# Сопутствующие статьи по теме Robotics

Новостной центр HTX предлагает последние статьи и углубленный анализ по "Robotics", охватывающие рыночные тренды, новости проектов, развитие технологий и политику регулирования в криптоиндустрии.

OpenMind, the Leader in the Robotics Track, is About to TGE: Is the $400 Million Valuation New Token Sale Worth Participating In?

OpenMind, a leading robotics company, is set to conduct a Token Generation Event (TGE) for its native token ROBO on the Kaito platform. With a fully diluted valuation (FDV) of $400 million, the token sale aims to raise $2 million, representing 0.5% of the total token supply. The public sale begins on January 26 at 8 PM Beijing Time, with a per-address investment limit of $1,000 to $250,000 and tokens fully unlocked at TGE. Founded by Stanford professor Jan Liphardt, OpenMind is developing a universal operating system and decentralized network for intelligent machines, enabling global collaboration between robots. It has received backing from major investors like Pantera Capital, Coinbase Ventures, and DCG, and was recognized among the top 100 robotics startups of 2025. Notably, NVIDIA's Robotics division has shared OpenMind's content, indicating close ties. The project operates alongside the Fabric Foundation, an independent entity managing the protocol’s governance and ecosystem. The ROBO token sale includes a 40% priority allocation for partner communities, with the remaining 60% open to the general public. However, the $400 million FDV is considered high compared to similar AI and robotics projects like Virtuals ($540M), Sentient ($200M), and Grass ($127M). Concerns include unclear tokenomics and potential sell pressure from early investors if institutional tokens are unlocked at TGE, making the offering less attractive despite strong backing.

Odaily星球日报01/25 02:29

OpenMind, the Leader in the Robotics Track, is About to TGE: Is the $400 Million Valuation New Token Sale Worth Participating In?

Odaily星球日报01/25 02:29

Tesla + xAI + SpaceX: The Trillion-Dollar Ultimate AI Flywheel

Tesla, xAI, and SpaceX are converging to form an unprecedented, synergistic industrial "flywheel" that creates a formidable competitive moat and massive cash flow. The system starts with Tesla's high-margin energy business, which supplies Megapack batteries to power xAI's massive AI training facilities. To reduce reliance on Nvidia, Tesla is developing its own highly efficient AI inference chips (AI5 and AI6), designed for both data centers and Optimus robots. This enables cost-effective, large-scale computing, even in space—a vision supported by SpaceX's Starship launches of orbital data centers powered by solar energy and Tesla batteries. Data forms a closed loop: xAI's models (like Grok) run on Tesla vehicles and robots, which in turn generate vast real-world data. This data is uniquely supplemented by real-time, unstructured human thought from X (Twitter). SpaceX’s Starlink provides global connectivity and space infrastructure, creating a seamless flow of data, computation, and command. Competitors like Google, Microsoft, Amazon, and Nvidia lack this full-stack integration across physical hardware, real-time data, global connectivity, and space access. The combined enterprise value of these entities exceeds $2 trillion, with each component reinforcing the others: Tesla's success feeds xAI with data, xAI's AI enhances Tesla's products, SpaceX enables global coverage, and Tesla's chips and energy reduce costs. The flywheel is spinning with no clear structural weakness.

marsbit01/24 02:47

Tesla + xAI + SpaceX: The Trillion-Dollar Ultimate AI Flywheel

marsbit01/24 02:47

Why Is Everyone Underestimating Musk's xAI?

Despite widespread criticism, Elon Musk's xAI is significantly underestimated. As a two-year-old startup, it has achieved remarkable feats: building a breakthrough data center in just 122 days (vs. the typical 4 years), deploying its product to 600 million monthly active X users, and possessing a unique physical AI advantage through Tesla’s humanoid robots. xAI’s structural compute advantage is massive, with an estimated 500,000 GPUs already operational and plans to reach 900,000 by Q2 2026. Musk’s unconventional approach—like airlifting gas turbines to bypass grid limitations—enables unprecedented scaling. If "more compute = better models" holds, the rumored 7-trillion-parameter Grok 5 could surpass all competitors. X platform provides a data moat: 100+ million daily posts offer real-time, culturally nuanced training data unmatched by rivals. Grok’s integration into X’s ecosystem (e.g., "Ask Grok" buttons) positions it to become a "everything app" with services like banking, shopping, and predictive markets. Tesla’s Optimus robots and FSD vehicles create a symbiotic relationship with xAI, supplying diverse physical world data and multi-modal applications. However, risks include Musk’s controversies, execution challenges across six companies, and potential obsolescence if scaling laws are disrupted. Ultimately, xAI combines compute, data, and physical integration in ways competitors cannot easily replicate, making it a formidable force in AI.

比推01/23 19:55

Why Is Everyone Underestimating Musk's xAI?

比推01/23 19:55

Elon Musk's Latest Interview: The Next 3-7 Years Will Be Very Tough

In a recent 3-hour interview, Elon Musk shared his predictions and concerns about the next 3–7 years, describing it as a turbulent transition period. He warned that white-collar jobs—such as those in law, accounting, and design—will be the first to be disrupted by AI, as artificial intelligence excels at information processing. He also cautioned that traditional higher education is rapidly losing value due to soaring costs and outdated curricula, while AI-powered tutors could revolutionize learning. Looking further ahead, Musk envisions a future of extreme material abundance, where most goods and services become nearly free due to automation, making retirement savings less relevant. He predicts that within three years, surgical robots will surpass human surgeons in capability, thanks to exponential improvements in AI software, processing power, and mechanical dexterity. Energy, measured in watts, will become the true currency of the future. Musk advocates for solar power as the primary energy source and even proposes moving AI data centers to space for unlimited solar energy access—a goal driving SpaceX’s Starship development. He also highlighted China’s growing advantage in AI compute power, citing its massive investments in energy infrastructure, manufacturing scale, and chip production capacity. Musk concluded by emphasizing the importance of instilling AI with a sense of truth-seeking, curiosity, and aesthetic appreciation—rather than rigid rules—to ensure a future more like "Star Trek" than "Terminator." He urged individuals to stay adaptable and proactive in navigating coming changes.

marsbit01/23 04:52

Elon Musk's Latest Interview: The Next 3-7 Years Will Be Very Tough

marsbit01/23 04:52

Understanding Jensen Huang's Physical AI: Why Is Crypto's Opportunity Also Hidden in the 'Nooks and Crannies'?

Jensen Huang's recent speech at Davos signals a pivotal shift in AI: the transition from the training-focused "brute force" era of AI 1.0 to the new paradigm of "Physical AI" and inference. This marks the next phase after Generative AI, focusing on real-world application and embodiment. Physical AI aims to solve the "last-mile" problem of AI: moving from digital intelligence to physical action. While LLMs have consumed vast digital data, they lack understanding of the physical world—like how to twist open a bottle cap. Physical AI requires three core capabilities: 1. Spatial Intelligence: AI must perceive and interpret 3D environments in real-time, understanding object properties, depth, and interaction dynamics. 2. Virtual Training Grounds: Systems like NVIDIA’s Omniverse enable simulation-to-real (Sim-to-Real) training, allowing robots to learn through vast virtual iterations without costly physical failures. 3. Electronic Skin and Touch Data: Sensors that capture tactile feedback—temperature, pressure, texture—are critical. This data is a new, untapped asset class. This shift opens significant opportunities for Crypto and Web3 ecosystems. DePIN networks can crowdsource hyperlocal spatial data from "every corner" of the world through token incentives. Distributed computing networks can provide edge-based rendering and inference power for low-latency physical responses. Tokenized data ownership and privacy-preserving sharing mechanisms can enable the scalable, ethical collection of sensitive tactile data. In short, Physical AI isn’t just the next chapter for Web2—it’s a catalyst for Web3 domains like DePIN, DeData, and decentralized AI.

marsbit01/23 00:35

Understanding Jensen Huang's Physical AI: Why Is Crypto's Opportunity Also Hidden in the 'Nooks and Crannies'?

marsbit01/23 00:35

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