与「Humanoids」相关的搜索结果

1 billion humanoids. That’s how many could be in use globally within the next quarter-century. We’re mapping the companies bringing robots from the lab to your living room in The Robot Almanac.

My top 5 robotics companies to start a career at, based on 412 open jobs i read: 1. @Figure_robot most open roles of anyone, 101. humanoid robot operators on morning, afternoon and night shifts. 63 of 101 jobs don't mention a degree 2. @1x_tech 3 to 6 month AI Residency at $10K a month. your code ships to NEO robots in real homes. every single job post shows the pay 3. @physical_int robot operator at $25/hr, no degree listed. you teleoperate the arms that train their robot brain 4. @agilityrobotics "Robot Operator II": $102K to $133K. associate degree or equivalent certs, basic Python and Linux 5. @SkildAI robot operator jobs in Pittsburgh and India. you don't have to live in San Francisco to get in the door into humanoids isn't the research team. it's one of these 5

NEW: Stord’s $3B Bet on Robotics, AI & Physical Infrastructure From Thiel Fellow at 19 to building a $1B+ revenue business Founder & CEO Sean Henry (@seanhenry) @GetSTORD stats: › 100M packages/year › ~$20B in GMV › $1B+ revenue this year, after 10Xing in 4 years › 8B operational data points The goal is to level the playing field with Amazon Prime for the other 2/3 of commerce on the internet. I sat down with Sean in Cap Ferrat to talk about the company's $250M Series F, its massive bet on robotics & AI, plus why he believes the biggest value from this technology may ultimately accrue to physical businesses, not the AI and robotics companies themselves. We get into: › The data advantage behind 100M packages a year › Why humanoids may be the wrong form factor for warehouses › How acquisitions & vertical integration are accelerating Stord's scale › Going from Thiel Fellow at 19 to building a $1B+ revenue business Sean also explains the flywheel behind Stord: more volume creates greater density, lower costs and faster delivery, which in turn makes the company more competitive as it scales. 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Sean Henry, Founder & CEO at Stord (00:41) What Stord is building in logistics (02:42) Why robotics is finally ready for the real world (04:37) How Stord is teaching robots to work (06:09) Do humanoid robots actually make sense? (07:20) Why owning the whole supply chain matters (10:01) The problem that started Stord (11:53) The Thiel Fellowship lesson: Build a monopoly (13:10) Hot take: Why AI and robotics will become commodities

Feeling the AGI/ASI, few observations 1. Opus 5.5 really gives strong vibes of AGI (maybe not fully there, but we're very close, like 80%-90%). For example, few breakthoughs in training humanoids are needed. We need to move this intelligence into physical world. 2. I don't think Anthropic has discovered any magical formula. 3. Which means, SpaceXAI, Google, and others will soon follow. This prediction is based on the amount of compute they already have + additional compute being added all the time. 4. Never was more confident that Anthropic, SpaceXAI, Google, OpenAI, likely Meta, basically all big US AGI labs will have proper AGI in 2027. 5. And from there we'll move quickly to ASI territory (likely also in 2027). It looks like few GW of compute are enough for strong AGI, now imagine what we will able to do with 10-20GW of compute which are rapidly coming online. And then with 100GW-200GW... 2027 will be an utterly insane year.

What would the best humanoid robot we can build in 2026 actually look like? Scott Walter (@GoingBallistic5), broke it down from the ground up. 00:00 The Philosophy of Robot Design 02:51 Understanding Bot Ecosystems 05:59 Choosing the Right Bot for the Task 08:59 Identifying Market Opportunities 11:45 Designing a Sprinting Bot 15:05 The Importance of Arm Movement in Running 18:12 Degrees of Freedom in Robot Design 21:10 Weight and Mass Distribution Challenges 23:56 The Role of the Head and Waist in Humanoids 27:03 The Mechanics of Running Bots 38:48 The Evolution of Humanoid Hip Designs 44:39 The Importance of Knee Actuators in Robotics 51:46 Challenges of Specialization in Humanoid Robotics 1:10:32 Choosing Between Off-the-Shelf and Custom Actuators 1:15:30 Leveraging Global Resources for Humanoid Development 1:16:20 The Open Source Robotics Movement 1:21:51 Navigating the Humanoid Market Landscape 1:22:31 The Future of Humanoid Robotics 1:30:10 Actuation Strategies and Challenges 1:39:17 The Role of AI in Humanoid Robotics 1:45:03 The Hardware Landscape and Future Prospects

This is the most important chart to understand right now as an AI investor There are 3 waves of token consumption. Each wave is bigger than the last, and we're only just starting wave 2 Wave 1: Chat Wave 2: Agents Wave 3: Physical AI (humanoids, robotaxis) Token usage is expected to multiply 24 TIMES by 2030, with enterprise agents alone burning ~120 quadrillion tokens/month The growth in chat is limited from here, but that's ok because wave 2 has already kicked off and its accelerating extremely fast right now Wave 2 is Agents that work continuously instead of answering one prompt at a time, enterprises deploy them by the thousand, and consumer agents (the new Siri, Gemini on Android) haven't even shipped at scale yet. That's the 24x, and it's why compute, memory and power demand keeps accelerating through 2030 But wave 3 is the real kicker and it crushes everything else. This is the part that isn't in many of the models today. Physical AI: Humanoids, robotaxis, autonomous machines. Expected to be the biggest consumer by 2030 and reach 400 quadrillion tokens a month by 2040, the biggest of every category on the chart And here's why wave 3 is different for infra investors: it pays the infra stack TWICE. Every robot runs inference around the clock (tokens), and every robot IS hardware itself too. A humanoid carries roughly 10x the memory of an advanced car, plus the sensors, chips and power systems. Wave 3 demand shows up in tokens AND in physical components As I've said many times before, the demand for compute and AI infra is infinite becuase the demand for intelligence is infinite. As the form factors we use intelligence continue to grow, the demand does too The sooner you understand this, the sooner it becomes easier to learn how to invest in it. or to make it even easier, you can track my real-time portfolio and 4 other analysts' with live trade notifications and research inside Milk Road PRO. It's just $1 to try it out right now, learn more here: If you enjoyed this, give me a follow @kylereidhead for more insights on AI and markets

I feel like AI investing is simpler than what people expect. Because $NVDA + Jensen literally tells everyone what's coming. But somehow. Almost every. single. time. Markets dismiss it until it actually happens? Be Nvidia in 2025: Buys up EML and laser capacity. Markets dismissing it: "Photonics is a bubble and like quantum! ____ company is a scam with shady management" 1 year later: $LITE +678%, $AAOI +475.12%, $COHR +260.7%, $AXTI +3,843.9%. _ Nvidia in 2026: Buys up CW/EML capacity with LTAs. 800V shift. Extraordinary explicit about CPO shift. States Physical AI as the next theme. Markets now: "CW players are meme stocks! 800v, CPO is not coming anytime soon, Humanoids are not profitable!" Yeah... We'll see what happens in 2027. I think I'm putting my money on Jensen/Nvidia as the leading indicator.

A humanoid robot is fundamentally an embodied AI system. While motors, actuators, batteries, and sensors provide the body, neural intelligence provides the mind. Without neural computation, a humanoid is simply an advanced machine. With it, the robot becomes capable of adapting to unpredictable environments, understanding language, recognizing objects, planning tasks, and continuously improving through experience. This shift positions "Humanoid Neural" as a foundational concept within the robotics ecosystem. Neural Intelligence is the Core of Future Humanoids. Modern humanoids rely on neural-network-based systems to perform nearly every cognitive function. These include: Visual perception Speech recognition Language understanding Object identification Human pose estimation Motion planning Reinforcement learning Dexterous manipulation Long-term memory Decision making Navigation Emotional recognition Social interaction As robots become more capable, nearly every subsystem transitions from traditional programming toward learned neural models. This makes "neural" less of a niche AI term and more of an umbrella for robot intelligence. A Broad and Scalable Brand One of the strongest characteristics of is that it is not confined to a single product category. #Languageunderstanding# #neuralnetwork# #socialinteraction# #neuralntelligence# #smarthumanoids# #iq#

While many of the world's brightest engineers were focused on building the best humanoid robots possible, PITN focused on building something different—a multilingual digital asset gateway designed for the emerging humanoid robotics ecosystem. Every transformational technology has had a moment when the market underestimated its importance. The internet.
Smartphones.
Artificial intelligence. Humanoid robotics may be approaching that same moment. PITN has assembled a portfolio of 500+ robotics and AI digital assets spanning the world's top 30 languages, including exact-match digital assets. Here's the question: When will a major robotics company have its "aha" moment and realize that a gateway they can leverage already exists? In any specialized industry, connections tend to tighten as the ecosystem matures. When humanoid robotics evolves into the global industry many expect, the paths between innovators, brands, and digital identity may become increasingly interconnected. The future is multilingual. The future is voice activated. 
The future is .HUMANOIDS WEB3. The future is POWER IN THE NUMBERS! For investor relations inquiries, DM #engineer# #TechCulture# #HumanoidRobotics# #AI# #Robotics# #DigitalAssets# #FutureTech# #Innovation#