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SpaceX fires Falcon Heavy’s 27 booster engines ahead of “most difficult launch ever”
For the third time ever, SpaceX has successfully performed a critical static-fire test of an integrated Falcon Heavy, briefly igniting all 27 of its Merlin 1D engines to verify the health and readiness of the rocket.
Per SpaceX’s official confirmation, a “quick-look” inspection of static fire telemetry has indicated that the company’s Falcon Heavy rocket is ready for its second launch in less than three months, a milestone that could also allow both flight-proven side boosters to tie SpaceX’s own record for booster turnaround. Falcon Heavy Flight 3 is now scheduled to launch the US Air Force’s Space Test Program 2 (STP-2) mission no earlier than 11:30 pm ET (03:30 UTC), June 24th. According to SpaceX CEO Elon Musk, the mission will unequivocally be the company’s “most difficult launch ever”.
Coincidentally, on top of being Falcon Heavy’s first scheduled night launch, STP-2 has now also marked the massive rocket’s first nighttime static fire. During this critical test, Falcon Heavy briefly ignites all 27 of its three boosters’ Merlin 1Ds and throttles the engines up to full thrust, much like airliners sometimes set their brakes and throttle up before attempting to take off. The difference between Falcon Heavy and passenger aircraft is nevertheless rather significant, given that Falcon Heavy produces ~15x the thrust of an A380 – the world’s most powerful mass-produced passenger aircraft – at liftoff: 22,820 kN (5.1M lbf) to the massive jet’s meager 1,440 kN (0.3M lbf).
Despite all of that thrust, Falcon Heavy is held down during static fire by eight accurately-named hold-down clamps, themselves a part of a massive transport/erector, which is itself anchored directly to Pad 39A’s concrete foundation. In short, Falcon Heavy (and especially Falcon 9) is not going anywhere until those hold-down clamps are explicitly released. Thanks to SpaceX’s avoidance of the solid rocket boosters used by almost every other modern launch vehicle, Falcon 9 and Heavy rockets can abort at any point prior to clamp release, offering a uniquely broad abort capability.
As such, not only does SpaceX’s dedicated pre-launch static fire fully test the rocket’s health, but the same procedure is essentially repeated in the seconds before clamp release during an actual orbital launch attempt. If at any point Falcon 9’s autonomous onboard computer decides that it doesn’t like any of the thousands of channels of telemetry it’s constantly analyzing, it can command an engine shutdown and total launch abort even if all first stage engines have already ignited and reached full thrust. If routine McGregor, TX acceptance testing – also involving a full static fire – is accounted for, every single Falcon 9 booster technically completes three fully-integrated static fires before its inaugural liftoff. Falcon Heavy is slightly different, as each booster is independent test-fired in Texas but the integrated rocket can only perform static fires at Pad 39A.
After those three critical tests, flight-proven Falcon boosters are subjected to the less stringent few-second static fires SpaceX performs at the launch pad 3-7 days before a given launch. With Falcon Heavy Flight 3, the rocket’s center core, upper stage, and payload fairing are all brand new, fresh from either SpaceX’s Hawthorne factory or McGregor acceptance testing. However, both side cores – Block 5 boosters B1052 and B1053 – are flight-proven, having successfully completed their first launches and landings on April 11th, less than 70 days ago.
Set by regular old Falcon 9 boosters, SpaceX’s current record for booster turnaround time (time between two launches) is 71 days (set in June 2018), while the Block 5 upgrade’s record stands at 74 days (set in October 2018). If Falcon Heavy’s STP-2 launch holds strong on June 24th, B1052 and B1053 will simultaneously tie SpaceX’s Block 5 turnaround record. This would be accomplished despite the added pressure from the US Air Force’s decision to use STP-2 as a sort of dress rehearsal for certifying all flight-proven commercial rockets, an honor (and burden) that likely added extra work, oversight, and scrutiny to the process of refurbishing and relaunching B1052 and B1053.
“[T]he US Air Force has decided that STP-2 presents an excellent opportunity to begin the process of certifying flight-proven SpaceX rockets for military launches. The STP-2-related work is more of a preliminary effort for the USAF to actually figure out how to certify flight-proven commercial rockets, but it will still be the first time a dedicated US military mission has flown on a flight-proven launch vehicle. Down the road, the processes set in place thanks – in part – to STP-2 and Falcon Heavy may also apply to aspirational rockets like Blue Origin’s New Glenn and ULA’s “SMART” proposal for Vulcan reuse.”
— Teslarati.com, 06/16/2019
In a last-second surprise, SpaceX updated Falcon Heavy center core B1057’s planned drone ship landing site from a brief 40 km (25 mi) to more than 1240 km (770 mi) off the coast of Florida. SpaceX set its current record for recovery distance less than three months ago during Falcon Heavy’s commercial launch debut, in which Block 5 center core B1055 landed nearly 970 km (600 mi) offshore on drone ship Of Course I Still Love You (OCISLY). If all goes well, B1057 – the second finished Block 5 center core – will absolutely crush its predecessor’s record, implying that the booster will likely be subjected to SpaceX’s most difficult reentry and recovery yet.
For more on what CEO Elon Musk describes as “[SpaceX’s] most difficult launch ever”, check out these previous articles on an unexpected ultra-fast booster reentry and the extraordinary challenge facing Falcon upper stage.
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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.”
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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.
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.
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
Tesla earns top honors at MotorTrend’s SDV Innovator Awards
