News
What’s causing SpaceX’s Falcon Heavy delays?
Although uncertainty in the schedule remains, SpaceX’s Falcon Heavy rocket appears to be nearly ready for its first engine ignition test (called a ‘static fire’) sometime within the next week or so.
An attempt at 1 PM EST today, January 16, was canceled for unspecified reasons, although Kennedy Space Center reportedly maintained the usual roadblock to prevent vehicles from driving past, implying that SpaceX still intends to conduct propellant loading tests with Falcon Heavy. It was noted earlier this morning by spaceflight journalist Chris Bergin that things were “a bit too quiet” if a test was indeed planned for today, and his intuition appears to have been correct. It still remains the case that Falcon Heavy is an experimental and untested rocket to an extent, and these delays are to be expected as SpaceX works out the inevitable kinks and bugs that arise during the extensive testing big launch vehicle has been and is still being put through.
KSC is in roadblock stance, so they will still do some testing it would seem, but we will have to wait for the Static Fire itself. https://t.co/DxzsRn85NR
— NSF – NASASpaceflight.com (@NASASpaceflight) January 16, 2018
Due to range requirements in support of an upcoming launch of the United Launch Alliance’s (ULA) Atlas 5 rocket, currently NET Thursday, SpaceX has postponed the static fire of Falcon Heavy without a replacement date. It is unlikely that another attempt will occur before the upcoming weekend, but SpaceX should have at least a solid week of uninterrupted range support once ULA’s launch occurs, hopefully without delay. Godspeed to ULA, in the meantime.
The crazy complexity of rocketry
Most recently, and perhaps somewhat related to Falcon Heavy’s static fire delays, SpaceX completed as many as two complete wet dress rehearsals (WDRs), which saw Falcon Heavy topped off with full tanks of its cryogenic (super cool) liquid oxygen (LOX) and rocket-grade jet fuel (RP-1). In essence, the rocket became equivalent to several hundred tons of carefully stabilized explosive. Nominally, these rehearsals appear entirely uneventful to an outside observer, with little more than ice formation and the occasional bursts of propellant tank vents to suggest that something important is occurring. However, anomalies like the failure of Falcon 9 during the Amos-6 static fire provide a staggering demonstration of just how explosive and sensitive a rocket’s fuel is, and Falcon Heavy has approximately three times the fuel capacity of Falcon 9. Empty, Falcon 9’s mass has been estimated to be around 30 metric tons, a minuscule amount of structure in the face of the more than 500 metric tons of propellant the vehicle carries at liftoff.
These propellant loading tests can also be challenging for reasons aside from their highly explosive nature. Due to basic realities of the physical nature of metal, the predominate ingredient for Falcon 9’s load-bearing structures, metallic structures shrink under extreme cold (and expand under heating). In the case of Falcon 9’s massive 45 meters (150 foot) tall first stage, the scale of this contraction can be on the order of several inches or more, particularly given SpaceX’s predilection towards cooling their propellant as much as possible to increase its energy density. For Falcon 9, these issues (thermodynamic loads) are less severe. However, add in three relatively different first stage boosters linked together with several extremely strong supports at both their tops and bottoms and that dynamic loading can become a fickle beast. The expansion or compression of materials due to temperature changes can create absolutely astounding amounts of pressure – if you’ve ever forgotten a glass bottled drink in the freezer and discovered it violently exploded at some future point, you’ll have experienced this yourself.
With several inches of freedom and the possibility that each Falcon Heavy booster might contract or expand slightly differently, these forces could understandably wreak havoc with the high precision necessary for the huge rocket to properly connect with the launch pad’s ground systems that transmit propellant, fluids, and telemetry back and forth. Information from two reliable Kennedy Space Center sources experienced with the reality of operating rockets, as well as NASASpaceflight.com, suggested that issues with dynamic loads (such as those created by thermal contraction/expansion) are a likely explanation for the delays, further evidenced by their observations that much of the pad crew’s attention appeared to be focused at the base of Transporter/Erector/Launcher (TEL). The TEL base hosts the clamps that hold the rocket down during static fires and launches, as well as the Tail Service Masts (TSMs) that connect with the Falcon 9/Heavy to transport propellant and data to the first stage(s). These connection points are both relatively tiny, mechanically sensitive, and absolutely critical for the successful operation of the rocket, and thus are a logical point of failure in the event of off-nominal or unpredicted levels of dynamic stresses.
-
- The white bars in this photo are half of Falcon Heavy’s seperation mechanism. A number of actuators take the place of the more common solid rocket motors used with vehicles like the Delta IV Heavy. (SpaceX)
-
- Falcon Heavy’s three boosters and 27 Merlin 1D engines on full display. (SpaceX)
-
- Falcon Heavy. Modeled and rendered by NASASpaceflight forum user WBY1984. (WBY1984)
Test, launch, land, repeat.
All things considered, these difficulties demonstrate that even after months (even years) of relentless modeling, testing, remodeling, and retesting, rockets (and especially huge rockets like Falcon Heavy) are immensely complex, and even tiny mistakes can lead the vehicle to stray from its expected behavior. Quite simply, the reality of engineering only truly comes into play once hardware is fully in the loop, and it’s in this state that SpaceX has demonstrated again and again a distinct and elegant ability to learn from their hardware, rather than attempt to salve uncertainty with a neurotic and counterproductive level of statistical analysis, modelling, and documentation. The agile launch company still dabbles in those aspects when beneficial or necessary, but testing comes first in its importance.
The conclusion here, then, is that Falcon Heavy’s delays betray this aspect of SpaceX – a launch company that loves its fans, but also understands the need for cautious testing when it comes to new and untried rocket hardware. Whether Falcon Heavy succeeds or fails, SpaceX will learn from the proceedings, and they will be better off for it (although maybe less so financially…).
Follow along live as launch photographer Tom Cross and I cover these exciting proceedings as close to live as possible.
Teslarati – Instagram – Twitter
Tom Cross – Instagram
Eric Ralph – Twitter
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:
“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.”
🚨 Tesla’s Ashok Elluswamy reveals Nav decisions when encountering construction and parking options contain “some elements of reasoning”
More uses of reasoning will be shipped later this quarter, a big tidbit of info as we wait v14.3 https://t.co/jty8llgsKM
— TESLARATI (@Teslarati) January 9, 2026
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).
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.
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.
Tesla AI Head says future FSD feature has already partially shipped
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
