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How the Tesla Cybervault, Optimus & the Megapack fit into Master Plan Part 3 [Photos]

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Tesla pulled out all the stops during China’s International Consumer Goods Fair. The Cybervault, Mebagpack, and Optimus—the Tesla bot—were all part of the exhibit. 

Tesla’s exhibit in China focused on the company’s Master Plan Part 3. The three main components of Tesla’s next phase are meeting electricity demand, establishing renewable electricity supply, and investing in material development and next-level manufacturing.  div class=”in-article-ad”>

Electricity Demand & Supply

Meeting electricity demand by providing supply from sustainable resources is central to the company’s future goals. As such, it is fitting that the Megapack was featured at the exhibit in China. 

Earlier this week, Tesla announced the construction of a Megapack factory in China located in Shanghai’s Lingang area. Construction on Tesla’s Megapack factory in China is expected to start in the third quarter of this year. Tesla estimated an initial production capacity of 10,000 units per year or nearly 40 kWh worth of energy storage from its Megafactory in China. Production is expected to start at the beginning of Q2 2024. 

In line with meeting electricity demand, the Tesla Cybervault also appeared in the company’s exhibit in China. The Cybervault is clearly inspired by Tesla’s Cybertruck. The home EV charger pile has a similar shape to Tesla’s pickup truck and appears to be made of the same material as the Cybertruck’s exoskeleton. The Cybervault is a little bit bigger than Tesla’s original wall connector but might make up for its size with its design.

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In Master Plan Part 3, Tesla emphasizes the importance of having EV chargers available at home and the workplace to supplement charging stations. The Cybervault is an excellent way to generate interest in home-charging solutions for electric vehicles. 

Material & Manufacturing Investments

Tesla dedicated a whole section in its Master Plan Part 3 to the investment required for the materials it needs to reach its goals.

Tesla identifies a few materials that need significant capacity growth to reach a sustainable energy economy. In the mining industry, Tesla believes nickel, lithium, graphite, and copper mining need to undergo some capacity growth. While in the refining industry, nickel, lithium graphite, cobalt, copper, and battery-grade iron and manganese need some more attention.

Manufacturing investments go hand-in-hand with investments in materials. The company’s work on the Tesla bot seems to directly connect to its manufacturing goals. 

Tesla has an ambitious vehicle sale goal of for its next phase. It also plans to launch an all-electric van, bus, and a compact vehicle. It will take a lot of manpower to produce and run the factories necessary to build and deliver 89 million units—and that might be how the Tesla bot fits into Master Plan Part 3. 

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Elon Musk has stated that the Tesla bot will address human labor shortage in the future. The company predicts that Optimus could help with boring, repetitive tasks or dangerous work. 

“[The Tesla Bot] has the potential to be a generalized substitute for human labor over time. The foundation of the economy is labor. Capital equipment is essentially distilled labor… The fundamental constraint is labor. There are not enough people. I can’t emphasize this enough,” Musk said during an interview. 

The Teslarati team would appreciate hearing from you. If you have any tips, contact me at maria@teslarati.com or via Twitter @Writer_01001101

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Maria--aka "M"-- is an experienced writer and book editor. She's written about several topics including health, tech, and politics. As a book editor, she's worked with authors who write Sci-Fi, Romance, and Dark Fantasy. M loves hearing from TESLARATI readers. If you have any tips or article ideas, contact her at maria@teslarati.com or via X, @Writer_01001101.

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Elon Musk dispels $52 billion SpaceX-NVIDIA GPU deal: ‘Fake news’

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Credit: SpaceX

Elon Musk dismissed reports claiming SpaceX had placed a massive order for NVIDIA GPUs worth $52 billion. The denial came hours after Taiwanese media, citing unnamed industry sources, reported that SpaceX planned to acquire approximately 13,000 AI server racks, equating to roughly 1 million GB300 GPUs, from Foxconn.

Each rack was estimated at around $4 million, with deliveries potentially starting in late 2025.

The story suggested this would mark SpaceX’s first major foray into Foxconn-manufactured NVIDIA hardware, breaking from suppliers like Supermicro and Dell. Musk responded bluntly on X:

Despite the denial, the rumored scale aligns with SpaceX’s explosive growth in AI infrastructure. NVIDIA’s GB300 (successor to the GB200 NVL) racks deliver unprecedented performance for large-scale training and inference. A $52 billion commitment would dwarf most corporate AI budgets and provide the compute muscle needed for frontier models.

SpaceX already operates gigawatt-scale terrestrial clusters like Colossus in Memphis, Tennessee, and has monetized them aggressively through leasing deals.

SpaceX’s newest Starmind will make earth data centers obsolete

Major customers include Anthropic (paying ~$1.25 billion monthly for 220,000+ GPUs), Google (~$920 million monthly for 110,000 GPUs), and Reflection AI. These arrangements are projected to generate tens of billions in annual revenue, far outpacing traditional SpaceX businesses.

Such an investment would fuel internal AI efforts, particularly Grok models under the integrated SpaceXAI division, while supporting ambitious orbital data center plans. SpaceX envisions launching thousands of AI-optimized satellites powered by solar energy and cooled in space, bypassing terrestrial power and land constraints.

This “Starmind” constellation could position the company as a leader in space-based computing.

SpaceX as an Emerging AI Powerhouse

Once primarily known for reusable rockets and Starlink satellite internet, SpaceX has transformed into a multifaceted AI player.

The 2026 acquisition of xAI integrated Grok development directly into the company. Starlink’s low-latency global network complements massive compute clusters, enabling efficient data flow for training and serving AI models.

Musk has long argued that AI scaling demands solutions beyond Earth, citing things like real estate and electricity limits on the ground.

While the Foxconn deal may not be in the cards, SpaceX’s trajectory is continuing on the path of blending aerospace engineering with hyperscale AI to dominate both launches and intelligence infrastructure.

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Elon Musk sheds details on Tesla FSD’s upcoming improvements

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Credit: Tesla

Elon Musk shed more details on the upcoming improvements to Tesla’s Full Self-Driving suite, specifically one that the CEO mentioned last week, which should help owners see fewer interventions.

Last week, Musk hinted that one major improvement that Tesla planned to roll out to Full Self-Driving users was the car’s ability “to remember your specific interventions and match each person’s individual preferences.”

Elon Musk says your Tesla will start to learn your individual preferences

This small bit of detail was linked to a post from Tesla community member Whole Mars, who said that FSD’s tendency to exit the carpool lane, a feature that owners can turn on but at times the car will disregard.

It sounds like, based on Musk’s two responses since that original post, it is safe to say the things FSD will start to remember are wide-ranging. However, it seems the biggest differences will be noticed with parking performance, which Musk continues to mention.

Highway Lane Preferences

The initial post Musk mentioned, with these new remembered preferences soon to arrive for Tesla owners everywhere, was the Carpool/Express Lane.

Tesla has a setting in the FSD menu that lets drivers enable HOV Lane travel. However, the car won’t always stay in that suggested or preferred lane.

Some owners have also complained of left lane camping, an illegal maneuver in at least some states. Cruising in the passing lane has resulted in tickets for some, as it is illegal in over 30 states in the U.S.

Tesla did not confirm if these preferences would also be included in new FSD behaviors, but it would certainly help move the company toward fewer interventions.

Parking Preferences

This seems to be the real focus of the entire operation, as Musk stated several weeks ago that parking was overwhelmingly the most frequent reason for interventions.

The major issue with parking is not necessarily the parking “performance,” as FSD is generally good at parking. It definitely has its issues; we’ve recorded plenty of them, including this one as recent as last week:

However, the changes coming are more about preferences, meaning where you park and how your car enters the spot, either pulling in or backing in. Owners have also reported that pulling into the correct driveway is a relatively rare thing for FSD, something else that needs to be confronted.

Musk basically confirmed that all of these things would be part of Tesla’s plan to address driver preferences with FSD:

It’s obvious there is something big coming with FSD, and the company’s focus seems to be eliminating any intervention that would be related to preferences. This is probably the biggest bottleneck between Tesla and being fully autonomous. Critical interventions do occur, but they are much less frequent.

The only time a driver should be taking over is because of a critical intervention; this seems to be the goal of Tesla right now.

This all seems to be a priority as Tesla continues to move closer to the prospect of unsupervised driving.

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Elon Musk says your Tesla will start to learn your individual preferences

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Credit: Tesla

Elon Musk said today on X that Teslas will start to learn your individual preferences. This is something that he seemed to hint toward earlier this month when he said parking was by far the biggest reason drivers intervene with Full Self-Driving.

Musk made the comment in response to notable Tesla influencer Whole Mars, who said that his vehicle will sometimes disobey the settings he has enabled for his car. He responded to the post, stating that “The car will start to remember your specific interventions and match each person’s individual preferences.”

This is something that could be perhaps one of the biggest ways Tesla could minimize or even work closer toward eliminating interventions altogether. While FSD does a lot of things really well, many people intervene a vast majority of the time not due to major or critical safety errors.

Instead, many take over because the car is doing something that they do not like as a preference; it might park in a parking spot that is not preferred by the driver, it might linger too long in the left lane on the highway (a personal favorite), or it could even take a route that the driver does not like.

These all lead to interventions, but they are not triggered by a major safety issue. Instead, it’s just preference.

READ OUR REVIEW OF TESLA’S LATEST FSD VERSION:

Tesla Full Self-Driving v14.3.5 Early Impressions: new features and early performance

If Teslas could start to learn the personal preferences of the person who owns them, interventions will truly begin to be less frequent. Some of this is already pretty evident, in my opinion. Teslas use a neural network to learn behaviors and accumulate data to improve performance.

For months now, we’ve tracked FSD’s performance at “Except Right Turn” stop signs, something that is very common in Pennsylvania, but many of our readers located in other parts of the U.S. have never heard of. FSD handles one Except Right Turn stop sign very well, one that I travel past frequently. Others that I do not navigate through as often do not have as confident a performance. It seems like the cars might already be doing this to an extent.

That example is also for something that is a street sign and not necessarily a driver preference; however, I still feel it is worth mentioning because it only handles that commonly passed Except Right Turn stop sign with true confidence. Others it still seems to struggle with.

This could be one of Tesla’s big moves toward full autonomy, and it could be a pathway to truly unsupervised driving. Every day, millions of cars on the road travel at a human driver’s personal preferences with no incident. Why can’t autonomous vehicles still cater to a passenger’s preferences while being autonomous? Tesla seems to have the idea that it would be possible.

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