Mojonized🔥

[Modular @Modular]

Mojo in Jupyter is here 🙌

@jeremyphoward released a new Jupyter kernel that lets you run Mojo directly in notebooks.

It works great on macOS, supports recent Linux versions, and is easy to install via pip or uv.

Give it a try and let us know what you build!
https://t.co/3AN1UooKCd

#MojoLang #OpenSource #DeveloperTools

[Will Manidis @WillManidis]

https://t.co/bDCdltFo0A

[Chieh-Hsin (Jesse) Lai @JCJesseLai]

Tired to go back to the original papers again and again? Our monograph: a systematic and fundamental recipe you can rely on!

📘 We’re excited to release 《The Principles of Diffusion Models》— with @DrYangSong, @gimdong58085414, @mittu1204, and @StefanoErmon.

It traces the core ideas that shaped diffusion modeling and explains how today’s models work, why they work, and where they’re heading.

🧵You’ll find the link and a few highlights in the thread.
We’d love to hear your thoughts and join some discussions!

⚡ Stay tuned for our markdown version, where you can drop your comments!

[Thinking Machines @thinkymachines]

Our latest post explores on-policy distillation, a training approach that unites the error-correcting relevance of RL with the reward density of SFT. When training it for math reasoning and as an internal chat assistant, we find that on-policy distillation can outperform other approaches for a fraction of the cost.

https://t.co/JhpyWQOpBe

[Sander Dieleman @sedielem]

In diffusion LMs, discrete methods have all but displaced continuous ones (🥲).

Interesting new trend: why not both? Use continuous methods to make discrete diffusion better.

Diffusion duality: https://t.co/KPO56vDygp
CADD: https://t.co/CNOIWcUIMo
CCDD: https://t.co/2jOBIcZvQZ

[Chris Lattner @clattner_llvm]

@aryanvs_ Have you given Mojo a try for this? It has a bunch of infra and existing basic support for neon matmuls - I bet you could make it significantly faster!

[Chris Lattner @clattner_llvm]

Jeremy builds on his years of AI and teaching experience, embracing AI coding by using it the right way: increase productivity and understanding of code, rather than replace programmers with "vibe code".
solveit is an innovative platform to learn and build apps. Check it out! 👇

[Chris Lattner @clattner_llvm]

Makes sense. Mojo gives you the full power of the hardware, it doesn't "abstract" it like some other systems, so it is perfect for doing this sort of work.
It provides helper libraries that you can optionally use to make some things (incl tiling etc) more declarative, and provides full AI models that you can run to benchmark your code under real workloads. You can basic NEON and VNNI implementations here:
https://t.co/Ymg6TK4AxM

The folks on https://t.co/Fc822uz6qr or discord would be happy to provide pointers too if you're interested!

[𝔈𝔥𝔰𝔞𝔫 @ehsanmok]

Let's gooooooo Modular 🚀🚀🚀🚀🚀🚀🚀🚀🚀🚀🚀🚀🚀🚀🚀🚀🚀

[Mojonized🔥 @mojonized]

@Modular congratulations 🙌🏼

[𝔈𝔥𝔰𝔞𝔫 @ehsanmok]

torch.compile is PT's achilles heel!

[Chris Lattner @clattner_llvm]

@jeremyphoward @ehsanmok You're a simple person who is so shy and doesn't know anything about these sorts of things :-)

[Jeremy Howard @jeremyphoward]

@clattner_llvm @ehsanmok It did occur to me that they're starting to understand why Mojo is actually needed...

[Chris Lattner @clattner_llvm]

@ehsanmok @jeremyphoward Did you tell Jeremy that Mojo runs on all the NV and AMD consumer GPUs and is starting to work on Apple GPUs too? :-)

[𝔈𝔥𝔰𝔞𝔫 @ehsanmok]

@jeremyphoward Mojo ftw https://t.co/nRhjXBYNOX

[Chris Lattner @clattner_llvm]

@tensorwave @AMD @Modular It was wonderful to spend the day with you in Austin today Kyle. Very excited about the collaboration and our path ahead 🦾!

[𝔈𝔥𝔰𝔞𝔫 @ehsanmok]

@_xjdr One more thing to be skeptical. Matter of time that dsl dies too. Mojo 🔥 ftw. Stay tuned for part 4 https://t.co/nRhjXBYNOX

[Chris Lattner @clattner_llvm]

@Modular @AMD Good day today @tensorwave!

[Modular @Modular]

ssshh... 🤫 @AMD Mi355X... now available in nightlies.

[Chris Lattner @clattner_llvm]

For more context, see https://t.co/vg71WP5uPQ
and https://t.co/jxtU91QGSQ