

News
SpaceX drone ship fleet aces two Falcon 9 booster recoveries in 48 hours
SpaceX’s two-vessel drone ship fleet has successfully returned two boosters from sea to port in the space of just ~40 hours, an impressive feat that simultaneously shed light on a new kind of bottleneck for Falcon launches.
Completed on January 20th and 24th and originally planned as few as 25 hours apart, SpaceX’s back-to-back Starlink-16 and Transporter-1 launches made it clear that drone ship availability could quickly become a constraint as the company eyes increasingly ambitious launch cadence targets. CEO Elon Musk has stated that SpaceX is targeting up to 48 launches in 2021, translating to an average of one launch every 7.5 days.
As it turns out, measured from port departure to port arrival, that target is practically the same as the average amount of time it takes one of SpaceX’s two drone ship landing platforms to complete a booster recovery. Both existing drone ships must be slowly towed to and from the booster landing area, generally involving a minimum round trip of 800 miles (~1300 km) and some five days in transit.
In other words, even given a perfectly optimized schedule in which SpaceX launches missions requiring at-sea recovery every ~180 hours throughout 2021, each mission would have just a handful of days worth of margin before one launch delay would inherently delay another launch. Fundamentally, with a fleet of two drone ships requiring an average of five days of transit time per recovery, SpaceX could theoretically support as many as ~70 booster recoveries annually assuming zero downtime, no launch delays, and mere hours spent at the landing zone before turning around and heading back to port.
To be clear, recovery ship availability is an excellent problem to have, as it implies that SpaceX is fast approaching a rate of launch (and routine rocket landings) unprecedented in the history of commercial spaceflight. Thankfully, SpaceX also has an exceptional track-record of solving hard problems and there remains a great deal of ‘slack’ to be optimized out of its fleet of recovery ships.
That is all to say that removing the fundamental bottlenecks posed by SpaceX’s existing fleet will absolutely require at least one or two new drone ships on top of at least two major oil rig conversion projects in work for Starship. Whether in the form of one or more new converted barges or some kind of faster, self-propelled vessel, it’s safe to say that new ships are virtually guaranteed and likely close at hand unless SpaceX has decided to accept a semi-arbitrary ceiling on annual East Coast launches.
Just one month into 2021, SpaceX’s two drone ships are already being stretched to their operational limits to the point of launch delays. Delayed from January 17th to January 20th, Starlink-16 held up drone ship Just Read The Instruction for several days, resulting in the vessel returning to port on the 24th, just ~60 hours prior to Starlink-17’s original January 27th launch target. With drone ship Of Course I Still Love You (OCISLY) already indisposed at sea to support SpaceX’s January 24th Transporter-1 launch, SpaceX had to move Starlink-17 to January 30th.
After a few days in port for booster processing and maintenance, drone ship JRTI ultimately departed Port Canaveral for Starlink-17 on the evening of the 27th, most likely delaying the launch to Sunday, January 31st. For now, though, Falcon 9 booster B1049 is scheduled to launch for eighth time no earlier than (NET) 7:24 am EST (12:24 UTC), January 30th. Simultaneously, drone ship Of Course I Still Love You will likely need to depart Port Canaveral later this weekend to support Starlink-18, scheduled to launch as soon as 1:19 am EST, February 4th.
News
Tesla Model 3 gets perfect 5-star Euro NCAP safety rating
Tesla prides itself on producing some of the safest vehicles on the road today.

Tesla prides itself on producing some of the safest vehicles on the road today. Based on recent findings from the Euro NCAP, the 2025 Model 3 sedan continues this tradition, with the vehicle earning a 5-star overall safety rating from the agency.
Standout Safety Features
As could be seen on the Euro NCAP’s official website, the 2025 Model 3 achieved an overall score of 90% for Adult Occupants, 93% for Child Occupants, 89% for Vulnerable Road Users, and 87% for Safety Assist. This rating, as per the Euro NCAP, applies to the Model 3 Rear Wheel Drive, Long Range Rear Wheel Drive, Long Range All Wheel Drive, and Performance All Wheel Drive.
The Euro NCAP highlighted a number of the Model 3’s safety features, such as its Active Hood, which automatically lifts during collisions to mitigate injury risks to vulnerable road users, and Automatic Emergency Braking System, which now detects motorcycles through an upgraded algorithm. The Euro NCAP also mentioned the Model 3’s feature that prevents initial door opening if someone is approaching the vehicle’s blind spot.
Standout Safety Features
In a post on its official Tesla Europe & Middle East account, Tesla noted that the company is also introducing new features that make the Model 3 even safer than it is today. These include functions like head-on collision avoidance and crossing traffic AEB, as well as Child Left Alone Detection, among other safety features.
“We also introduced new features to improve Safety Assist functionality even further – like head-on collision avoidance & crossing traffic AEB – to detect & respond to potential hazards faster, helping avoid accidents in the first place.
“Lastly, we released Child Left Alone Detection – if an unattended child is detected, the vehicle will turn on HVAC & alert caregivers via phone app & the vehicle itself (flashing lights/audible alert). Because we’re using novel in-cabin radar sensing, your Tesla is able to distinguish between adult vs child – reduced annoyance to adults, yet critical safety feature for kids,” Tesla wrote in its post on X.
Below is the Euro NCAP’s safety report on the 2025 Tesla Model 3 sedan.
Euroncap 2025 Tesla Model 3 Datasheet by Simon Alvarez on Scribd
Elon Musk
USDOT Secretary visits Tesla Giga Texas, hints at national autonomous vehicle standards
The Transportation Secretary also toured the factory’s production lines and spoke with CEO Elon Musk.

United States Department of Transportation (USDOT) Secretary Sean Duffy recently visited Tesla’s Gigafactory Texas complex, where he toured the factory’s production lines and spoke with CEO Elon Musk. In a video posted following his Giga Texas visit, Duffy noted that he believes there should be a national standard for autonomous vehicles in the United States.
Duffy’s Giga Texas Visit
As could be seen in videos of his Giga Texas visit, the Transportation Secretary seemed to appreciate the work Tesla has been doing to put the United States in the forefront of innovation. “Tesla is one of the many companies helping our country reach new heights. USDOT will be right there all the way to make sure Americans stay safe,” Duffy wrote in a post on X.
He also praised Tesla for its autonomous vehicle program, highlighting that “We need American companies to keep innovating so we can outcompete the rest of the world.”
National Standard
While speaking with Tesla CEO Elon Musk, the Transportation Secretary stated that other autonomous ride-hailing companies have been lobbying for a national standard for self-driving cars. Musk shared the sentiment, stating that “It’d be wonderful for the United States to have a national set of rules for autonomous driving as opposed to 50 independent sets of rules on a state-by-state rules basis.”
Duffy agreed with the CEO’s point, stating that, “You can’t have 50 different rules for 50 different states. You need one standard.” He also noted that the Transportation Department has asked autonomous vehicle companies to submit data. By doing so, the USDOT could develop a standard for the entire United States, allowing self-driving cars to operate in a manner that is natural and safe.
News
Tesla posts Optimus’ most impressive video demonstration yet
The humanoid robot was able to complete all the tasks through a single neural network.

When Elon Musk spoke with CNBC’s David Faber in an interview at Giga Texas, he reiterated the idea that Optimus will be one of Tesla’s biggest products. Seemingly to highlight the CEO’s point, the official Tesla Optimus account on social media platform X shared what could very well be the most impressive demonstration of the humanoid robot’s capabilities to date.
Optimus’ Newest Demonstration
In its recent video demonstration, the Tesla Optimus team featured the humanoid robot performing a variety of tasks. These include household chores such as throwing the trash, using a broom and a vacuum cleaner, tearing a paper towel, stirring a pot of food, opening a cabinet, and closing a curtain, among others. The video also featured Optimus picking up a Model X fore link and placing it on a dolly.
What was most notable in the Tesla Optimus team’s demonstration was the fact that the humanoid robot was able to complete all the tasks through a single neural network. The robot’s actions were also learned directly from Optimus being fed data from first-person videos of humans performing similar tasks. This system should pave the way for Optimus to learn and refine new skills quickly and reliably.
Tesla VP for Optimus Shares Insight
In a follow-up post on X, Tesla Vice President of Optimus (Tesla Bot) Milan Kovac stated that one of the team’s goals is to have Optimus learn straight from internet videos of humans performing tasks, including footage captured in third person or by random cameras.
“We recently had a significant breakthrough along that journey, and can now transfer a big chunk of the learning directly from human videos to the bots (1st person views for now). This allows us to bootstrap new tasks much faster compared to teleoperated bot data alone (heavier operationally).
“Many new skills are emerging through this process, are called for via natural language (voice/text), and are run by a single neural network on the bot (multi-tasking). Next: expand to 3rd person video transfer (aka random internet), and push reliability via self-play (RL) in the real-, and/or synthetic- (sim / world models) world,” Kovac wrote in his post on X.
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