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SpaceX wins launch contracts for three more Launcher space tugs
Startup ‘Launcher Space’ has chosen SpaceX to launch at least three more ‘Orbiter’ space tugs, meaning that the company will have a payload on every dedicated SpaceX rideshare launch planned from Q4 2022 to the end of 2023.
Following SpaceX’s third successful dedicated rideshare launch in January 2022, the company has another two missions – Transporter-4 and -5 – scheduled in the first half of the year. In October 2021, Launcher announced its Orbiter spacecraft program and plans to manifest the first vehicle on a SpaceX rideshare mission – likely Transporter-6 – scheduled to launch no earlier than (NET) October 2022.
Announced in the summer of 2019, SpaceX’s Smallsat Rideshare Program has offered one of the easiest and most affordable tickets to space for two and a half years. Following a handful of Starlink rideshare missions in 2020, SpaceX kicked off dedicated Transporter launches in January 2021 and has since delivered more than 320 customer satellites and payloads to orbit. By treating each Transporter mission a bit like public transit and also opening the door for third-party launch servicers, SpaceX has been able to somewhat simplify the tedious process of organizing large-scale rideshare missions.
Most importantly, thanks to the unprecedented affordability of its Falcon 9 rocket, SpaceX has allowed rideshare customers to reap a great deal of the benefits by charging just $1M per 200-kilogram (440 lb) ‘slot’ and a flat $5,000 for each additional kilogram. To anyone unfamiliar with the cost of spaceflight, that might seem obscene, but it’s extraordinarily affordable and far cheaper than every advertised alternative. Astra Space, the cheapest dedicated smallsat launch provider, sells a Rocket 3 vehicle capable of launching about 50 kilograms (110 lb) to a similar orbit for ~$3.5M – equivalent to $70,000 per kilogram. Rocket 3 has only completed one successful launch, however. Rocket Lab’s more accessible Electron rocket costs at least $7.5M for ~200 kilograms to sun-synchronous orbit (SSO) – a price of $37,500/kg.
Nonetheless, the single most significant drawback of rideshares – a one-size-fits-all orbit – remains. Short of a much more complex, expensive trajectory that would require Falcon 9’s upper stage to reignite several times, every payload launched on Transporter missions ends up in the same initial orbit. To solve that problem, a not insignificant number of companies have been formed in recent years to develop competitive orbital transfer vehicles. In theory, propulsive space tugs could potentially give rideshare payloads the best of both worlds – ultra-cheap launch costs and, within reason, delivery to a specific orbit of choice.
Launcher’s Orbiter is perhaps the most promising of the lot. Scheduled to debut no earlier than (NET) October 2022, Orbiter will use pressure-fed 3D-printed thrusters fed by ethane and nitrous oxide propellant stored in 3D-printed tanks. The company has already begun printing and hot-fire testing multiple thrusters, has received the first set of Orbiter avionics and solar panels, and seemingly remains very confident about the schedule for that spacecraft’s launch debut.
Additionally, Launcher is actually publicizing pricing for the stage. Bought outright, each Orbiter will cost about $400,000. Using its full 400 kg (880 lb) payload margin, a Falcon 9 launch with Orbiter – enabling precise orbital targeting – would cost a prospective customer about $3.5M – less than $9,000/kg. For a 200 kg (440 lb) payload, a Falcon 9 + Orbiter launch might cost less than $7,000/kg (~$2.5M). For Orbiter rideshare missions, Launcher will charge between $8,000 and $25,000 per kilogram – multiple times cheaper than alternatives at the low end and still competitive at the high end.
Other companies like Spaceflight Industries, D-Orbit, Momentus, Exolaunch, and more are also developing – or already flight-testing – their own space tugs, though most are being cryptic about their prices and capabilities.
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.”
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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.
Tesla AI Head says future FSD feature has already partially shipped
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
