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AI doesn’t “know” facts the way humans do. It predicts what should come next—and sometimes does it so convincingly that we forget to check. Fluent doesn’t always mean correct. 🤖 AI并不是像人一样“知道答案”，它更像是在预测接下来最可能出现的内容。 说得很像真的，也不一定就是真的。 #AI# #AIEducation# #LLM# #MachineLearning# #ChatGPT#

The future of humanoids isn't just mechanical—it's neural. A humanoid robot is an embodied AI system. Motors, sensors, and actuators provide the body, but neural intelligence provides the mind. Neural models power vision, speech, language, navigation, manipulation, planning, memory, decision-making, and continuous learning. As robotics evolves, nearly every cognitive subsystem is becoming neural-first. That's why represents more than a niche—it's a foundational concept for the next generation of intelligent robotics. #HumanoidRobots# #EmbodiedAI# #PhysicalAI# #NeuralNetworks# #ArtificialIntelligence# #Robotics# #MachineLearning# #DeepLearning# #RobotLearning# #ReinforcementLearning# #ComputerVision# #GenerativeAI# #AIResearch# #Automation# #FutureOfAI#

AI & ML Full Course 2026! #BigData# #Analytics# #AI# #MachineLearning# #DataScience# #IoT# #IIoT# #Python# #RStats# #TensorFlow# #JavaScript# #ReactJS# #CloudComputing# #Serverless# #DataScientist# #Linux# #Programming# #Coding# #100DaysofCode#

Thrilled to share that my single-author paper "Revisit Micro-batch Clipping: Adaptive Data Pruning via Gradient Manipulation" has been accepted at ICLR! While I love collaborating, it's incredibly rewarding to see a solo project through to publication. Onwards and upwards! 🚀 #ICLR2024# #MachineLearning# #research#

We partnered with @planet to send a prototype satellite carrying four TPUs into orbit. We’ll be looking to see how well the TPUs withstand the harsh conditions of space to assess whether we can eventually host machine learning in orbit.

We’re sending TPUs to space (yes, really). After years of research, we’re launching a satellite to evaluate if and how Google Tensor Processing Units (TPUs) hold up in orbit. The test mission, as part of our latest moonshot — Project Suncatcher — is designed to gather data exploring how we can one day host machine learning infrastructure in space.

Everything you need to master in 2026 to get rich: • Using Astra 6 high for planning, low for execution • Grok Bot to manage day to day • Coding loops • Taking advantage of Codex's computer use • Herdr to manage tons of agents • /goal • Running local models • Karpathy's Autoresearch • Building an X audience • Creating videos • How machine learning works • How databases work (been using Convex) • Using API's • Training your own LoRAs • Elimination of doom scrolling • Most importantly: focus

如果你想学习，想提升技能， 这 16 个频道最合适。且免费。 涵盖编程、AI、数据科学等。 1. SQL 👉 2. Excel 👉 3. Statistics 👉 4. Math 👉 5. Python 👉 6. Data Analysis 👉 7. Machine Learning 👉 8. Deep Learning 👉 9. Java 👉 10. Big Data 👉 11. Data Engineering 👉 12. NLP (自然语言处理) 👉 13. 计算机视觉与AI 👉 14. 生成式AI 👉 15. 大学级课程 👉 👉 16. 全能科技学习 👉

Announcing Discovery Loop! I am very excited to announce that, along with my longtime friends and collaborators @Sanjay_Ghemawat, @OriolVinyalsML and @quocleix, we are founding Discovery Loop (@DiscoLoopAI), a Public Benefit Corporation whose mission is to automate machine learning, science, and engineering to accelerate discoveries and progress. The four of us have worked together for 14 to 30 years, and have helped build some of the world’s most used products, infrastructure and AI models, and we’re excited to turn our attention to this ambitious endeavor. ♾ Learn more at:

All Paid Courses (Free for First 4500 People). 𝗣𝗮𝗶𝗱 𝗖𝗼𝘂𝗿𝘀𝗲 𝗙𝗥𝗘𝗘 (PART - 1) 1. Artificial Intelligence 2. Machine Learning 3. Prompt Engineering 4. Claude, ChatGPT, Grok 5. Data Analytics 6. AWS Certified 7. Data Science 8. BIG DATA 9. Python 10. Ethical Hacking (72 Hours only ) Like + RT + comment '' Drive '' Must Follow me so I can DM you.