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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#

Project Suncatcher is our moonshot exploring whether we can one day host machine learning infrastructure in space 🚀 To do so, we need to know whether our AI hardware can operate in orbit. Can our TPUs handle the physical stress of spaceflight and the radiation and thermal extremes of space? These are the questions Google researchers have been exploring for the past few years. Last week, we launched our first test satellite carrying four TPUs into orbit — putting us one step closer to getting answers.

After many years in top machine learning organizations, with friends at frontier labs, I still consider Tesla’s ML engineers the best—the only ones I would trust with my life. Unsatisfied with theory, they scrutinize every detail until it is proven in reality. They demand real-world miles, not charts. This culture exists nowhere else. This week marks another anniversary at Tesla. I am honored to work with you all for many years to come.

Are you scared of losing your job? Reporting my latest story on Silicon Valley’s job struggles, two things stayed with me: the willingness to keep learning, and the importance of building a life beyond your job. Xingtao Zhao spent more than a decade at @Google . After leaving for a startup and later being laid off, he faced rejection even with a PhD in machine learning. He’s now applying his skills to quantitative trading while continuing to look for work. What struck me was his curiosity and optimism. He sees AI changing the opportunities around him—and keeps learning how to adapt. “It closes a window but opens a door,” he told me. Basem Istanbouli offered another kind of wisdom: build your community and your sense of self outside work, too. His (un)PTO group brings people between jobs together for hikes, coffee and companionship. We can be professionals, friends, parents, hikers, creators, volunteers, lifelong learners. Having several sources of meaning gives us somewhere to turn when one part of life becomes difficult. Losing a job can hurt financially and emotionally. Learning something new, finding people who understand, and remembering the other parts of ourselves can help us find a way forward. Thank you to everyone who shared their experiences with me. Your honesty—and your determination to keep going—deserve to be heard. My latest for @californiapost and @nypost 👇

Up, up, and away. 🚀 Today, in partnership with @planet, we launched a prototype satellite carrying four TPUs into orbit on @SpaceX's Transporter-18 rideshare mission. This launch is the first step of Project Suncatcher, our long-term research moonshot to see whether we can one day host scalable machine learning infrastructure in space. Over the coming weeks, we'll gather in-orbit data on how our TPUs handle the physical stress, radiation, and thermal extremes of space. Whatever we learn, we'll use it to refine our future designs.

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.