News
SpaceX’s Falcon 9 sticks foggy booster recovery at California landing zone
Update: SpaceX has successfully wrapped up the Radarsat Constellation Mission, likely its last launch from Vandenberg Air Force Base for six to nine months. Supporting its second mission, Falcon 9 booster B1051 completed a flawless launch and landing, returning to SpaceX’s pad-adjacent LZ-4 landing zone after a gentle, (relatively) low-velocity reentry at ~1.6 km/s (3700 mph).
Sadly, the sun was unable to beat back Vandenberg’s iconic fog layer and it’s unlikely that remote cameras (even including SpaceX’s own on-pad webcast cameras) captured anything more than gray fog. According to Teslarati’s photographers, the sonic booms produced by the returning Falcon 9 booster were as spectacular as ever, though.
Despite more than seven months of delays, the Canadian Space Agency (CSA) can finally rest now that all three Radarsat Constellation spacecraft are safely in orbit, completing what is arguably the most arduous leg of most spacecraft journeys. Valued at more than $1 billion, SpaceX has also successfully launched its most expensive payload by a large margin, adding to Falcon 9’s increasingly impressive record of reliability.




SpaceX is just hours away from its sixth Falcon 9 launch of 2019, likely the company’s last Vandenberg Air Force Base (VAFB) mission for the rest of the year (and possibly longer).
Flight proven Falcon 9 booster B1051.1 has been assigned to the launch and will attempt to return to SpaceX’s LZ-4 landing zone after sending Canada’s Radarsat Constellation Mission (RCM) on its way to orbit. Likely weighing approximately 5000 kg (11,000 lb), RCM is comprised of a trio of Earth observation spacecraft with large surface-scanning radars as their primary payloads. At a cost of more than $1 billion, RCM will be the most expensive payload SpaceX has ever attempted to launch. Falcon 9 has a 13-minute window for launch but liftoff is scheduled to occur at 7:17 am PDT (14:17 UTC) on Wednesday, June 12th.
As it stands, Falcon 9’s RCM launch will last just over one hour from start to finish. B1051 will separate from Falcon 9’s upper stage, fairing, and payload and perform a return-to-launch-site (RTLS) recovery, landing at SpaceX’s LZ-4 pad less than eight minutes after liftoff.

LZ-4 sits barely a quarter of a mile away from SLC-4E, the SpaceX-leased pad that B1051.1 will lift off from. Sadly, B1051 is unlikely to remain at SLC-4 after its (hopefully successful) landing at LZ-4 due to the fact that SpaceX has no public missions scheduled to launch from VAFB until Q1 2020 at the earliest. In fact, SpaceX is reportedly planning major organizational changes – set to begin soon after this launch is complete. As such, RCM could be SpaceX’s last launch from California for at least the next six months, a period of downtime that could easily grow to a year or more if tenuous 2020 launch dates suffer payload-side delays.
SpaceX currently has three launches scheduled from its Vandenberg pad in 2020, although one, two, or even all three could easily slip into 2021 based on the limited information available about the payloads in question. In 2021, SpaceX has a fairly busy VAFB manifest of at least six possible launches – possibly more if 2020 missions slip.
Regardless, RCM will be a good temporary send-off to SpaceX’s launch activity in California. Press photographers – unaffiliated with SpaceX – will have the first opportunity ever to remotely capture images of a Falcon 9 booster landing in daylight. Additionally, weather permitting, Vandenberg Air Force Base makes for an exceptionally beautiful venue for rocket launches thanks to the vistas and setting offered by Northern California and the Pacific Ocean.
Current forecasts suggest that the traditional fog layer will begin to clear at 7am local time, around the same time that SpaceX’s RCM webcast will kick off. With any luck, the photographers’ remote cameras will be greeted by a clear Pacific morning come liftoff.


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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.”
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.
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.”
News
Tesla earns top honors at MotorTrend’s SDV Innovator Awards
MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
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.
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.
Elon Musk
Judge clears path for Elon Musk’s OpenAI lawsuit to go before a jury
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder.
A U.S. judge has ruled that Elon Musk’s lawsuit accusing OpenAI of abandoning its founding nonprofit mission can proceed to a jury trial.
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder. These claims are directly opposed by OpenAI.
Judge says disputed facts warrant a trial
At a hearing in Oakland, U.S. District Judge Yvonne Gonzalez Rogers stated that there was “plenty of evidence” suggesting that OpenAI leaders had promised that the organization’s original nonprofit structure would be maintained. She ruled that those disputed facts should be evaluated by a jury at a trial in March rather than decided by the court at this stage, as noted in a Reuters report.
Musk helped co-found OpenAI in 2015 but left the organization in 2018. In his lawsuit, he argued that he contributed roughly $38 million, or about 60% of OpenAI’s early funding, based on assurances that the company would remain a nonprofit dedicated to the public benefit. He is seeking unspecified monetary damages tied to what he describes as “ill-gotten gains.”
OpenAI, however, has repeatedly rejected Musk’s allegations. The company has stated that Musk’s claims were baseless and part of a pattern of harassment.
Rivalries and Microsoft ties
The case unfolds against the backdrop of intensifying competition in generative artificial intelligence. Musk now runs xAI, whose Grok chatbot competes directly with OpenAI’s flagship ChatGPT. OpenAI has argued that Musk is a frustrated commercial rival who is simply attempting to slow down a market leader.
The lawsuit also names Microsoft as a defendant, citing its multibillion-dollar partnerships with OpenAI. Microsoft has urged the court to dismiss the claims against it, arguing there is no evidence it aided or abetted any alleged misconduct. Lawyers for OpenAI have also pushed for the case to be thrown out, claiming that Musk failed to show sufficient factual basis for claims such as fraud and breach of contract.
Judge Gonzalez Rogers, however, declined to end the case at this stage, noting that a jury would also need to consider whether Musk filed the lawsuit within the applicable statute of limitations. Still, the dispute between Elon Musk and OpenAI is now headed for a high-profile jury trial in the coming months.