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SpaceX slashes base price of smallsat rideshare program, adds “Plates”
SpaceX has rolled out an upgraded version of its Rideshare program that will allow even more small satellite operators to send their spacecraft to orbit for extremely low prices.
SpaceX threw its hat into the growing ring of smallsat launch aggregators in August 2019 with its Smallsat Program. Initially, the company offered a tiered pricing scale with multiple rates for the different sizes of ports a satellite operator could attach their spacecraft to. For customers purchasing their launch services more than 12 months in advance, SpaceX aimed to charge a minimum of $2.25 million for up to 150 kilograms (~330 lb) and a flat $15,000 for each additional kilogram. Customers placing their order 6-12 months before launch would pay a 33% premium ($20,000/kg).
SpaceX may have sorely misjudged the market, however, because the company introduced a simpler, reworked pricing system just a few months later. SpaceX slashed prices threefold, removed most of the tier system, and added a portal that allowed customers to easily reserve launch services online. Compared to the first attempt, the new pricing – $1 million for up to 200 kilograms (~440 lb) and $5000 for each extra kilogram – was extraordinarily competitive and effectively solidified SpaceX as the premier source of rideshare launch services overnight. Save for an inflation-spurred increase to $1.1 million and $5500/kg, that pricing has remained stable for almost three years, and SpaceX’s Smallsat Program has become a spectacular success.
SpaceX, however, was unable to sit idle and has introduced several significant improvements to its rideshare services. While it technically hasn’t reduced its prices, SpaceX will now allow satellites as small as 50 kilograms to book directly through the company at its virtually unbeatable rate of $5500 per kilogram. Before this change, customers with small satellites would either have to pay for all the extra capacity they weren’t using, boosting their relative cost per kilogram, or arrange their launch services with a third-party aggregator like Spaceflight or Exolaunch.
Aggregators purchase slots on SpaceX’s rideshare missions and then seek out numerous small satellites (usually well under 50 kilograms each) to try to reach their 200-kilogram minimum, thus ensuring that even the smallest satellites can launch for close to the advertised rate of $5500 per kilogram. As is always the case, a subcontractor has its own bills to pay and profit margins to seek, so aggregators likely charge customers quite a bit more than SpaceX’s base price.
If price-gouging was a problem, SpaceX reducing its base price to $275,000 for up to 50 kilograms (~110 lb) will effectively lower the aggregator price ceiling fourfold. In general, it will also make purchasing rideshare launch services easier and cheaper for more prospective satellite operators. To ensure that, SpaceX also appears to be willing to book and integrate individual ‘containerized’ cubesats without the need for an aggregator’s dispenser.
That’s largely thanks to the biggest technical change to the Smallsat Program, which will see SpaceX replace its old cylindrical payload dispenser tower with a new “Rideshare Plate” system. Seemingly derived from the machined aluminum plates SpaceX uses to add rideshare payloads to Starlink launches, the plates should offer customers a more modular and flexible platform capable of supporting all kinds of payload adapters and dispensers.
These changes will likely help SpaceX continue to dominate the global satellite launch rideshare market. Since its Smallsat Program first took flight in January 2021, five dedicated Transporter rideshare launches and eight Starlink rideshare launches have delivered approximately 450 customer satellites and payloads to low Earth orbit (LEO). Seven more Transporter missions are scheduled between December 2022 and Q4 2024.
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.
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
