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Relive SpaceX’s high-altitude Starship launch debut in 4K [video]

Starship SN8's launch and (explosive) landing debut. (Richard Angle)

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SpaceX has published a 4K recap of Starship serial number 8’s (SN8) spectacular high-altitude launch debut, highlighting all crucial aspects of the immensely successful test flight and hinting at the next steps forward.

On December 9th, after days of anticipation and delays for the unprecedented test flight, Starship SN8 sailed through a clean preflight flow, ignited three Raptor engines, and lifted off around 4:45 pm CST – just 15 minutes before the launch window was scheduled to close. In a move that would later be confirmed to be intentional, Starship’s ascent went exactly as planned with all three Raptors sequentially shutting down over the course of almost five minutes – necessary, said Elon Musk, to keep the rocket from “[blowing] through the [12.5-kilometer] altitude limit.”

Although technical difficulties prevented a high-altitude NASA reconnaissance jet from capturing aerial footage of the spectacle from up high, SpaceX certainly seems to have made do with more mundane platforms, capturing all aspects of Starship SN8’s launch in high definition.

At apogee, Starship SN8 vented most of the remaining liquid oxygen in its main tank and shut down the last active Raptor engine, kicking off an unprecedented guided freefall back to Earth. To achieve that feat, Starship SN8 had to reach apogee more or less vertical, begin falling tail-first, activate cold-gas thrusters and actuate four giant flaps to tilt belly-down, and use those same thrusters and flaps to maintain stability.

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Liftoff to apogee. (SpaceX)

Likely reaching speeds of around 150 m/s (~330 mph) during that freefall, Starship SN8 made it look effortless, twitching its flaps and occasionally using a burst of thrusters to elegantly and stably glide back to about 1 km (~0.6 mi) above the ground. At that point, the rocket ignited one – and then two – Raptor engines with no apparent issue, gimballing violently and firing thrusters to flip its 9m by 50m (30 ft by 165 ft) hull ~120 degrees in a handful of seconds, ending in a tail-down landing configuration.

Up to that point, more than six minutes into the flight test, Starship SN8 had all but aced the gauntlet of firsts SpaceX had thrown at it, notably surpassing CEO Elon Musk’s expectation of a successful ascent but otherwise failed descent.

Freefall descent, powered descent, and a rather hard “landing”. (SpaceX)

Instead, SN8 made it just a dozen or two seconds away from a soft landing before things went wrong. According to Musk, who commented after the fact, the Starship’s fuel (methane) header tank – a small secondary tank used to store landing propellant at high pressures – began to exhibit lower than needed pressures in the seconds before touchdown. Whether intentional or not, one of the two Raptors ignited during SN8’s flip maneuver shut down around ten seconds later, at which point the lone remaining engine throttled up only to have its plume turn an almost solid green.

In simple terms, without enough pressure in the fuel header, Raptor’s combustion turned very oxygen-rich, dramatically ramping up the heat and literally melting the engine’s copper-rich combustion chamber liner (hence the green hue). Had that tank been able to maintain pressure, it’s reasonable to assume that SN8 would have stuck a soft landing just like SN5 and SN6 did a few months prior. Thankfully, Musk says the source of the pressure issue was “minor” and, as SpaceX notes at the end of the recap, Starship SN9 is almost ready to carry the torch forward.

Eric Ralph is Teslarati's senior spaceflight reporter and has been covering the industry in some capacity for almost half a decade, largely spurred in 2016 by a trip to Mexico to watch Elon Musk reveal SpaceX's plans for Mars in person. Aside from spreading interest and excitement about spaceflight far and wide, his primary goal is to cover humanity's ongoing efforts to expand beyond Earth to the Moon, Mars, and elsewhere.

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Tesla Hardware 3 owners could be made whole this month

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Credit: Tesla Asia/Twitter

Tesla Hardware 3 owners are set to get a new Full Self-Driving version this month as the company plans to release what it is referring to as v14 Lite.

The rollout is not yet confirmed for June, but Tesla executives have stated on several occasions that this more refined FSD iteration will work with their cars and increase its capabilities.

This comes after Tesla admitted during its last Earnings Call that these Hardware 3 vehicles would not be able to achieve Full Self-Driving, something that they did not know when they bought these cars. We regularly receive messages from Hardware 3 owners asking when v14 Lite will come out, what they should expect, and whether it is worth it to upgrade the self-driving computer or buy a new car altogether.

It is hard not to feel for them; Tesla CEO Elon Musk said at the company’s 2019 Autonomy Day that all vehicles produced at the time, including Hardware 3 cars, had “all the hardware necessary, compute and otherwise, for Full Self-Driving.”

Musk also said in March of that year that, “Anyone who purchased Full Self-Driving will get FSD computer upgrade for free.”

However, during the Q1 2026 Earnings Call, Musk admitted that Hardware 3 vehicles would not be capable of FSD, as “It has only 1/8th the memory bandwidth of Hardware 4, and memory bandwidth is one of the key elements needed for unsupervised FSD.”

Tesla has made some effort to remedy these Hardware 3 owners by offering:

  • Discounted trade-ins toward AI4 cars
  • Hardware retrofits, which would replace the self-driving computer and upgrade all cameras
  • Full Self-Driving v14 Lite

The issue is that many of these owners were led to believe their cars would be capable of unsupervised self-driving. Now, they’re left scrambling for options, and while there are several, they will all require more money out of their pockets.

Expectations for Tesla v14 Lite for Hardware 3 Owners

The big differences between the AI4 v14 and v14 Lite for Hardware 3 owners will stem primarily from hardware constraints. Tesla developed v14 Lite with an optimized frame of mind; the v14 neural nets are toned down to run on an HW3 computer.

Tesla v14 will use the same behavior, but its limits will be hardware-related, especially given that the cameras on HW3 vehicles are lower-resolution.

Tesla reveals its plans for Hardware 3 owners who are eager for updates

This will result in potentially more edge cases due to the lower quality perception and less long-range detection, but reaction time and overall confidence should be more refined.

There should also be a handful of additional features that are available on AI4 cars, such as:

  • Starting Full Self-Driving from Park
  • Auto Shift
  • Streaks
  • Speed Profiles
  • Improved Dynamics, like Pulling Over for Emergency Vehicles

Tesla plans to release v14 Lite this month, but we are all familiar with how the company can be with timelines. Additionally, if v14 Lite has not proven to be ready for a wide release, Tesla will slam the brakes on the rollout.

We would anticipate that Tesla is testing v14 Lite internally, and likely has been for several months.

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SpaceXAI just launched into your kitchen with their new app

SpaceXAI just powered its first consumer app and it predicts what you want to buy.

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SpaceXAI just made its first move into consumer AI, and it involves your grocery cart. On June 3, 2026, Gopuff and SpaceXAI announced the launch of Go, a Grok-powered shopping assistant built directly into the Gopuff app that predicts what you need before you even start searching for it.

Gopuff is an instant delivery platform that operates more than 400 micro-fulfillment centers across the U.S., delivering everyday essentials, snacks, drinks, and household items in as little as 15 minutes. It is not a restaurant delivery app or a marketplace. It owns its inventory, controls its warehouses, and handles its own logistics, which means it has built one of the most detailed consumer behavior datasets in retail over its 13-year history.

Go combines SpaceXAI’s advanced reasoning, voice, and image generation models with Gopuff’s dataset of hundreds of millions of orders and real-time cultural signals from X to prepare a suggested cart the moment a customer opens the app. It learns each shopper’s habits and automatically builds a personalized cart based on time of day, location, order history, and real-time indicators. Returning customers can check out with a single tap.


Rather than searching for specific items, users can describe a situation like a game-day party or the desire for a healthy breakfast and Go will assemble a cart automatically. It can also predict when shoppers are running low on items like coffee or paper towels and have them packed and delivered in under 15 minutes. Grok voice integration lets users talk to the app in plain conversational language and check out completely hands-free.

Gopuff co-founder and co-CEO Yakir Gola said: “Today, we believe the greatest friction left in commerce is not delivery or instantaneous access to the essentials customers need. It’s the moment before: the thinking, the deciding, the remembering. We’re combining Gopuff’s demand intelligence with xAI’s frontier reasoning to create an everyday shopping experience that feels like a true extension of you.”

Why SpaceX just made a $60 billion bet on AI coding ahead of historic IPO

The timing carries context beyond the product launch. SpaceXAI was formed after SpaceX completed an all-stock merger with Elon Musk’s xAI earlier this year, folding one of the most advanced AI labs in the world into the same corporate structure as the company preparing what could be the largest IPO in history. SpaceXAI is dipping into consumer-focused AI just as it prepares for its public debut, and while Musk has openly discussed building an everything app, this launch uses Grok to power another company’s product rather than launching a standalone consumer platform. Every consumer-facing deployment of Grok ahead of the IPO roadshow adds tangible evidence that SpaceXAI is not just an infrastructure play but a direct competitor in the AI application layer where OpenAI and Google are already fighting for dominance.

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Tesla adds new Supercharger feature for a better idea of what to expect

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Credit: Tesla

Tesla has introduced an enhanced visualization in its Supercharger navigation system, building directly on the Site Maps feature rolled out a few months ago.

This latest software update adds detailed 3D icons that represent specific vehicle models parked at charging stalls, offering drivers a more precise view of site occupancy and layout.

The Site Maps debuted in Tesla’s 2025 Holiday Update, providing 3D overviews of select Supercharger locations with real-time stall availability.

Tesla supplements Holiday Update by sneaking in new Full Self-Driving version

Drivers could see which spots were open, occupied, or out of service when navigating to supported stations.

Now, the system takes this capability further by rendering accurate representations of Tesla vehicles, including distinctions between models such as the Model 3, Model Y, Model S, Model X, and Cybertruck. These icons appear as lifelike 3D renderings, complete with recognizable shapes and proportions that match the actual cars charging at the site:

This refinement improves the user experience during road trips and daily charging stops. As drivers approach a Supercharger, the navigation display now shows not just generic occupied markers but identifiable vehicle types plugged into each stall.

Blue indicators highlight active charging sessions, while other visual cues denote availability or maintenance status. The feature integrates seamlessly with the existing map interface, allowing quick assessment of the best available spot based on vehicle size and positioning.

Tesla continues to expand the availability of these detailed Site Maps across its global network. Initially piloted at a limited number of locations, the rollout has progressed steadily, with more stations gaining support in recent software versions.

Owners benefit from better planning, as the system helps identify compatible stalls and reduces uncertainty upon arrival. The update reflects Tesla’s ongoing commitment to refining its navigation and charging ecosystem through iterative software improvements.

In addition to model-specific icons, the enhanced maps maintain all prior functionalities, such as integration with nearby amenities and energy usage predictions. This ensures a comprehensive tool for efficient Supercharging.

As Tesla’s fleet grows and the network scales, such features play a key role in optimizing the overall ownership experience. Future updates may extend similar visualizations to additional sites and incorporate even more data points for drivers.

With this piggyback enhancement, Tesla demonstrates how small but thoughtful additions can elevate an already useful tool, making Supercharger visits smoother and more informed for its customers. The company is expected to broaden the feature’s reach in upcoming releases, further solidifying its leadership in EV charging infrastructure.

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