Ranganaut
Thinkerer, Tinkerer
The Daily Planet #124: The Anatomical Compiler
Michael Levin is an interesting thinker; a rare Platonist in Biology. This quote from a recent post of his makes me think of biological engineering, but not the kind where we force organisms to do our willing, but rather work with their agential capacity to produce forms that we need:
The Daily Planet #121: Timefulness
I have been reading Marcia Bjornerud's "Timefulness" and really enjoying it. The more woke we are, the more we are prone to possessing our experience as somehow uniquely our own, like "this is my reality, and you have no right to doubt it." But that personal reality is embedded in a much larger planetary reality that doesn't care about our I-Me-Myself experiences that much. As Bjornerud says when she visited Svalbard as a graduate student:
The Daily Planet #119: On Deep Time
We barely remember what happened yesterday, so to expect us to take geological eras into consideration is a bit much. However, our lives are built on deep time - I wouldn't be writing these words if someone hadn't figured out how to turn solidified & liquified fossils into fuel.
The Daily Planet #118: On Contradiction
The term "contradiction" has many meanings. In logic it means claiming a proposition and its negation are both true at once. In conversation it means asserting the opposite of what someone else is saying. There's the Marxist version where contradictions reveal the underlying instability of the capitalist system.
The Weekly Planet #19: The China Shock, Part 3: AI.
When UBTech robots walked onto the factory floor at Zeekr's electric vehicle plant in March 2025, they did something no humanoid robots had done before: they worked as a coordinated team, lifting boxes, assembling car parts, and performing quality checks - all without human supervision. Powered by DeepSeek's reasoning model, these machines represented more than a manufacturing curiosity. They embodied a fundamentally different vision of artificial intelligence, one that may reshape the global technology competition in ways Silicon Valley hasn't fully grasped.
The Daily Planet #117: The China Shock, Part 18
And finally, any country that's rapidly becoming more technologically capable and dominant in some industries is going to get adverse attention. Are they trustworthy? Will they eat us alive? These are fair questions, and it's instructive to see how the official Chinese sources are responding to them. This is what they have to say:
The Daily Planet #115: The China Shock, Part 16
The race to develop humanoid robots is unfolding along two very different paths in China and the United States, reflecting contrasting philosophies about how robots should learn and improve. China is taking a bold, fast-paced approach by deploying large numbers of robots directly into real-world environments like factories, streets, and homes. This “learn-on-the-job” strategy allows robots to gather vast amounts of real-world data, which is then used to continuously improve their artificial intelligence. Companies such as Unitree and Agibot are leading this effort, with Agibot even offering an open-source operating system called Lingqu OS to encourage collaboration and innovation across the industry. By flooding the market with task-specific robots, China creates a massive, living laboratory that accelerates progress through collective learning and rapid iteration.
The Daily Planet #114: The China Shock, Part 15
Embodied intelligence refers to intelligent agents that have a physical or virtual body and interact with their environment through continuous sensing, decision-making, and action. Unlike traditional AI that processes static data, embodied intelligence emphasizes the dynamic loop where perception guides action, and action changes what is perceived. This interaction involves three key components: intelligence (the computational brain), embodiment (the physical or simulated body), and environment (the external world with its objects and dynamics).
The Daily Planet #113: The China Shock, Part 14
China is advancing its artificial intelligence (AI) efforts in a way that differs significantly from the United States. While the U.S. mainly focuses on developing large language models (LLMs) to achieve artificial general intelligence (AGI) - a future AI that can outperform humans in all cognitive tasks - China is taking a broader and more balanced approach. Instead of putting all its resources into one method, China is investing in multiple paths to AGI simultaneously.