If semantic voids are real, then they are not merely gaps in language.
They are measurable gaps in collective cognition.
Once a void is filled, people’s ability to reason changes.
Consider the word “meme.” Before it existed, the phenomenon still existed. After the word became widespread, people could analyze cultural replication much more easily.
Or consider “burnout.” The experience predated the label, but once it had a name, it became easier to recognize, discuss, and study.
The word didn’t create the phenomenon. It made it cognitively accessible.
@TorontoStar It’s not that Canadians aren’t ambitious. BlackBerry was the visible case. We had the company, the talent, and the early proof. Then the conditions required to keep scaling it were allowed to erode. Everything since has followed the same logic.
I actually respect what Palantir built: the vision, the tech that works, and how Alex Karp talks about it without the usual bullshit.
The problem isn’t the intentions. The problem is the structure. They’re building a single platform that pulls data from everywhere into one place and layers AI on top to automate decisions at scale. (From an AI safety perspective.) That means one system ends up with far more visibility and steering power over operations and choices than anyone else. Put that in private hands with founder-level control, and when you look at the companies they partner with, it stops feeling like a neutral tool.
They named it after the palantir on purpose.
What am I missing?
@elonmusk@SpaceX
On Starlink scaling: With 10k+ satellites and plans for 15k–30k+
maneuver rates are already high (50k avoidance burns in recent 6 months). How does propellant budget and cascaded avoidance complexity scale in denser shells?
Kepler syndrome risk is exponential.
You teach the system how you think so it can keep going when you’re not there to think it.
Right now most of what gets called institutional memory is still just documents the model pulls from. The actual gap is building something with real agency, something that holds how decisions get made and gets sharper on its own instead of needing people to keep feeding it the same patterns.
How do you close that without the loop learning to run without the people who started it? Ultimately replacing them.
@oprydai Do you think we’re in a hype cycle with robotics because of AI? AI allows for advancements, but the bottleneck is physics data. How do you see the labs getting around that?