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SpaceX begins Falcon Heavy booster deliveries for first launch in two years
SpaceX’s first Falcon Heavy rocket launch in almost two years has entered the final stages of preparations – flight hardware acceptance testing, delivery, and assembly.
Comprised of five major elements, the vast majority of the challenges of building and launching Falcon Heavy come from the rocket’s three first-stage boosters – each more or less equivalent to a single-core Falcon 9 booster. Falcon Heavy’s twin side boosters are by far the most visually recognizable sign of that similar-but-different nature thanks to the need for aerodynamic nosecones instead of a Falcon booster’s normal interstage (a hollow cylinder).
While easily recognizable, the center core is the most technically Falcon Heavy-specific part of SpaceX’s partially-reusable heavy-lift rocket, requiring a unique airframe relative to side cores, which are essentially Falcon 9 boosters with a few major add-ons. It’s one of those Falcon Heavy side boosters that was spotted traveling by road from SpaceX’s test facilities to a Florida launch pad on Tuesday, January 26th.
For unknown reasons, although SpaceX currently has two reused Falcon Heavy side boosters that flew a second time on the US Air Force’s own STP-2 mission, the company has manufactured all-new boosters – likely at the US military’s request – for the rocket’s fourth launch. Rebadged from AFSPC-44 to USSF-44, that mission will see SpaceX attempt its first-ever direct-to-GEO launch, nominally launching a several-ton mystery satellite directly into geostationary orbit (GEO).
The main challenge of direct-to-GEO launches is the need for a given rocket’s upper stage to coast for hours in orbit and then reignite after that multi-hour coast period. The direct launch profile also demands more delta-V (propellant) than alternative transfer orbits (GTOs) – propellant that must be launched into orbit in addition to the customer’s payload. That requires the use of extremely large and/or efficient rockets, which is why SpaceX is launching USSF-44 with Falcon Heavy instead of a much cheaper and simpler Falcon 9.
Unlike all other direct-to-GEO launches in history, however, Falcon Heavy Flight 4 will (hopefully) mark the first time a rocket launches a payload into geostationary orbit while still recovering a large portion of its first stage. After liftoff, Falcon Heavy side boosters B1064 and B1065 will attempt the first-ever dual drone ship landing at sea, while the rocket’s custom center core will be intentionally expended. According to CEO Elon Musk, that sacrificial-center-core configuration theoretically allows Falcon Heavy to achieve ~90% of its expendable performance while still recovering two otherwise reusable boosters.
As of the first USSF-44 side booster’s appearance in Louisiana, at least one other booster (most likely the mission’s second side booster) has already been spotted at SpaceX’s McGregor, Texas development facilities and may have already completed its own round of static fire acceptance testing. Given the three-month gap between the first USSF-44 side booster’s static fire and a side booster’s appearance in transport, there’s a distant possibility that the booster spotted on January 26th was the second of two side boosters to ship east, but that’s improbable given how much Falcon boosters stick out on the road.
Ultimately, assuming the second USSF-44 side booster’s static fire acceptance test went well, the only major Falcon Heavy-specific hardware SpaceX needs to ship from its Hawthorne, CA headquarters is center core B1066. An upper stage and payload fairing will also have to pass acceptance testing and head to Florida but both will likely be standard Falcon 9-issue hardware, minimizing small-batch uncertainty.
If SpaceX delivers B1066 to McGregor within the next week or two, the center core should be ready to ship to Florida by March or April, leaving SpaceX two or three months to integrate, static fire, and prepare Falcon Heavy for its fourth launch. According to the latest official information from the US military, USSF-44 is scheduled to launch no earlier than (NET) “late-spring 2021,” likely implying late-May or June.
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
