mikejulietbravo

came to say this, there's almost zero history for this so unless their supply chain got meaningfully distorted I can't see why this would happen now

text editors 5ever

as benchmarked on AA

The short answer is that it depends how well you define the boundaries of the task and the relative complexity. For example, smaller model is usually fine for something like summarization, but an "easier" coding task might still actually be quite difficult unless you eval it heavily like @paulhoule said

how many mentions of silicon valley?

seems like more than invested in other inference players

nuances like idioms can and will be solved. wispr flow is already solving a lot of these things via their speech-to-text interface.

as better models are introduced, figurative language, implication, cultural nuancec etc. becomes easier to reconcile.

does the plugin architecture come with added overhead (assuming you add a lot of elements)?

was just glad this wasn't about twitter :)

Awesome - we'd love to have our CEO/CTO chat with you and your team if you're interested. Shoot me a note at mike.bilodeau @ baseten.co and I'll make it happen!

Mike from Baseten here

We're super proud to support this work. If you're thinking of running deepseek in production, give us a shout!

The start of this reads like the beginning of a cult manifesto, but then transitions to a very logical solution for an important problem.

Baffling. I'm in

What's the tl;dr on a difference from this to SD?