made a more thorough version of this for people with longer attention spans.
37 questions instead of 10 and added likert scales for more psychometric reliability.
i like the original but it feels a bit flat imo
have fun
https://t.co/kFlBoV9Ivi
A new diagnostic quiz
10 questions for you to think about.
This is probably more fun for people who are relatively new to philosophy. Try it out and see!
I am having a lot of fun creating these tools, quizzes, and resources.
Enjoy!
https://t.co/XsoQ8IwmN5
in markets, to go long on something is to bet it grows more valuable over time. much of the conversation today is short on humans, wagering that ai makes people redundant. we believe the opposite is true for the industries @ThriveHoldings operates in.
we are long humans.
https://t.co/oqygDJKZGO
The most frightening person i ever witnessed was a man who only wanted one thing. everybody around him had a hundred plans, a hundred projects they were going to start next month, and he had one, just one. and he never talked about it much, and that was the part that unnerved you, because when someone talks a lot about what they want, you can relax. talking is letting the pressure out, so it's harmless. but he was airtight.
Everything in him was moving toward one point, in silence. within a few years he was in a place no one else could reach, and everybody who had watched him stood there scattered and confused, with their mouths full of plans that never solidified into anything. i learned from watching him that the mouth is a leak. every time you say what you are going to do, you lose a piece of the will that would have done it
music is the final frontier. in 10 years from now we will stare into the abyss and yell and the echo will throw us back to the sky to remind us what it feels to be human
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.