A new “subfield” founded in 2019 is making waves, and is more accessible than I first thought

With the devolving world order, seeking positive, engaging work, I wanted to learn a) what actually is machine learning for climate change and b) are there reasonable paths for us to dive in and contribute? To quote the call for action in a paper I cite heavily later:

Groundbreaking technologies have an impact, but so do well-constructed solutions to mundane problems.

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Recent work

To start with, I knew there were a bunch of recent workshops on climate change and machine learning (such as ICLR 2020, ICML 2019, NeurIPs 2019 editions). …

How electrical engineers see the world: Models, Systems, Code; and Robots

The best teams for robotics are not all computer scientists — they have electrical & mechanical engineers, computer scientists, robots, and more to fill the cracks. This post is an exploration of how different ways of thinking contribute in robotics — and by extension to many software engineering projects.

How would you summarize the overarching conceptual theme of your undergraduate major?

This was originally posted on my free newsletter on robotics & automation, Democratizing Automation.

Seeing models

I don’t characterize EE primarily by circuit design nor nano-fabrication. It took me a long time to figure out what was different between my degree in electrical engineering (EE) and a similar computer science degree. So many of my classmates get software engineer (SWE) jobs regardless, are we really different? …

Re-thinking robot design: don’t restrict your robot worldview to robot (a) does task (b).

In this post, I address two questions:

  1. Is automation intelligence — is one a prerequisite for another?
  2. How do we train agents to act in ways that align with human goals — what limits are there on automation with the standard model.

I am intentionally avoiding a couple of hot topics in reinforcement learning that pertains to generalization/task transfer (such as meta-learning or other generalizable methods). I think that most generalization to date is proportional to data-distribution coverage of multiple tasks — not the ability for the same hyperparameters to solve numerically distinct tasks.

The good news: I think expanding our robot worldview can lead to robots that can generalize and help humans all the same. …


Nathan Lambert

Learner, non-pro athlete, yogi, and robot learning research @ UCBerkeley. Subscribe directly at democraticrobots.com. More at natolambert.me

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