Fit. Successful. Well-rested.
Pick two. The moment you chase all three, one quietly collapses. Sustainable growth isn’t about having it all — it’s about choosing which corner you’re willing to sacrifice, on purpose.
“Why should Norway trust India when fundamental rights are being violated?”
A nation that has sustained democratic plurality across 1.4 billion people, hundreds of languages, and 5,000 years of civilisational memory doesn’t lack a framework for fundamental rights. It invented one.
Learn that. Respect that. Trust that.
@HelleLyngSvends@Aftenposten
Productivity with machines (read AI) isn’t “do more with less effort & time.”
It’s “do more with the same — or even more.”
That’s what AI actually delivers: explosive output while humans maintain or increase effort.
Not replacement. Multiplication.
Elon just endorsed it.
Gad Saad dropped the hammer on Fox this morning.
We now live in a world where:
- Rape victims get less sympathy than their rapists
- Homeowners get less than the squatters breaking in
- American vets get less than illegal migrants
- Repeat felons with 186 charges get 200 more “chances” because “society made them do it”
This isn’t kindness.
This is suicidal empathy.
Universities spent decades teaching our judges, leaders, and elites that personal agency is a myth if you check the right oppression boxes. So criminals become victims, victims become bigots for complaining, and the whole system rots from the inside.
Turkish proverb says -
"If a father bathes his children, both will laugh, and if a son bathes his father, both will cry."
Honor the duty while you have the chance. Time spares no one.
Introducing SubQ - a major breakthrough in LLM intelligence.
It is the first model built on a fully sub-quadratic sparse-attention architecture (SSA),
And the first frontier model with a 12 million token context window which is:
- 52x faster than FlashAttention at 1MM tokens
- Less than 5% the cost of Opus
Transformer-based LLMs waste compute by processing every possible relationship between words (standard attention).
Only a small fraction actually matter.
@subquadratic finds and focuses only on the ones that do.
That's nearly 1,000x less compute and a new way for LLMs to scale.