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New Chinese humanoid robot shows off its strength by lifting 35 pounds per hand

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New Chinese humanoid robot shows off its strength by lifting 35 pounds per hand

China’s Shanghai Kepler Robotics is making waves in the world of humanoid robotics with its innovative Forerunner series. 

Its latest humanoid robot, the Forerunner K2, has quickly become a hot topic, showcasing Kepler’s commitment to pushing the boundaries of what robots can do. 

With each new development, Kepler is not just keeping pace with the competition. It’s setting the stage for a future where humanoid robots play an integral role in our everyday lives.

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Forerunner K2 humanoid robot  (Shanghai Kepler Robotics Co., Ltd)

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Pioneering technology

The original Forerunner, now known as K1, showcased Kepler’s advanced technology, including proprietary planetary roller screw actuators, intelligent dexterous hands and the Nebula AI system. Standing at 5 feet, 10 inches tall and weighing 187 pounds, the K1 was designed to compete directly with other leading humanoid robots in the market.

Forerunner K2 humanoid robot  (Shanghai Kepler Robotics Co., Ltd)

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The next generation: Forerunner K2

Building on the success of the K1, Kepler has introduced the Forerunner K2, representing the fifth generation of its humanoid robot technology. This latest model has undergone extensive software and hardware enhancements, tailoring it for commercial applications across various industries.

Forerunner K2 humanoid robot  (Shanghai Kepler Robotics Co., Ltd)

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Advanced features and capabilities

The Forerunner K2 features an impressive 52 degrees of freedom throughout its body, allowing for more natural and fluid movements. Its rotating and tilting head module, combined with improved arm and leg rigidity, enhances its overall functionality and ease of maintenance.

One of the most remarkable features of the K2 is its dexterous hands. Each hand supports up to 11 degrees of active and passive freedom and can carry up to 33 pounds. The fingertips are equipped with sensor arrays, each containing 96 contact points, enabling precise object manipulation and tactile sensing.

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Forerunner K2 humanoid robot  (Shanghai Kepler Robotics Co., Ltd)

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AI and software advancements

Kepler has significantly enhanced the K2’s vision system and navigation software, allowing it to better perceive and react to its environment in real time. The robot’s artificial intelligence capabilities have been expanded through a combination of embodied intelligence software, imitation and reinforcement learning and a cloud-based cognitive model.

These improvements enable the K2 to perform specific tasks autonomously and cooperate effectively with human operators. The robot’s stability and walking speed have also been improved through advancements in gait planning and control algorithms.

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Forerunner K2 humanoid robot  (Shanghai Kepler Robotics Co., Ltd)

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Commercial applications and future prospects

Kepler has positioned the Forerunner K2 as an ideal solution for various industries, including intelligent manufacturing, warehousing and logistics, high-risk operations and research and education. The company has already begun evaluating the K2’s performance in customer facilities, where it’s being used for materials handling, sample processing, patrol and inspection and quality control tasks.

With an estimated retail price range of $20,000 to $30,000, Kepler aims to make its humanoid robots accessible to a wide range of businesses. The company plans to commence mass production of its humanoid robots in the second half of 2024, positioning itself at the forefront of the industry.

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Forerunner K2 humanoid robot  (Shanghai Kepler Robotics Co., Ltd)

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Kurt’s key takeaways

Kepler’s Forerunner K2 is truly a game changer in the world of humanoid robotics, showcasing impressive advancements that hint at a future where these machines become commonplace in our workplaces. With rapid improvements from the K1 to the K2, it’s clear that Kepler is not just keeping pace but leading the charge in innovation. As these robots become more capable and affordable, we can expect to see them assisting us in various industries, from manufacturing to health care.

How comfortable are you with the increasing presence of humanoid robots like Kepler’s Forerunner K2 in everyday life and the workplace, and what concerns or benefits do you foresee? Let us know by writing us at Cyberguy.com/Contact

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Xbox is now XBOX

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Xbox is now XBOX

Xbox just allcapsmaxxed: Meet XBOX. This isn’t a joke; Microsoft appears to be actually rebranding Xbox to XBOX. Asha Sharma, Xbox CEO, ran a poll on X earlier this week, asking fans whether Microsoft should use Xbox or XBOX. The results were in favor of XBOX, and the company has now renamed its X account.

Curiously, the Threads and Bluesky accounts for Xbox haven’t been renamed yet, but if Microsoft is going ahead with a rebranding then I expect those will change soon. I asked Microsoft to comment on this potential Xbox rebranding and the company simply referred me to Sharma’s post.

The use of all caps for Xbox is a return to original form, though. Microsoft’s first Xbox logo for its console was all caps, and the company has favored using similar capped versions for the Xbox 360, Xbox One, and Xbox Series X / S console logos.

The apparent rebranding comes just a few weeks after Sharma scrapped Microsoft Gaming and renamed Microsoft’s gaming division back to Xbox. It’s part of Sharma’s continued promise of a “return of Xbox,” which has involved fan-focused console updates, a new Xbox logo, Game Pass pricing changes, and lots more in recent weeks.

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AI data centers may soon ride ocean waves

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AI data centers may soon ride ocean waves

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Artificial intelligence (AI) already shows up in your phone, your searches and plenty of apps you use every day. Now, some Silicon Valley investors are betting the machines behind those AI answers could one day run at sea.

A company called Panthalassa has raised $140 million in new funding to develop and deploy autonomous, floating AI computing nodes powered by ocean waves. The Series B round brings Panthalassa’s total funding to $210 million, a sign that investors are taking this ocean-based AI idea seriously. The round was led by Peter Thiel, the Palantir co-founder, and the company says the money will help complete a pilot manufacturing facility near Portland, Oregon. Panthalassa also plans to deploy its Ocean-3 pilot node series in the northern Pacific Ocean later in 2026.

Instead of building another giant AI data center on land, Panthalassa wants to place computing power out at sea. Ocean waves would generate electricity. Seawater would help with cooling. Onboard computing systems would process AI prompts and send the results back to land through low-Earth-orbit satellites.

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Panthalassa’s Ocean-2 prototype rides in open water during testing, giving a real-world look at the kind of floating wave-energy system behind the company’s ocean AI plan. (Panthalassa)

How AI data centers at sea could work

Panthalassa’s floating nodes are designed to capture wave motion and turn it into electricity. The company says it has spent a decade developing the technology behind its power generation, onboard computing and autonomous ocean operations. Its earlier Ocean-1, Ocean-2 and Wavehopper prototypes were tested in 2021 and 2024. Think of each node like a floating power station with AI hardware inside. Waves move the system. That motion helps drive a generator. The power then feeds the onboard chips.

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The company’s plan is to use those chips for AI inference. That is the part of AI where a model responds to your prompt after it has already been trained. In simple terms, it is what happens when you ask a chatbot a question and get an answer back. That makes the ocean plan a little easier to understand. Training massive AI models requires huge data movement and tight coordination. Answering prompts may be more realistic for a floating node, at least in some situations.

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Why AI data centers are moving offshore

AI data centers need huge amounts of electricity. They also need space, cooling systems and local support from communities that may not want a massive facility nearby. Those problems have pushed companies to look for unusual answers. Ocean-based computing is one of them.

Panthalassa says its nodes would operate far from shore in wave-rich parts of the ocean. The goal is to use that wave energy directly onboard instead of sending the power back to land. “We’ve built a technology platform that operates in the planet’s most energy-dense wave regions, far from shore, and turns that resource into reliable clean power,” said Garth Sheldon-Coulson, Panthalassa’s co-founder and CEO.

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The ocean also offers cold surrounding water. That could help cool the chips onboard. Cooling is a major issue because data centers produce a lot of heat. Panthalassa is taking a different path from traditional land-based data centers. Instead of pulling more power from the grid, it wants floating nodes that generate their own electricity from waves.

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The Ocean-2 prototype sits inside a coastal facility, showing the size and shape of Panthalassa’s floating node before deployment at sea. (Panthalassa)

The satellite problem for ocean AI data centers

The ocean may help with power and cooling, but it creates another problem: connection. Traditional data centers rely on high-capacity fiber-optic connections because they need to move huge amounts of data fast. A floating node far out at sea may depend on low-Earth-orbit satellite links. That can work for some AI responses, but it may be slower and more limited than fiber.

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The challenge grows when multiple nodes need to work together. AI systems often depend on fast communication between chips, servers and storage. If those parts are floating in the ocean and talking by satellite, coordination gets harder. That means AI data centers at sea may not replace land-based data centers anytime soon. They may be better suited for certain AI tasks where the model can live onboard, and the response does not require constant back-and-forth with other machines.

Repairing floating AI nodes could be difficult

There is another practical question: What happens when something breaks? A land-based data center can send in technicians. A floating AI node in rough seas may need a ship, special equipment and the right weather window. That adds cost and delay.

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Panthalassa says it is developing autonomous systems meant for harsh ocean conditions. Its press release says Ocean-3 testing is meant to demonstrate AI inference and refine manufacturing before commercial deployments in 2027. Still, the ocean is brutal. Saltwater eats away at equipment. Storms can turn a routine repair into a major operation. Constant motion also puts stress on the hardware. For this plan to work, Panthalassa will have to show that each node can keep running for years in harsh ocean conditions without frequent human repairs.

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Panthalassa’s Ocean-2 prototype is transported by barge, a reminder that building AI infrastructure at sea also means solving major deployment and maintenance challenges. (Panthalassa)

Ocean data centers have been tested before

Ocean data centers are not new. Microsoft experimented with underwater data center servers through Project Natick, including tests in 2015 and 2018. Those tests showed that sealed underwater servers could run reliably while using seawater for cooling, with Microsoft reporting a lower failure rate than comparable land-based systems. Microsoft later ended the project.

Chinese companies have also reportedly pushed ahead with underwater data center projects near Hainan and Shanghai. Keppel has explored floating data center designs in Singapore, where land constraints make the concept especially attractive. Panthalassa’s plan goes in a different direction. It combines wave power with onboard AI chips and satellite-based results. It also depends on floating nodes that would need to operate far from the kind of support a normal data center gets. That is why the idea is getting attention. It is also why skepticism is fair.

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What AI data centers at sea mean for you

For now, this will not change how your phone or computer works. You will not suddenly see a “powered by ocean waves” label on your favorite AI app. But the bigger picture affects everyone. AI needs an incredible amount of electricity. As more companies add AI tools to their products, they need more places to run those systems. That pressure can affect energy grids, water use, local battles over new data centers and even your utility bills over time.

Panthalassa argues its approach could reduce the need for new data centers and power plants on land. That could ease pressure on local communities and the grid, but the company still has to prove the system can work reliably at sea. If ocean-based AI moves beyond testing, it could also raise fresh questions about marine maintenance, environmental oversight and who controls computing infrastructure in international waters.

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Kurt’s key takeaways

Everyone is using AI on their phones and computers these days, but the heavy lifting often happens in huge data centers behind the scenes. That is why Panthalassa’s ocean plan is getting attention. The company wants to use waves for power and seawater for cooling. The hard part is proving that floating AI nodes can survive rough seas, limited satellite links and complicated maintenance. If Panthalassa can pull it off, ocean-based AI could become part of the tech we use every day. If it cannot, it may show just how difficult it is to keep feeding AI’s growing demand for power.

If this kind of ocean-powered AI takes off, would you worry about what these floating nodes could mean for our oceans? Let us know by writing to us at Cyberguy.com

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OpenAI keeps shuffling its executives in bid to win AI agent battle

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OpenAI keeps shuffling its executives in bid to win AI agent battle

OpenAI announced yet another reorganization Friday, consolidating certain areas and making company president Greg Brockman the official lead of all things product.

In a memo viewed by The Verge, Brockman wrote that since OpenAI’s product strategy for this year is to go all-in on AI agents, the company is combining its products to “invest in a single agentic platform and to merge ChatGPT and Codex into one unified agentic experience for all.”

To do this, the company is making a suite of org chart changes, although it’s still operating under some of the same ones from last month. That’s when AGI boss Fidji Simo went on medical leave and OpenAI announced that Brockman would be in charge of product strategy and CSO Jason Kwon, CFO Sarah Friar, and CRO Denise Dresser would take control of business operations.

It’s all part of OpenAI’s recent strategic shift to focus on key revenue drivers like coding and enterprise and stop pouring resources into “side quests” ahead of its potential IPO later this year and amid investor pressure to turn a profit.

In Simo’s continued absence, Brockman’s role leading product strategy is now official, as well as the company’s “scaling” arm. Under Brockman will be four different pillars. The first is core product and platform, led by Thibault Sottiaux, who has been OpenAI’s engineering lead for Codex, and the second is critical enterprise industries, led by ChatGPT head Nick Turley. Third is the consumer pillar, such as health, commerce, and personal finance, which will be led by Ashley Alexander, who has been its healthcare products VP. The fourth pillar — core infrastructure, ads, data science, and growth — will be led by Vijaye Raji, who has been OpenAI’s CTO of applications.

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Brockman wrote in the memo that OpenAI’s goal is now to “bring agents to ChatGPT scale, in order to give individuals and organizations significantly more value and utility from our products.”

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