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2024 wrapped I was a bit new to ML, didn't do much...but I did do some stuff. Hoping to do cooler ML research(and with big GPUs) in 2025 :) Major(part-completed) stuff/experiments I did this year(mostly from July):
last presentable Jax thing I did was making a checkpointing library for Flax(nnx API) models. still needs more testing and improvement. I created it cus I wanted to make something simpler than the rest github.com/kelechi-c/nnx_…
having a real job really interferes with my ability to tweet 20 times a day
excited to share that I have joined @audiogenai (as a research intern) to build the next generation of audio/music generation models 🚀. It's been extremely cool working with the team so far 🫡
I have EXCITING news: I've started a company! Introducing Sophont We’re building open multimodal foundation models for the future of healthcare. We need a DeepSeek for medical AI, and @SophontAI will be that company! Check out our website & blog post for more info (link…
companies just wanna make money, so all you need to do is show them how you can help them make money drop everything you have ever been told about getting a job and start over from that simple statement
o3-mini(tiny) Then it can be distilled to phone-level
for our next open source project, would it be more useful to do an o3-mini level model that is pretty small but still needs to run on GPUs, or the best phone-sized model we can do?
128108 vote · Final results
The pharmacy course is a side project. Tbh if I had a choice I would leave it😅
This one isn't for the weak...@tensor_kelechi is doing both pharmaceutical studies and ML research 😭😂
Cool. Now someone should make arxiv reels.
Training our most capable Gemini models relies heavily on our JAX software stack + Google's TPU hardware platforms. If you want to learn more, see this awesome book "How to Scale Your Model": jax-ml.github.io/scaling-book/ It was put together by my @GoogleDeepMind colleagues…
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
Many people leaving everything and grind RL because it’s the trend. Others going all in on CUDA. Same people who will start grinding flow matching when someone releases a video gen model. Choose something you like and do it consistently. Grass is greener where you water it.
2 years ago diffusion lora training was literally side project I did in the final exam week because i was too lazy to study for the exam ...and now its industry of its own 🤷
burning out is real btw. when i was 18 i thought it was something for dummies who didn't wanna work. it took me ~3 years to recover fully, and could physically not work for 5months after it happened
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