News
SpaceX's next Crew Dragon launch is delayed but that's actually good news
NASA says that SpaceX’s next big Crew Dragon flight test has slipped a bit further into 2020, a counterintuitively positive sign that the human-rated spacecraft’s next launch is firmly scheduled for the first month of the next decade.
Known as Crew Dragon’s In-Flight Abort (IFA) test, SpaceX opted to include the mission in its Commercial Crew contract, a decision NASA chose to leave up to its providers. Boeing, for example, chose not to perform a real-world in-flight abort test of its Starliner spacecraft, instead relying on a pad abort test and digital modeling to determine the spacecraft’s capabilities. NASA allowed this flexibility because it believes – at least theoretically – that it should be possible to determine whether a spacecraft can perform the most challenging abort scenarios without actually doing full-fidelity flight tests.
Given that NASA chose to perform an extremely expensive full-fidelity in-flight abort test with its own Orion spacecraft just a few months ago, one can’t exactly say that the space agency has chosen to reap what it’s sown, but with any luck, the Starliner spacecraft will never have to perform such an abort and find out how close Boeing’s modeling is to reality.
It’s also worth noting that despite the fact SpaceX elected to perform an extra abort test that will likely destroy an entire Falcon 9 rocket, Crew Dragon development will cost NASA $2 billion (40%) less than Starliner, while each operational Crew Dragon launch will also cost some $250 million (39%) less than a comparable Starliner launch.
As of December 18th, NASA says that SpaceX’s In-Flight Abort (IFA) test has slipped a week from January 4th to January 11th, 2020. Counterintuitively, that delay is actually an extremely encouraging sign that Crew Dragon’s next launch is quite firmly set for the first month of 2020. For reference, as NASA and SpaceX approached Crew Dragon’s Demo-1 orbital launch debut earlier this year, the mission was initially set for January 17th. Around three weeks later, NASA announced that Demo-1 had slipped to no earlier than (NET) “February”. Four weeks after that delay, NASA once again announced another delay to March 2nd, which would turn out to be the day that Crew Dragon really did reach orbit for the first time.
On the other hand, IFA – Crew Dragon’s second launch – had its first firm launch date (January 4th) announced by NASA on December 6th, 2019. Less than two weeks later, NASA says that the launch date has slipped by exactly one week to January 11th, less than four weeks from today. It’s entirely possible that SpaceX’s IFA test will slip further into 2020 in the coming weeks, but compared to Crew Dragon’s Demo-1 mission, both NASA and SpaceX appear to be far more confident in the schedule for Crew Dragon’s second launch.
Regardless of when exactly it lifts off, Crew Dragon’s In-Flight Abort is going to be an extremely challenging test for the spacecraft. Designed to simulate a near-worst-case abort scenario during launch, SpaceX will essentially trick Dragon into believing that Falcon 9 has failed around a minute and a half after launch. At that point, the rocket and spacecraft will be traveling as fast as Mach 2.5 (860 m/s, 1900 mph) and experiencing what is known as Max Q, the point of peak aerodynamic stress (referring to heating, buffeting, pressure, and more).
At that exact point, Crew Dragon capsule C205 will ignite all eight of its SuperDraco abort engines, almost instantaneously producing 130,000 lbf (570 kN) of thrust to send the spacecraft almost a kilometer (0.5 mi) away from Falcon 9 in just a few seconds. If Crew Dragon survives the ordeal, it will quickly detach its trunk section, flip around to face its heat shield towards the ground, and ultimately deploy parachutes before gently landing in the Atlantic Ocean.
SpaceX plans to recover and reuse the otherwise orbit-worthy capsule on a future mission, likely one of the company’s upcoming CRS2 space station resupply launches. Finally, if everything goes exactly as planned during the In-Flight Abort test and both NASA and SpaceX see no issues with the flown hardware or data the test produces, Crew Dragon Demo-2 – the spacecraft’s first astronaut launch – could potentially be ready for flight as early as February or March 2020.
Check out Teslarati’s Marketplace! We offer Tesla accessories, including for the Tesla Cybertruck and Tesla Model 3.
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
