“Playthings” is by far the best Black Mirror episode I’ve watched. Thronglets ❤️
Yiğit Demirağ
@yigit.ai
Research Scientist at Google. PhD from ETH Zürich. Exotic AI architectures and silicon. 👾 Zürich, Switzerland
I appreciate @bsky.app once more when Elon starts blocking access to 100s of Twitter accounts engaged in expressing pro-democracy sentiments in Turkey.
Making LLMs run efficiently can feel scary, but scaling isn’t magic, it’s math! We wanted to demystify the “systems view” of LLMs and wrote a little textbook called “How To Scale Your Model” which we’re releasing today. 1/n
If you’re passionate about brain-inspired algorithms/hardware and novel neural computation beyond current TPU/GPU stack please apply to the CapoCaccia Workshops for Neuromorphic Intelligence. It values creativity, exploration and interdisciplinary collaboration🧪 capocaccia.cc/en/public/at...
Live ISS telemetry is interesting to watch. You can monitor critical sensors i.e, airlock or cabin pressures, or the urine tank percentage :)
Sedat Kapanoğlu@ssg.dev · 2y agoISS sensors in real time. iss-mimic.github.io/Mimic/
I didn't properly practice winter sports during my 5-year PhD in Switzerland. This morning, I'm on the SBB train to LAAX to learn snowboarding in 5 days.
1/ Okay, one thing that has been revealed to me from the replies to this is that many people don't know (or refuse to recognize) the following fact: The unts in ANN are actually not a terrible approximation of how real neurons work! A tiny 🧵. 🧠📈 #NeuroAI #MLSky
Blake Richards@tyrellturing.bsky.social · 2y agoWhy does anyone have any issue with this? I've seen people suggesting it's problematic, that neuroscientists won't like it, and so on. But, I literally don't see why this is problematic...
Nobel lecture in economic sciences from Daren Acemoglu is about to start
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Today is Gemini's 1st birthday 🎂, and the new experimental model, gemini-exp-1206 is #1 across the board in LMSYS Chatbot Arena.
ASML in Europe builds one of the most complex and precious engineering artifact, EUV lithography machines, and sit at the root of modern tech tree.
Computational lithography: Driving nanometer precision in microchip manufacturing | ASML
YouTube video by ASML
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Why does #compneuro need new learning methods? ANN models are usually trained with Gradient Descent (GD), which violates biological realities like Dale’s law and log-normal weights. Here we describe a superior learning algorithm for comp neuro: Exponentiated Gradients (EG)! 1/12 #neuroscience 🧪
Jonathan Cornford@repromancer.bsky.social · 2y agoBrain-like learning with exponentiated gradients www.biorxiv.org/content/10.1...
My morning routine now includes practicing latte art with my flat white at the Google MKs.
Google Research Zürich is a magical place quite like Hogwarts. Every wizard I meet works on powerful spells and potions.
Quite a candy for my optimization appetite :) As majority of inference are still on CPUs on mobile/edge accelerators, Mojo will be interesting to watch closely. I wonder how well it will support Triton or CUDA https://youtu.be/6GvB5lZJqcE
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I release a minimal (<150 lines) JAX implementation of "Gradients without Backpropagation" paper. It proposes a simple addition to forward AD to estimate unbiased gradients during single inference pass (quick project, might be further optimized) https://github.com/YigitDemirag/forward-gradients
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