(How might image generators solve p;problems?
Elsewhere people used to read a lot, courses were gut or food for thought. Now social media is prevalent, so how is that used?
Robots are still unnerving.
In any case, Godel remains, and cybernetics. Where is the determinism? Can any element remotely know another without the direct prompt? Or would that have to become a function of long-term evolution. In which case, what are the competing or environmental factors?
Thiis may become interesting when robots like Optimus are sent on long-range missions such as Mars without humans around and occasionally on comms. How can that be tested more locally ahead of time? Other than by starving them of resources.
Who picks the missions? Scary version.
Perhaps a Tyrell origin story. Old Norse or French.
Who picks Tyrell?
What is the implicit goal?
Incidentally, early on, Minsky reportedly favored tele-presence. Others later looked at expert systems. Assuming they are not hallucinating, machines are also capable of augmented or mixed reality. How do they know the difference? How do people, in either sense? Other than biases.
Or Space Force interns go DOGE versus Delphi mode.
Backtracking through the plan, from results to analysis or methods, how do they pick better questions or problem sets?
Does self-reporting evidence subjectivity?
Are there Platonic or universal prompts or are they personalized or localized? Can those be made equivalent through a dictionary?
Is this another form of mimicry where the collaborating or training partner or source is then removed? Expecting Enlightenment. At least pattern affinity.
Why AI?)
Google Gemini summary: According to the video, the lesson learned from the talk is that planning and learning are complementary to each other and both are necessary for robots to achieve intelligence.
The speaker, Russ Tedrake, argues that while foundation models are powerful and will play an important role in the future of robotics, planning is still an important aspect that should not be ignored. He emphasizes that planning can improve the efficiency of learning by guiding the exploration process and focusing on the most promising actions.
The talk also introduces GCS (Graphs of Convex Sets) as a powerful tool for planning in robotics. GCS allows robots to reason about the uncertainties in their environment and make decisions that are robust to these uncertainties.
Here are the key points from the talk:
Planning and learning are complementary: Planning can improve the efficiency of learning by guiding the exploration process. GCS is a powerful tool for planning in robotics: GCS allows robots to reason about uncertainties in their environment. Behavior cloning is a useful tool for robotics: Behavior cloning can be used to learn from human demonstrations. Foundation models are powerful but not a silver bullet: Planning is still important in the age of foundation models.
"Useful in a variety of ways"
"The Sticky Notes are sturdy as advertised. Nice to convert any other surface into a Rocketbook. Use them in combination as a spread such as replicating a planner template. Since am using a Core and Flip alternately for that and journaling, stuck these inside the covers for weekly status at a glance. Also for daily priorities, although the Mini is also good. Basically will pick up any extra content like ideas or todos to be transferred somewhere or accomplished. Am trying to generalize categories for an overall agenda between this and digital notes so these are, like the cloud cards, good for experimentation. Save facts for quick reference."