@svpino Unfortunately is the upgradeability in a sad state. Because when you upgrade a Framework laptops components after two years it will be as performant as a today's MacBook. Making it upgradability a money drain.
The search queries that @perplexity_ai performs and the the results it gets are a serious bottleneck (@MrBeast )
This is the opposite of grounding as the LLM's are
1. Gaslit into thinking the query aligned with the request
2. Forced to consolidate the results or ignore them
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.
Hey @perplexity_ai why is half the screen empty and the settings part of the chat obscured by the not closeable ad? What's even better clicking the ad by accident deletes what you've been writing thus far 😐
I asked Claude for a plan and generated a 16 page word.docx - impressive. But very much overkill for what I expected to get.
Would be nice to get asked, before Claude starts writing code for 3min to generate a word doc.
@AnthropicAI
I collaborated with @wabi and @joonasvirtanen to bring this incredible intro sequence to life, and I’d love to share it with you!
We wanted way more flexibility than Liquid Glass, so I made a custom glass shader that refracts + disperses light.
More technical details soon :)