News
SpaceX’s Cargo Dragon spacecraft nears space station with 2.5 tons of cargo
Following a successful May 4th launch atop Falcon 9, SpaceX’s latest Cargo Dragon spacecraft is just a few hours away from starting its International Space Station (ISS) berthing sequence.
Scheduled to begin around 5:30 am EDT (09:30 UTC), SpaceX operations staff will command Dragon to continue a cautious ISS approach. Several hours later, the spacecraft will be quite literally grabbed by station astronauts and gently berthed with one of the space station’s several Common Berthing Mechanism (CBM) ports. Once Cargo Dragon has been safely joined with the ISS, the station’s crew of astronauts can begin the intensive process of unpacking more than 1500 kg (3300 lb) of pressurized cargo, including dozens of time-sensitive and complex science experiments.
Aside from the 1.5 tons of cargo contained inside Dragon’s climate-controlled cabin, ISS astronauts and ground-based NASA controllers will again use the space station’s robotic Canadarm2 manipulator to extract two large unpressurized payloads from Dragon’s trunk. The ‘flagship’ instrument of CRS-17 is NASA’s Orbiting Carbon Observatory-3 (OCO-3), an upgraded follow-on to OCO-2 that should dramatically improve the quantity and quality of data available on the distribution of carbon in the Earth’s atmosphere. The second trunk-stashed payload is known as STP-H6 and is carrying around half a dozen distinct experiments.
Both STP-H6 and OCO-3 will be installed on the outside of the space station with the help of Canadarm2, an extremely useful capability that limits the need for astronauts to suit up and perform risky and time-consuming EVAs (extra-vehicular activities) outside the ISS. With its trunk emptied, Cargo Dragon will eventually discard the section to burn up in Earth’s atmosphere just before the reusable capsule begins its own reentry.
Unlike several other spacecraft with service sections, both proposed, flying, or retired, SpaceX’s Dragon spacecraft strive to minimize the complexity and cost of their expendable service sections. For both Cargo and Crew Dragon, the trunk serves as a structural adapter for unpressurized payloads and the Falcon-Dragon interface, hosts solar arrays and radiators, and doesn’t do much else. All propulsion, plumbing, and major avionics are kept within the capsule to maximize reusability.
Defining “slow and steady”
The process of berthing or docking with the ISS is a fundamentally cautious thing, developed by NASA, Roscosmos, and other international partners through forced and painful trial and error. In short, the road to today’s cautious procedures has been paved with countless failures and close calls over decades of space activity. For Cargo Dragon, the process involves berthing, more passive and less complex than docking. Outside of a dozen or so meters, the processes begin quite similarly. Cargo Dragon (Dragon 1) will very slowly approach the station’s several-hundred-meter keep out zone, typically no faster than a few m/s (mph).
Then follows a back-and-forth process of stop and go, in which SpaceX commands Dragon forward, halts at set locations, verifies performance and station readiness with NASA, and repeat. Once within 10 or so meters of the ISS, Dragon will begin carefully stationkeeping, essentially a version of formation flying without a hint of aerodynamic forces. ISS astronauts will then command the Canadarm2 robotic arm toward a sort of target/handle combo located on the spacecraft. The arm follows similar stop-start procedures before finally grappling Dragon, at which point the astronauts in command are legally required (/s) to quip something along the lines of “We’ve caught ourselves a Dragon!”
From start to finish, the process takes about 1.5 hours under optimal conditions. Around 2.5 hours after that, Canadarm2 will physically berth Dragon with one of several ISS berthing ports. Soon after, station astronauts can open Dragon’s hatch, snag some fresh goodies, and begin the unpacking process. CRS-17’s ISS arrival operations will be covered live on NASA TV.
Check out Teslarati’s Marketplace! We offer Tesla accessories, including for the Tesla Cybertruck and Tesla Model 3.
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
