VINAY (✱,✱)

680 posts

VINAY (✱,✱)

VINAY (✱,✱)

@vinayA2255

Contributor @axisrobotics

Katılım Haziran 2024
176 Takip Edilen76 Takipçiler
Vishnu
Vishnu@VishnuCrypx·
Huge congratulations to all the FITG winners 🔥👏 🥇 @Rayman — 20 points 🥈 @Toriola — 15 points 🥉 @Xpress — 10 points You really deserved it 👏 Your consistency, effort, participation were all clearly visible… and in the end it also yielded good results. Also a shoutout to everyone who participated 🙌 In competitions like this, it's not just about points, being active in the community, interactions, support - all of these are equally important. Full positive vibes all the way 🤝 Many more wins ahead. @axisrobotics @iamlogtun Onto the next one fam @NGA 🚀
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Vishnu@VishnuCrypx

Huge Congratulations to our Top 3 Winners! 👏 🥇 @Nagasai911 — 10 Points 🥈 @namexstevn — 10 Points 🥉 @sarega03— 10 Points Well deserved , Your effort and consistency truly outstanding Big thanks to everyone who participated and Make Great more points and surprises are coming Soon . Don’t miss the upcoming events More events Comming try To Participate And Get The points Join in, stay active, Make Active Community More competitions = More rewards = More winners 🏅 And Once again To Thanks Who Participated To All And Congrats To The Winner @axisrobotics Thanks to conduct The SmashCart Game @iamlogtun

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VINAY (✱,✱) retweetledi
VINAY (✱,✱)
VINAY (✱,✱)@vinayA2255·
Everyone talks about AI. But very few talk about the fuel behind it: DATA. LLMs learned from internet data. Robots learn from real-world interaction data. Every physical movement is training data for the next generation of AI. @axisrobotics @iamlogtun @plpiaoliang
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Just Lυмму
Just Lυмму@iamlummyjay·
while touching grass, let’s learn a little about AXIS everyone talks about AI robots like the hard part is the model. Is it really? the bottleneck is data. LLMs had the internet. physical AI has almost nothing. that’s the gap @axisrobotics is trying to solve @iamlogtun
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Vishnu
Vishnu@VishnuCrypx·
𝐖𝐡𝐲 𝐢𝐬 𝐃𝐚𝐭𝐚 𝐭𝐡𝐞 𝐁𝐚𝐜𝐤𝐛𝐨𝐧𝐞 𝐨𝐟 𝐑𝐨𝐛𝐨𝐭𝐢𝐜𝐬? --> Currently , we are talking about how Ai Can Fast Learning Everything Now a Days . Ex - : (LLM ) Large Language Model has Learning Billion web pages , Books ,videos , other Ralated Real world Interaction By Information Data Learn Via Internet. --> However, robots do not learn merely by "reading." For them to learn, they require doing. -> Physical interaction data is crucial for a robot: -> How much force to apply when lifting an object -> How to maintain balance while walking -> How to react if an object slips or breaks -> How to handle real-time environmental changes --> This constitutes the biggest difference between AI models and robots. --> Internet data teaches AI to understand language. But physical-world data teaches robots to understand the real world. --> Every movement a robot makes, every sensor reading, every camera frame and even its mistakes transform into learning data. --> In robotics, data is not merely information. It is the "experience" gained by a robot. --> In the future, the companies that will dominate the field of robotics won't be those with just better models- but rather those with superior real-world interaction data. @axisrobotics @iamlogtun
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Role Miracle Ayomide(✱,✱)
Role Miracle Ayomide(✱,✱)@themiraculous01·
Day 1 — Why Data is the Backbone of Robotics 🧵 Everyone talks about robot hardware. The arms. The sensors. The humanoid movement. But the real backbone of robotics is not hardware. It’s DATA. 🤖 @0xzagen @0xsexybanana @Abyomiii
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Role Miracle Ayomide(✱,✱)@themiraculous01

🤖 Shaping the future of Physical AI with @axisrobotics on @KaitoAI Studio Most AI talks about chatbots. Axis is building the real thing — Physical AI that moves, learns, and acts in the real world.

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𝗙ᴀᴠᴏᴜʀ
𝗙ᴀᴠᴏᴜʀ@favour7814·
Large Language Models scaled through internet data. Physical AI will scale through interaction data. This is one of the fundamental differences between digital intelligence and robotic intelligence. LLMs learn from text, images, and online information. Robots, however, must learn from experience within physical environments through movement, perception, manipulation, and continuous feedback. As a result, the primary challenge in robotics is not model capability alone, but the availability of scalable, high quality interaction data. Axis Robotics is addressing this challenge through a simulation first infrastructure designed to generate and expand robotic training data at scale. By combining: • simulation environments • human guided interaction • large scale data augmentation • sim to real validation Axis Robotics is building the foundation required for adaptable, real world robotic intelligence. The next phase of AI will not only process information it will interact with and understand the physical world. @axisrobotics
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CRYPTO TIGER
CRYPTO TIGER@Cryptottiger·
Data is the backbone of Axis Robotics because robots learn from data just like humans learn from experience. The more data a robot collects, the smarter and more accurate it becomes. Without data, a robot can only follow fixed instructions. For example, if a robot wants to learn how to pick up a cup. It needs to practice many times. The data records: • how the hand moved • the shape of the cup • how much force was used • mistakes made After learning from thousands of examples, the robot becomes better without breaking the cup. Same thing with self-driving cars. They learn daily from: • traffic signs • human movement • weather conditions • road mistakes That data helps AI make safer and smarter decisions. At @axisrobotics, the more people interact and contribute data, the more robots can learn new movements and adapt to real-world situations. Simple meaning: Data is like food for AI robots🔻 🔸Without food, humans become weak 🔸Without data, robots cannot improve or think smarter. @iamlogtun @plpiaoliang
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VINAY (✱,✱) retweetledi
VINAY (✱,✱)
VINAY (✱,✱)@vinayA2255·
What is @axisrobotics? Axis is building the future of Robotic General Intelligence (RGI) A decentralized ecosystem where robots learn, adapt, and interact with the real world using community-powered data. Not just AI. Real intelligence for real-world robotics. @plpiaoliang
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