MAROKO133 Breaking ai: China designs dexterous wheeled robot concept to support lunar rese

📌 MAROKO133 Update ai: China designs dexterous wheeled robot concept to support lu

Engineers in China are exploring a new robotic system designed to operate as a versatile worker on the Moon. Developed by researchers from the Beijing Institute of Spacecraft System Engineering, the concept combines wheeled mobility with humanlike dexterity, allowing the machine to travel across the lunar surface while carrying out a wide range of tasks. 

These include construction work, equipment maintenance, scientific experiments, as well as collecting and analyzing lunar samples. According to the team, the robot’s mechanical design is built for flexibility and precision. Its waist can rotate roughly 180 degrees in either direction and bend forward up to 90 degrees, enabling it to reach and position tools more effectively in challenging environments. 

Meanwhile, its articulated hand offers four degrees of freedom, allowing for delicate manipulation, the researchers explained, detailing the design and its capabilities in a paper published in the Journal of Deep Space Exploration.

Advantages of wheeled locomotion for lunar operations

According to the researchers, a wheeled mobility system could give the robot a significant operational advantage on the Moon. An active suspension mounted on wheels allows the platform to move faster and remain more stable than traditional bipedal walking systems, creating a steady base for the robot’s upper body while it performs tasks. 

The team noted that China already relies on wheeled locomotion for planetary exploration, pointing to the success of its Yutu lunar rovers and the Zhurong rover on Mars. To withstand the Moon’s harsh terrain and temperatures, the robot’s wheels are expected to use a lightweight metal mesh design reinforced with steel-wire treads, the South China Morning Post reported.

This structure provides durability while maintaining flexibility and shock absorption, helping the vehicle maintain traction and travel long distances smoothly across the rugged lunar surface even in extreme cold.

Humanoid-style machines have long been considered useful for assisting astronauts in space missions. One early example is Robonaut, a project jointly developed by NASA and General Motors. In 2011, the robot became the first humanoid system deployed in orbit when it was sent to the International Space Station.

China pushes forward multinational lunar base project

China has outlined plans for a new lunar outpost that could serve as a long-term hub for scientific research and exploration. In 2021, the country proposed the creation of the International Lunar Research Station, a multinational project intended to be built near the Moon’s south pole. The facility is envisioned as a comprehensive scientific base capable of operating autonomously for extended periods, with astronauts visiting only for shorter missions while robotic systems handle much of the routine work.

Beijing is also preparing a series of missions and technologies that would pave the way for its future lunar base. One of the key steps is the upcoming Chang’e‑7 mission, scheduled to launch later this year, which will perform an in-situ investigation of possible water ice deposits in permanently shadowed craters near the Moon’s south pole.

In addition to the semi-humanoid robotic concept, the Beijing-based team has proposed another machine designed specifically for logistics. The platform features six legs and would be capable of performing a soft landing on the Moon before walking across the surface to transport cargo, forming part of a broader robotic system envisioned to help construct the future lunar research station.

🔗 Sumber: interestingengineering.com

📌 MAROKO133 Eksklusif ai: Railway secures $100 million to challenge AWS with AI-na

Railway, a San Francisco-based cloud platform that has quietly amassed two million developers without spending a dollar on marketing, announced Thursday that it raised $100 million in a Series B funding round, as surging demand for artificial intelligence applications exposes the limitations of legacy cloud infrastructure.

TQ Ventures led the round, with participation from FPV Ventures, Redpoint, and Unusual Ventures. The investment values Railway as one of the most significant infrastructure startups to emerge during the AI boom, capitalizing on developer frustration with the complexity and cost of traditional platforms like Amazon Web Services and Google Cloud.

"As AI models get better at writing code, more and more people are asking the age-old question: where, and how, do I run my applications?" said Jake Cooper, Railway's 28-year-old founder and chief executive, in an exclusive interview with VentureBeat. "The last generation of cloud primitives were slow and outdated, and now with AI moving everything faster, teams simply can't keep up."

The funding is a dramatic acceleration for a company that has charted an unconventional path through the cloud computing industry. Railway raised just $24 million in total before this round, including a $20 million Series A from Redpoint in 2022. The company now processes more than 10 million deployments monthly and handles over one trillion requests through its edge network — metrics that rival far larger and better-funded competitors.

Why three-minute deploy times have become unacceptable in the age of AI coding assistants

Railway's pitch rests on a simple observation: the tools developers use to deploy and manage software were designed for a slower era. A standard build-and-deploy cycle using Terraform, the industry-standard infrastructure tool, takes two to three minutes. That delay, once tolerable, has become a critical bottleneck as AI coding assistants like Claude, ChatGPT, and Cursor can generate working code in seconds.

"When godly intelligence is on tap and can solve any problem in three seconds, those amalgamations of systems become bottlenecks," Cooper told VentureBeat. "What was really cool for humans to deploy in 10 seconds or less is now table stakes for agents."

The company claims its platform delivers deployments in under one second — fast enough to keep pace with AI-generated code. Customers report a tenfold increase in developer velocity and up to 65 percent cost savings compared to traditional cloud providers.

These numbers come directly from enterprise clients, not internal benchmarks. Daniel Lobaton, chief technology officer at G2X, a platform serving 100,000 federal contractors, measured deployment speed improvements of seven times faster and an 87 percent cost reduction after migrating to Railway. His infrastructure bill dropped from $15,000 per month to approximately $1,000.

"The work that used to take me a week on our previous infrastructure, I can do in Railway in like a day," Lobaton said. "If I want to spin up a new service and test different architectures, it would take so long on our old setup. In Railway I can launch six services in two minutes."

Inside the controversial decision to abandon Google Cloud and build data centers from scratch

What distinguishes Railway from competitors like Render and Fly.io is the depth of its vertical integration. In 2024, the company made the unusual decision to abandon Google Cloud entirely and build its own data centers, a move that echoes the famous Alan Kay maxim: "People who are really serious about software should make their own hardware."

"We wanted to design hardware in a way where we could build a differentiated experience," Cooper said. "Having full control over the network, compute, and storage layers lets us do really fast build and deploy loops, the kind that allows us to move at 'agentic speed' while staying 100 percent the smoothest ride in town."

The approach paid dividends during recent widespread outages that affected major cloud providers — Railway remained online throughout.

This soup-to-nuts control enables pricing that undercuts the hyperscalers by roughly 50 percent and newer cloud startups by three to four times. Railway charges by the second for actual compute usage: $0.00000386 per gigabyte-second of memory, $0.00000772 per vCPU-second, and $0.00000006 per gigabyte-second of storage. There are no charges for idle virtual machines — a stark contrast to the traditional cloud model where customers pay for provisioned capacity whether they use it or not.

"The conventional wisdom is that the big guys have economies of scale to offer better pricing," Cooper noted. "But when they're charging for VMs that usually sit idle in the cloud, and we've purpose-built everything to fit much more density on these machines, you have a big opportunity."

How 30 employees built a platform generating tens of millions in annual revenue

Railway has achieved its scale with a team of just 30 employees generating tens of millions in annual revenue — a ratio of revenue per employee that would be exceptional even for established software companies. The company grew revenue 3.5 times last year and continues to expand at 15 percent month-over-month.

Cooper emphasized that the fundraise was strategic rather than necessary. "We're default alive; there's no reason for us to raise money," he said. "We raised because we see a massive opportunity to accelerate, not because we needed to survive."

The company hired its first salesperson only last year and employs just two solutions engineers. Nearly all of Railway's two million users discovered the platform through word of mouth — developers telling other developers about a tool that actually works.

"We basically did the standard engineering thing: if you build it, they will come," Cooper recalled. "And to some degree, they came."

From side projects to Fortune 500 deployments: Railway's unlikely corporate expansion

Despite its grassroots developer community, Railway has made significant inroads into large organizations. The company claims that 31 percent of Fortune 500 companies now use its platform, though deployments range from company-wide infrastructure to individual team projects.

Notable customers include Bilt, the loyalty program company; Intuit's GoCo subsidiary; TripAdvisor's Cruise Critic; and MGM Resorts. Kernel, a Y Combinator-backed startup providing AI infrastructure to over 1,000 companies, runs its entire customer-facing system on Railway for $444 per month.

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🔗 Sumber: venturebeat.com