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SpaceX fires up first upgraded Starship engine

A Raptor 1 engine performs a static fire in 2019. (SpaceX)

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CEO Elon Musk has implicitly revealed that SpaceX recently conducted the first test of Starship’s new Raptor 2 engine.

Aside from kicking off integrated static fire testing of a refined, operationalized version of Raptor, the first prototype may have briefly become the most powerful engine of its kind ever tested before destroying itself. While not quite as successful as the first static fire campaign of a full-scale Raptor 1 engine, which survived several tests, the first Raptor 2 prototype’s early demise is still a routine part of engine development and is the start of a process that should ultimately produce a Super Heavy booster with 50% more thrust than the next most powerful rocket ever flown.

Prior to last weekend, it’s likely that competitor Blue Origin’s BE-4 – still in development and hoped to one day power ULA’s Vulcan and the company’s own reusable New Glenn – was the most powerful methane/oxygen rocket engine ever tested. BE-4 is designed to produce up to 244 tons (~539,000 lbf) of thrust. On its very first static fire, it appears that SpaceX’s first finished Raptor 2 prototype has narrowly stolen BE-4’s crown, briefly generating main combustion chamber pressures of 321 bar (~4650 psi) and as much as 245 tons (~540,000 lbf) of thrust.

To BE-4’s credit, the engine (at least as far as Blue Origin’s sparse public communications go) didn’t destroy itself after its first full-thrust static fire. Raptor 2 wasn’t so lucky and apparently exploded before completing its first test. There’s also some ambiguity as Blue Origin’s own website pegs BE-4 thrust at “2400 kN (550,000 lbf)” when 2400 kilonewtons is actually equivalent to 539,000 lbf. Regardless, designed to produce up to 230 tons (~510,000 lbf) of thrust in flight, Musk has said that Raptor 2 or V2.0 “is a major improvement in simplification” over Raptor 1, which nominally produces up to 185 tons (~410,000 lbf) of thrust at chamber pressures closer to 270 bar (~3900 psi).

It’s not all that surprising, then, that the first Raptor 2 prototype ever completed exploded when SpaceX pushed it to almost 107% of its maximum rated thrust and main chamber pressure during its first test.

Though impressive, SpaceX has technically pushed Raptor 1 prototypes further – and without failure. Musk later indicated that there was some damage present but a fairly young Raptor 1 engine still made it all the way up to 330 bar (~4800 psi) and spent about 10 seconds at chamber pressures above 320 bar without failure during an August 2020 stress test. Still, had the Raptor 2 prototype also made it to 330 bar, it would have produced around 252 tons (555,000 lbf) of thrust – 12% more than its Raptor 1 predecessor.

Super Heavy boosters will ultimately have 33 more or less identical sea-level-optimized Raptors – 13 Raptor Center (RC) engines with thrust vectoring and 20 Raptor Boost (RB) engines without. (NASASpaceflight – bocachicagal)
Starship’s design features three Raptor Centers and three Raptor Vacuums. Musk has suggested a variant with 3 RCs and 6 RVs as a possible upgrade path. (Elon Musk)

According to Musk, the main differences between Raptor 1 and Raptor 2 are “much cleaner” plumbing and wire harnesses and a wider combustion chamber throat, which allows the engine to produce more thrust in roughly the same package at the cost of a slight efficiency loss. Over the last two years, the CEO has mentioned the possibility of a power-optimized Raptor variant with up to 300 tons of thrust but in recent months, Musk says SpaceX has decided to keep the Raptor family as streamlined as possible and opted for just two variants – one with a sea-level nozzle (Raptor Center and Boost) and one with a larger vacuum-optimized nozzle (RVac).

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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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Elon Musk

Tesla AI boss reveals how big Optimus is going to get

Tesla’s Optimus chief corrected himself on X, confirming a staggering 10 million robot production target.

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Tesla Optimus Gen 3 [Credit: Tesla]

Tesla’s Optimus program has a new number attached to it, after Ashok Elluswamy, the executive who has run the humanoid robot program since June 2025, posted a three word correction on X Thursday, “Correction, 10 million robots.”

The line clarifies the long term annual capacity Tesla is building toward its planned second Optimus production line at Gigafactory Texas, a figure Musk has cited repeatedly since last year’s shareholder meeting.

The scale is worth noting, because ten million robots a year would mean Tesla building more units annually than most countries sell in new cars. Tesla has framed this as a second line, not the first. The buildout is happening in two phases: a roughly one million unit per year line inside Tesla’s Fremont factory, installed on the floor space vacated when Model S and Model X production ended earlier this year, and a much larger dedicated facility under construction at Giga Texas that broke ground on its first steel structure in May. That Texas facility is the one Elluswamy’s correction refers to, and is expected to reach volume production sometime in 2027.

Tesla Optimus project fires up as Musk sees production line progress

Elluswamy took over Optimus from Milan Kovac last summer and has spent the months since talking up the program’s trajectory. Elon Musk has also floated the ten million figure at Tesla’s 2025 shareholder meeting.

Ending Model S and Model X production to make room for the first Optimus line was one of the more consequential manufacturing decisions in the company’s recent history, retiring two flagship vehicles in favor of a robot that has yet to enter mass production. Musk has previously estimated per unit production costs at $20,000 to $25,000 once Tesla reaches a million units a year, though he hasn’t said what that cost looks like at ten times the volume.

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Autonomous vehicle red tape gets slashed by Trump Administration

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Credit: Zoox

The Trump Administration today made several key moves to help with the deployment of autonomous vehicles by cutting overreaching red tape that has stifled growth and innovation for years.

The moves, which were put forth by the National Highway Traffic Safety Administration (NHTSA), aim to grant temporary exemptions to at least one company currently, although that could expand in the coming months. Additionally, it will work with organizations to develop standards and a sound but efficient regulatory landscape.

Zoox is the only company mentioned explicitly by the Trump Administration in its press release announcing the new terms today. They will receive a temporary two-year exemption that will allow the commercial deployment of up to 2,500 vehicles annually for two years.

There is a potential exemption for Robomart, Inc., which “requests a temporary exemption from certain FMVSS No. 500 requirements for a low-speed vehicle operated by an ADS without a human driver onboard. NHTSA will publish a separate notice seeking public comment on its merits once the initial evaluation is complete,” the agency said.

Here are the five new terms that Secretary Sean Duffy has implemented through the NHTSA today:

  1. Allow Zoox to commercially deploy its robotaxis through a temporary exemption.
    This temporary exemption will allow the commercial deployment of up to 2,500 vehicles annually for two years, subject to an enhanced, adaptable oversight structure that can evolve as Zoox’s technology advances.
  2. Accelerate development of first-ever AV performance standards through a partnership with SAE Industry Technologies Consortia (ITC).
    This partnership will fund a three-year, $5 million “A2SCEND” consortium, bringing together experts to gather data and accelerate creation of the first-ever AV performance standards. This project will inform a single national standard for AV safety to eliminate the patchwork regulatory landscape that has stifled innovation for years.
  3. Publish an interim final rule that allows vehicles manufactured prior to an exemption to be eligible for a commercial deployment exemption.
    This rule will modernize the application process and improve access to exemptions for innovators, including AV developers, by granting the NHTSA Administrator the discretion to apply temporary exemptions to vehicles manufactured prior to the effective date of an exemption grant.
  4. Streamline the application process for Part 555 exemptions by updating guidance and soliciting feedback from the public.
    By updating the Part 555 exemption process—which allows automakers to temporarily sell a limited number of non-compliant vehicles, primarily to test new technologies—NHTSA is aiming to create a more flexible oversight structure for exemptions and summarize recent AV framework activities, including expanded exemption pathways, streamlined crash reporting, and ongoing efforts to modernize Federal Motor Vehicle Safety Standards (FMVSS).
  5. Establish a new Federal Docket for public feedback on NHTSA’s updated safe AV development and deployment guidance.
    NHTSA is updating its technical guidance for AVs for the first time since 2017—focusing on key safety areas like emergency responder interactions, safety management systems, remote assistance, and post-crash behavior to help the industry scale up driverless deployments safely.

Additionally, the NHTSA said it has modernized some safety standards by proposing updates to:

  • FMVSS 102 – Transmission shifting
  • FMVSS 103/104 – Windshield defrosting and wiping
  • FMVSS 110 – Tire placards
  • FMVSS 135 – Braking systems
  • FMVSS 101 – Controls and displays
  • FMVSS 108 – Vehicle lighting
  • FMVSS 111 – Mirrors and rearview display
  • FMVSS 126 – Electronic stability control systems
  • FMVSS 201/208 – Sun visors and warning labels

These changes aim to make the regulatory process for autonomous vehicles more streamlined and efficient, which could help the U.S. gain dominance over autonomous vehicle systems moving forward.

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Elon Musk has a crazy prediction about AI in two years

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Daniel Oberhaus, CC BY-SA 4.0 , via Wikimedia Commons

Elon Musk is, in many respects, one of the biggest and most influential figures in modern-day artificial intelligence.

Given that Tesla, SpaceX, and xAI are all looked at in their respective fields as leaders to an extent, each of them has a heavy influence on the future of AI, even though two of them are not thought of, at face value, as AI companies.

Musk has grand expectations for what is to come with AI, not only as a form of assistance to make human lives easier, but to make humans multiplanetary and solve some of the biggest issues that face us today. But even he is astounded by AI’s pace of progress.

He believes that in two years, AI will be so mind-blowing it might be unrecognizable.

This progress can be seen in a variety of ways, but perhaps the most popular way people have shown AI’s progress, especially on social media, is through an incredibly arbitrary way of watching Will Smith eat spaghetti:

This is a great way to show people how AI is improving, especially from a perspective that examines how it can manufacture images and video from prompts. AI is an incredibly complex concept, however, and it goes much deeper than Will Smith eating Italian food.

Musk’s most widely adopted method of AI is likely Tesla Full Self-Driving, which impacts millions of people as they utilize it to increase safety with their travel. Musk has routinely pushed incredibly aggressive timelines for self-driving, especially unsupervised.

Perhaps this perspective is why he feels that things will be solved in a timeframe that is much more aggressive than most of us would think. Regardless, the progress of AI is moving fast, and it seems that Musk’s expectations for it could be high.

But if it can actually achieve full-length motion pictures and even more realistic production value, it will be hard to distinguish between reality and AI very soon.

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