The weekend spat that put a spotlight on orbital compute

Sam Altman and Elon Musk traded insults on social media over the weekend, and buried under the name-calling was a real disagreement about the future of computing in orbit.

Musk accused Altman of being a scammer. Altman fired back: “homeboy you’re the one sellling [sic] public market investors on short-term space datacenters.”

Set aside the schoolyard tone, and Altman’s jab lands close to what many industry insiders have concluded but public market investors seem to be ignoring: space data centers are not going to be a meaningful business anytime soon.

Why SpaceX’s orbital data center pitch is so seductive

SpaceX’s plan to launch a fleet of orbital data centers for AI inference work is a big reason the company is valued at $2 trillion. Bullish analysts see the potential for that processing power to fuel SpaceXAI’s models or serve as an orbital neocloud — something unprecedented in the AI boom.

The vision is compelling: put high-powered computing above the atmosphere, beam results down to Earth, and sidestep the terrestrial constraints of power and land. But experts who have actually studied the problem tell a different story.

What the experts say (when investors aren’t listening)

Talk to the entrepreneurs behind other space data center startups. Talk to the team at Google working on orbital compute. Talk to engineers who’ve run the numbers for fun. You get the same answer: this won’t make a big dent until we have much cheaper rockets and the ability to mass-produce high-powered satellites at low cost.

The economics simply don’t work yet. Launching a single satellite with meaningful compute power is expensive. Launching hundreds, or thousands, is currently inconceivable.

The Starship wildcard — and why it’s not enough

Musk’s answer to the skeptics is predictable: SpaceX‘s Starship, the massive new rocket, is expected to make its 13th test flight as soon as July 16. If Starship can fly again and again, the business case for space data centers could close.

But even a successful recovery of both stages on that test flight doesn’t mean operational reusable flight is right around the corner. It’s likely still years away. And even when Starship is flying regularly, space data center launches will take a back seat to SpaceX’s commitments to NASA and to building out its own Starlink network.

There’s another wrinkle. During its IPO road show, SpaceX conceded that Starship may not be fully reusable in the near term. Each launch might have to throw away its second stage. That would put a serious damper on the economics of orbital compute.

Musk’s “next year” promise falls flat

That’s why Musk’s rejoinder — “We start flying them next year” — doesn’t convince many people. Sure, SpaceX could launch a satellite equipped for high-speed data processing next year. That’s not the question.

The real question is when SpaceX can launch and manufacture these satellites at scale. And that’s likely a question for the 2030s.

For now, the gap between vision and reality in the space-compute business remains wide. Investors betting on near-term orbital data centers might be wise to listen to the engineers — and to Altman’s trash talk.

VentureBeat’s new research push has a name

Rob Strechay, formerly managing director and principal analyst at theCUBE Research, is now VentureBeat’s first Lead Analyst. He’s also a founding analyst of the company’s new research arm, VentureBeat Research.

The move signals something bigger than a single hire. VentureBeat is deliberately shifting toward specialization — analysis built for technical decision-makers like directors, VPs, CIOs, and CTOs who are actively evaluating, buying, and deploying enterprise AI.

“The enterprise AI stack is being rewritten in real time,” said VentureBeat’s leadership in announcing the appointment. “The decision-makers I talk with are starved for objective, defendable data.”

Why this hire matters now

The questions enterprise technology leaders are asking have changed. Organizations are moving past generative AI experimentation and into production deployment. They want to know how to orchestrate multi-vendor environments, where the security gaps in their agentic pipelines sit, and how to fix the utilization problems draining their infrastructure budgets.

News coverage alone can’t answer those questions. That’s the gap VentureBeat Research is built to fill.

An analyst who has sat on every side of the table

Strechay brings nearly three decades of experience as a practitioner, product executive, and industry analyst. Before becoming an analyst, he was an executive at startups including Zerto. He joined Amazon Web Services to help build a new analytics service. He later served as a senior analyst at Enterprise Strategy Group and, most recently, as managing director and principal analyst at theCUBE Research and SiliconANGLE.

His initial focus areas at VentureBeat: cloud infrastructure, advanced data infrastructure, platform engineering, DevOps orchestration and observability, and the intersection points where AI and enterprise security collide.

Already at work: GPU utilization and the VB Pulse surveys

Strechay hasn’t waited for an official start date. In May he published an analysis of enterprise GPU utilization, examining the compute waste sitting inside enterprise AI infrastructure. He also provided a substantive review of VentureBeat’s AI Infrastructure & Compute survey before it went into the field.

His infrastructure-level focus complements the research engine VentureBeat has built around its monthly VB Pulse surveys. These track five areas of enterprise AI adoption:

• Agentic orchestration
• Agent reliability and evals
• Agentic security and identity
• AI infrastructure and compute
• Context layers, including retrieval-augmented generation (RAG)

The June report on agentic orchestration, drawn from a survey of 145 enterprises, found that two-thirds had hedged their AI model strategy rather than committing to a single provider. The June outage of Anthropic’s Claude models made that posture’s value painfully clear.

VB In Conversation: The first vehicle

A core vehicle for this expanded research footprint will be a deepening of VentureBeat’s existing VB In Conversation video interview series, which Strechay will host. The series will bring architectural blueprints, actual deployment barriers, and back-end infrastructure realities to light through in-depth technical interviews with the architects and product leaders behind leading enterprise AI systems.

“VentureBeat has built an audience of enterprise builders and technology buyers that any analyst would want to serve,” Strechay said. “My goal is to use deep empirical metrics and VentureBeat’s proprietary tracking data to help enterprise buyers and the people building for them make sound platform and infrastructure decisions during the most disruptive transition enterprise technology has seen.”

What to expect next

The expanded VB In Conversation series will appear on VentureBeat and on VentureBeat’s YouTube channel, alongside Strechay’s written analysis on the site. Enterprise practitioners who want to take part in the monthly VB Pulse surveys, or arrange an analyst briefing with Strechay, can reach the research team directly.

For those tracking enterprise AI adoption trends, this hire is a signal. VentureBeat is betting that technical depth — not just news — is what enterprise buyers need most right now.

Samsung’s humanoid robot plans are real, but the factory floor comes first

Samsung wants a piece of the humanoid robot boom. But the company’s first concrete robotics push isn’t about a robot that walks your dog or folds your laundry. It’s about machines built for the factory floor.

The newly formed RX robotics division, led by a CEO, will initially focus on manufacturing robots. Samsung has separately flagged humanoids as a priority, though it hasn’t announced a commercial model or explained how one fits into the division’s near-term roadmap.

That gap between ambition and execution is telling. The machines Samsung can deploy first may look considerably less human than the ones in its promotional videos.

Why factories come first for Samsung’s robot push

The RX division fits neatly into Samsung’s broader plan to transform its manufacturing operations into AI-driven factories by 2030. The roadmap includes humanoids alongside assembly and logistics systems — but the sequencing matters.

Factories are an obvious starting market. The work is structured, the environment can be controlled, and Samsung already runs production facilities across the globe. That’s a far lower barrier to entry than a cluttered living room with unpredictable pets and toddlers.

That doesn’t mean the factory floor is just a training ground for future household humanoids. It gives Samsung somewhere practical to build an industrial robotics business while the grander promises remain unfinished. In other words, the company can make money now and dream later.

What Samsung could actually build first: the Rainbow Robotics RB-Y1

Samsung took control of Rainbow Robotics to accelerate its work on advanced robots, including humanoids. Rainbow was founded by researchers behind South Korea’s first bipedal humanoid, so the pedigree is real.

But the RB-Y1 offers a more realistic picture of what could arrive first. The robot has two arms and a human-like working range, yet it moves on wheels. It has reportedly undergone testing inside a Coupang warehouse, although Samsung hasn’t officially identified it as part of the RX division’s roadmap.

The design choice is pragmatic. Walking robots make impressive demonstrations. Wheels make more sense when the machine has a shift to finish. A robot that tips over on aisle three isn’t exactly a productivity win.

The case for wheeled robots in industrial settings

• Wheels are more stable and energy-efficient than legs for repetitive tasks
• Warehouse floors are flat and predictable, so legs add complexity without much benefit
• Maintenance costs are lower, and uptime is higher

That’s not to say Samsung has abandoned walking robots entirely. The company’s ambition clearly extends beyond conventional robot arms. But the first machines out of the gate will likely be the ones that can do a job reliably today, not the ones that look cool in a demo reel.

When could Samsung robots reach homes?

Samsung’s ambitions could eventually extend into stores and homes, but the company hasn’t announced a consumer humanoid or provided a launch window. Don’t hold your breath.

Its history with Ballie gives us reason to stay skeptical. The rolling home robot missed its planned release before Samsung repositioned it as an internal innovation platform. That’s a polite way of saying it didn’t ship as a consumer product.

So while Samsung’s smart home ecosystem continues to grow, a humanoid that folds your laundry remains firmly in the PowerPoint phase. The company’s immediate focus is on industrial robots, and that’s where the RX division will earn its keep.

What this means for the humanoid robot race

Samsung is hardly alone in chasing humanoids. Companies like Tesla with Optimus and Figure are pushing bipedal designs. But Samsung’s strategy is different: build the industrial business first, and let humanoids come later.

That’s a sensible approach, but it also means Samsung is playing catch-up in the consumer space. The company’s real strength lies in manufacturing and supply chain integration, which gives it a natural edge in factory automation.

For now, the takeaway is clear: Samsung humanoid robots are a long-term ambition, not a near-term product. The RX division will start with machines that work on wheels, in controlled environments, doing structured tasks. If that sounds less exciting than a robot butler, well, it is. But it’s also a lot more likely to actually ship.