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Thank you! Really great to be here, and great conversations throughout the event!

I'll start with "Julia meets the Intelligence Processing Unit" (pretalx.com/juliacon2023/t…), about running #JuliaLang on the Graphcore IPU, spectacular example of how llvm.org enables adopting new cool hardware in Julia, and how Julia opens up new doors in scientific computing

I’m biased obvs, but having seen a preview of this talk, I can recommend it highly!

I love that I'm being offered these - I guess the ad targeting knows I'm going to have a sudden urge to take up jewellery making long before I do...

So pleased to share that our OGB-LSC winning model GPS++ has just been published in TMLR.

Graphcore Research internships are now open 🎉 We're looking for PhD students for next summer We're interested in algorithms & tools for hardware-efficient ML, in areas like LLM training/inference, GNNs, knowledge graphs and frameworks Spread the word! graphcore.ai/jobs

Our latest edition of *Papers of the Month* is now available 📚 These are summaries of our team's favourite papers from March, including a new low-rank training procedure GaLore, and the supposed "Era of 1-bit LLMs" (really 1.58 bits) Mini-version in 🧵 graphcore-research.github.io/papers-of-the-…

Our team's summaries & analysis of our favourite papers from the last month. We give our take on: Mamba-2, sparse-µP, contextual position encoding & matmul-free models 🧵 graphcore-research.github.io/papers-of-the-…

babe wake up, new muP paper dropped arxiv.org/abs/2407.17465 And holy smokes does this look promising!

Our u-µP paper hit arXiv this morning! I'm so proud of this one — and grateful for a wonderful team who put so much into it 🥰 We add lots of good things to µP. Better sweeping, transfer, simple FP8. Already Simo Ryu has a great thread on it, which I highly recommend

Excited to present our work at ICML Conference WANT workshop: ⚖️ Scalify: scale propagation for efficient low-precision LLM training 🎉 github.com/graphcore-rese…

Introducing `tandv` - a library for tracking and visualising the internal stats of your model. We hope this will help with low-precision, debugging and more. (link in 🧵)

Our Papers of the Month for September is now live! We cover: - LLM self-correction via RL - Trillion-token FP8 training - SOAP (Shampoo + Adam) - Generative models for crystals All framed in terms of "proper conditioning" (🧵) graphcore-research.github.io/papers-of-the-…