for his role in advancing artificial intelligence and autonomy across the company’s vehicle lineup.

Tesla also secured recognition in the Expert category, with Lawson Fulton, a staff Autopilot machine learning engineer, honored for his contributions to Tesla’s driver-assistance and autonomous systems.

Tesla’s software-first strategy

While automakers like General Motors, Ford, and Rivian also received recognition, Tesla’s multiple awards stood out given the company’s outsized role in popularizing software-defined vehicles over the past decade. From frequent OTA updates to its data-driven approach to autonomy, Tesla has consistently treated vehicles as evolving software platforms rather than static products.

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This has made Tesla’s vehicles very unique in their respective sectors, as they are arguably the only cars that objectively get better over time. This is especially true for vehicles that are loaded with the company’s Full Self-Driving system, which are getting progressively more intelligent and autonomous over time. The majority of Tesla’s updates to its vehicles are free as well, which is very much appreciated by customers worldwide.

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