Fleek

Something new coming soon

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@irnlx83 hoping to release the new product this month. but we don't want to misspeak. once we have better certainty on timelines we will start sharing more publicly

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please excuse the silence. we've been cooking up something cool and are excited to share more details soon

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@xcorat not for long! ⚡️

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https://t.co/c9BU1DIfRA

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NVIDIA just dropped benchmarks showing 4-bit inference loses less than 1 point vs BF16 on most tasks.

It's not accuracy per request that you should be measuring. It's tasks completed per dollar. And at that metric, 4-bit wins by a landslide.

Read the full blog 👇

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https://t.co/c9BU1DIfRA

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@OpheliaMystic There are several other components to the stack that will be open-sourced in the coming weeks / months.

Stay tuned, and keep an eye out on the repos 👀

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1/ Yesterday we announced mdspan-cute:

C++23 std::mdspan syntax with CUTLASS cute layouts.

One header. Zero overhead.

Here's how it works 🧵

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8/ Check out the code: https://t.co/lrSwYLsWDP

Check out the Proofs: https://t.co/t2MwTK3KAc

/end

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7/ Layout algebra is formalized in Lean 4. 26 theorems, 0 sorry.

Properties extracted to RapidCheck tests.

The art/ directory has 23 SVG visualizations - we drew pictures until we understood.

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Read the blog: https://t.co/PBWUEL8LZD

Check out the repo: https://t.co/DVdKOCWasq

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💿 Open Source Release 💿

mdspan-cute: a zero-overhead bridge between C++23 std::mdspan and CUTLASS cute layouts.

One header. Swizzled memory. No bank conflicts.

Read the blog and check out the repo (links in reply)

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@cv_alphas @grok If their broad definition stands, it has implications for other industries including drones, robotics, and more - not just the EVs they claim later in the patent it applies to

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@cv_alphas @grok "Derivative" would mean it's based on prior art.

rfl means it IS prior art.

Not derived. Identical.

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6/ On "bit augmentation":

Log/exp is a bijection. Information in = information out.
You can't create precision from a reversible transformation.

Thermodynamics doesn't allow it.

[Fleek @fleek]

5/ Quantized RoPE already runs in:

→ LLaMA → Mistral → Most open source inference stacks

This isn't obscure. It's foundational.