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SpaceX launches Japanese lander, NASA cubesat to the Moon

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A SpaceX Falcon 9 rocket has successfully launched a privately-developed Japanese Moon lander and a NASA Jet Propulsion Laboratory cubesat on their way to lunar orbit.

Following five back-to-back delays that pushed the launch from November to mid-December, Falcon 9 lifted off with Japanese startup ispace’s first HAKUTO-R Moon lander on December 11th, kicking off a multi-month journey that will take the spacecraft more than 700,000 miles (1.1M km) away from Earth. It’s not the first time SpaceX has launched a mostly commercial Moon lander, and it won’t be the last. SpaceX’s first Moon lander launch happened in February 2019, when Falcon 9 launched Israeli company SpaceIL’s Beresheet Moon lander as a rideshare payload on Indonesia’s PSN-6 geostationary communications satellite. Beresheet failed just a minute or two before touchdown, but the attempt was still a historic step for commercial spaceflight.

Just shy of three years later, SpaceX has launched another private Moon lander. Unlike Beresheet, which made its way to the Moon from geostationary transfer orbit (GTO), HAKUTO-R was Falcon 9’s main payload, allowing the rocket to launch it directly into deep space. A Jet Propulsion Laboratory (JPL) cubesat that missed a long-planned ride on NASA’s first Space Launch System (SLS) rocket also joined the Moon lander as a Falcon 9 rideshare payload.

Approximately four months from now, both spacecraft will reach the end of similar low-energy ballistic transfer trajectories, at which point they will have limited opportunities to enter lunar orbit and continue their missions. Reaching that checkpoint will require several successful orbital correction maneuvers and enough longevity to survive months in deep space, unprotected by Earth’s magnetic fields.

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If they make it that far, HAKUTO-R will conduct several more burns to reach low lunar orbit (LLO), where ispace will verify the spacecraft’s health and eventually attempt a soft landing on the Moon. A privately-developed spacecraft has never landed on an extraterrestrial body, so the prestige at stake is about as high as it can get. If JPL’s Lunar Flashlight spacecraft [PDF] survives its journey, it will enter a near-rectilinear halo orbit around a point of gravitational equilibrium (Lagrange point) between the Earth and Moon. Once on station, it will spend most of its time 9000 kilometers (~5600 mi) away from the Moon but occasionally fly within 15 kilometers (~9 mi) of the surface. Under JPL’s nominal mission plan, Lunar Flashlight will complete at least ten week-long orbits and use an infrared laser instrument to search for water ice in permanently-shadowed Moon craters during each close approach.

(JPL)
Lunar Flashlight is about the size of a briefcase. HAKUTO-R is much larger. (ispace)

Without context, both missions seem to complement each other well, and it’s not hard to imagine an alternative scenario where a cubesat like Lunar Flashlight was intentionally included to prospect for ice that a lander could then target. But the JPL cubesat’s presence on ispace’s HAKUTO-R was purely by accident. Because of certain design decisions made by NASA’s Space Launch System (SLS) rocket and Orion spacecraft contractors, the giant rocket is intended to launch cubesat rideshare payloads to the Moon, but those satellites are barely accessible for the entire time the rocket is configured for its unprecedentedly slow launch campaigns.

As a result, even though SLS lifted off for the first time in November 2022, its cubesat payloads had to be ready for launch and installed on the rocket in October 2021. Out of 14 planned payloads, four – including Lunar Flashlight – weren’t ready in time, forcing them to find other ways to deep space. Ironically, that may have been an unexpected blessing, as the ten payloads that did make the deadline wound up sitting inside SLS for 13 months, much of which was spent at the launch pad. Half of those satellites appear to have partially or completely failed shortly after launch.

Because of the extremely circuitous path the NASA rocket ultimately took to reach launch readiness, JPL was able to find a new ride to the Moon and launch less than one month after SLS and its co-passengers. Unlike those copassengers, Lunar Flashlight likely spent just a few weeks installed on Falcon 9 before launching to the Moon. Additionally, the SLS launch trajectory took it more or less directly to the Moon, giving its rideshare payloads just a handful of days to troubleshoot any problems discovered. Thanks to the slower, more efficient transfer orbit SpaceX used to launch HAKUTO-R, JPL should still have opportunities to enter a nominal orbit even if Lunar Flashlight requires weeks of in-space troubleshooting – far more margin for error than most SLS copassengers received.

Lunar Flashlight weighs about 14 kilograms (~31 lb) at liftoff, features two sets of solar arrays, and packs a first-of-its-kind chemical propulsion system designed to deliver up to 290 m/s of delta-V – a ton of performance for such a small satellite. HAKUTO-R weighs closer to 1.1 tons (~2400 lb) and is a far more capable spacecraft, in theory – a necessity to land softly on the Moon. At ispace’s request, Falcon 9’s low-energy ballistic transfer orbit reduced the lander’s performance requirements, but it will need roughly 2000-2500 m/s of delta-V to enter lunar orbit and land on the lunar surface.

On December 12th, ispace confirmed that HAKUTO-R is in excellent shape around 24 hours after liftoff. ispace says the lander has secured stable communications, a stable orientation in space, and positive power generation from its solar arrays. An ispace infographic indicates that the spacecraft will enter lunar orbit around mid-April if all goes to plan. With HAKUTO-R in a stable state, the next most important near-term milestone will be the successful use of its propulsion and navigation systems. The startup hopes to demonstrate smooth deep space operations, including routine trajectory correction maneuvers, within one month of launch.

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HAKUTO-R was SpaceX’s 56th successful launch of 2022 and the company’s second direct Moon launch this year after sending South Korea’s KPLO orbiter to the Moon in August.

(Richard Angle)
(Richard Angle)
Falcon 9 produced a beautiful artificial nebula as the plumes of its booster and upper stage interacted above Earth’s atmosphere. (Richard Angle)

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 announces crazy new Full Self-Driving milestone

The number of miles traveled has contextual significance for two reasons: one being the milestone itself, and another being Tesla’s continuing progress toward 10 billion miles of training data to achieve what CEO Elon Musk says will be the threshold needed to achieve unsupervised self-driving.

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Credit: Tesla

Tesla has announced a crazy new Full Self-Driving milestone, as it has officially confirmed drivers have surpassed over 8 billion miles traveled using the Full Self-Driving (Supervised) suite for semi-autonomous travel.

The FSD (Supervised) suite is one of the most robust on the market, and is among the safest from a data perspective available to the public.

On Wednesday, Tesla confirmed in a post on X that it has officially surpassed the 8 billion-mile mark, just a few months after reaching 7 billion cumulative miles, which was announced on December 27, 2025.

The number of miles traveled has contextual significance for two reasons: one being the milestone itself, and another being Tesla’s continuing progress toward 10 billion miles of training data to achieve what CEO Elon Musk says will be the threshold needed to achieve unsupervised self-driving.

The milestone itself is significant, especially considering Tesla has continued to gain valuable data from every mile traveled. However, the pace at which it is gathering these miles is getting faster.

Secondly, in January, Musk said the company would need “roughly 10 billion miles of training data” to achieve safe and unsupervised self-driving. “Reality has a super long tail of complexity,” Musk said.

Training data primarily means the fleet’s accumulated real-world miles that Tesla uses to train and improve its end-to-end AI models. This data captures the “long tail” — extremely rare, complex, or unpredictable situations that simulations alone cannot fully replicate at scale.

This is not the same as the total miles driven on Full Self-Driving, which is the 8 billion miles milestone that is being celebrated here.

The FSD-supervised miles contribute heavily to the training data, but the 10 billion figure is an estimate of the cumulative real-world exposure needed overall to push the system to human-level reliability.

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Tesla Cybercab production begins: The end of car ownership as we know it?

While this could unlock unprecedented mobility abundance — cheaper rides, reduced congestion, freed-up urban space, and massive environmental gains — it risks massive job displacement in ride-hailing, taxi services, and related sectors, forcing society to confront whether the benefits of AI-driven autonomy will outweigh the human costs.

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Credit: Tesla | X

The first Tesla Cybercab rolled off of production lines at Gigafactory Texas yesterday, and it is more than just a simple manufacturing milestone for the company — it’s the opening salvo in a profound economic transformation.

Priced at under $30,000 with volume production slated for April, the steering-wheel-free, pedal-less Robotaxi-geared vehicle promises to make personal car ownership optional for many, slashing transportation costs to as little as $0.20 per mile through shared fleets and high utilization.

While this could unlock unprecedented mobility abundance — cheaper rides, reduced congestion, freed-up urban space, and massive environmental gains — it risks massive job displacement in ride-hailing, taxi services, and related sectors, forcing society to confront whether the benefits of AI-driven autonomy will outweigh the human costs.

Let’s examine the positives and negatives of what the Cybercab could mean for passenger transportation and vehicle ownership as we know it.

The Promise – A Radical Shift in Transportation Economics

Tesla has geared every portion of the Cybercab to be cheaper and more efficient. Even its design — a compact, two-seater, optimized for fleets and ride-sharing, the development of inductive charging, around 300 miles of range on a small battery, half the parts of the Model 3, and revolutionary “unboxed” manufacturing — is all geared toward rapid production.

Operating at a fraction of what today’s rideshare prices are, the Cybercab enables on-demand autonomy for a variety of people in a variety of situations.

Tesla ups Robotaxi fare price to another comical figure with service area expansion

It could also be the way people escape expensive and risky car ownership. Buying a vehicle requires expensive monthly commitments, including insurance and a payment if financed. It also immediately depreciates.

However, Cybercab could unlock potential profitability for owning a car by adding it to the Robotaxi network, enabling passive income. Cities could have parking lots repurposed into parks or housing, and emissions would drop as shared electric vehicles would outnumber gas cars (in time).

The first step of Tesla’s massive production efforts for the Cybercab could lead to millions of units annually, turning transportation into a utility like electricity — always available, cheap, and safe.

The Dark Side – Job Losses and Industry Upheaval

With Robotaxi and Cybercab, they present the same negatives as broadening AI — there’s a direct threat to the economy.

Uber, Lyft, and traditional taxis will rely on human drivers. Robotaxi will eliminate that labor cost, potentially displacing millions of jobs globally. In the U.S. alone, ride-hailing accounts for billions of miles of travel each year.

There are also potential ripple effects, as suppliers, mechanics, insurance adjusters, and even public transit could see reduced demand as shared autonomy grows. Past automation waves show job creation lags behind destruction, especially for lower-skilled workers.

Gig workers, like those who are seeking flexible income, face the brunt of this. Displaced drivers may struggle to retrain amid broader AI job shifts, as 2025 estimates bring between 50,000 and 300,000 layoffs tied to artificial intelligence.

It could also bring major changes to the overall competitive landscape. While Waymo and Uber have partnered, Tesla’s scale and lower costs could trigger a price war, squeezing incumbents and accelerating consolidation.

Balancing Act – Who Wins and Who Loses

There are two sides to this story, as there are with every other one.

The winners are consumers, Tesla investors, cities, and the environment. Consumers will see lower costs and safer mobility, while potentially alleviating themselves of awkward small talk in ride-sharing applications, a bigger complaint than one might think.

Elon Musk confirms Tesla Cybercab pricing and consumer release date

Tesla investors will be obvious winners, as the launch of self-driving rideshare programs on the company’s behalf will likely swell the company’s valuation and increase its share price.

Cities will have less traffic and parking needs, giving more room for housing or retail needs. Meanwhile, the environment will benefit from fewer tailpipes and more efficient fleets.

A Call for Thoughtful Transition

The Cybercab’s production debut forces us to weigh innovation against equity.

If Tesla delivers on its timeline and autonomy proves reliable, it could herald an era of abundant, affordable mobility that redefines urban life. But without proactive policies — retraining, safety nets, phased deployment — this revolution risks widening inequality and leaving millions behind.

The real question isn’t whether the Cybercab will disrupt — it’s already starting — it’s whether society is prepared for the economic earthquake it unleashes.

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Tesla Model 3 wins Edmunds’ Best EV of 2026 award

The publication rated the Model 3 at an 8.1 out of 10, and with its most recent upgrades and changes, Edmunds says, “This is the best Model 3 yet.”

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Credit: Tesla

The Tesla Model 3 has won Edmunds‘ Top Rated Electric Car of 2026 award, beating out several other highly-rated and exceptional EV offerings from various manufacturers.

This is the second consecutive year the Model 3 beat out other cars like the Model Y, Audi A6 Sportback E-tron, and the BMW i5.

The car, which is Tesla’s second-best-selling vehicle behind the popular Model Y crossover, has been in the company’s lineup for nearly a decade. It offers essentially everything consumers could want from an EV, including range, a quality interior, performance, and Tesla’s Full Self-Driving suite, which is one of the best in the world.

The publication rated the Model 3 at an 8.1 out of 10, and with its most recent upgrades and changes, Edmunds says, “This is the best Model 3 yet.”

In its Top Rated EVs piece on its website, it said about the Model 3:

“The Tesla Model 3 might be the best value electric car you can buy, combining an Edmunds Rating of 8.1 out of 10, a starting price of $43,880, and an Edmunds-tested range of 338 miles. This is the best Model 3 yet. It is impressively well-rounded thanks to improved build quality, ride comfort, and a compelling combination of efficiency, performance, and value.”

Additionally, Jonathan Elfalan, Edmunds’ Director of Vehicle Testing, said:

“The Model 3 offers just about the perfect combination of everything — speed, range, comfort, space, tech, accessibility, and convenience. It’s a no-brainer if you want a sensible EV.”

The Model 3 is the perfect balance of performance and practicality. With the numerous advantages that an EV offers, the Model 3 also comes in at an affordable $36,990 for its Rear-Wheel Drive trim level.

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