In case you missed it, Luca Trevisan's final talk was delivered today by @praveshkkothari and Salil Vadhan. Part 1 is on spectral graph theory, and part 2 is about his experiences as an outsider. Things start around 22:30. https://
youtube.com/live/FdP_n_x0a
1k?si=5BNaFKS9cFvjwzZo
…
MACHINE LEARNING
-
Luca Trevisan’s Final Talk on Spectral Graph Theory
By
–
-
llm.c Memory Efficiency Advantages Over PyTorch
By
–
If you match the parameters you're actually under-estimating the improvement, because llm.c takes up a lot less space so you can crank up the batch size. I haven't fully dug into why PyTorch takes up that much space, slightly worried I'm doing something wrong but not sure what
-
Apple’s GenAI Strategy: Small Models and LoRA Adapters at Scale
By
–
ICYMI: @Apple recently published their playbook for deploying #GenAI at scale across iOS devices. What's their secret? Small language models (#SLM) + lots of fine-tuned #LoRA adapters. Want to can replicate their approach? Check out our blog: https://
pbase.ai/3KXrIdO -
MLX Framework as Optimized Alternative to PyTorch MPS
By
–
I'd have a look at MLX, cc @awnihannun , from some recent chatter I understand it is a lot more optimized that PyTorch mps atm. This would need a re-write of the build-nanogpt code into mlx, but possibly it's not that involved. I'd be happy to accept a PR for mlx clone.
-
In-Context Learning as Testbed: Example Order and Label Effects
By
–
I quite like it as a nice/intuitive testbed of in-context learning, and the experiments around example order, label names, label flipping, etc., which give a sense of the strength of the prior, and ICL as an optimizer. Does the performance here also correlate with other LLM
-
Daily Content Sharing on Python Data Science and Machine Learning
By
–
That's a wrap! If you are interested in any of these below topics: – Python – Data Science – Machine Learning – Data Analysis – LLMs – MLOps Find me → @Sumanth_077 I'm sharing daily content over here.
-
Upload PDF Research Paper Data to Clarifai Vector Database
By
–
Step 3: Upload the data, Here we are uploading the pdf file of a research paper. Once you upload the data, it will embed and index the data into your Clarifai app. Clarifai Apps acts as your vector database.
-
Slimebot Volleyball: 3D Multi-Agent RL Environment on SlimeVolleyGym
By
–
Slimebot Volleyball is a 3D version of Neural Slime Volleyball. The game is implemented on top of SlimeVolleyGym. The major difference is the additional z-axis, and 2-vs-2 multi-agent play, which makes training more challenging for RL algorithms like PPO.https://t.co/cyL5l8DI8M pic.twitter.com/vITaGNu0Ph
— hardmaru (@hardmaru) 24 juin 2024Slimebot Volleyball is a 3D version of Neural Slime Volleyball. The game is implemented on top of SlimeVolleyGym. The major difference is the additional z-axis, and 2-vs-2 multi-agent play, which makes training more challenging for RL algorithms like PPO. https://
github.com/jbakams/slimeb
ot-volleyball
… -
Software 2.0: Machine Learning Approach to Software Development
By
–
What is Software 2.0? #Software 2.0 is a term used to describe a new approach to software #development that leverages machine learning (#ML) and artificial intelligence (#AI). It's a contrast to the traditional way of coding, which is referred to as Software 1.0. Here's a
-
Essential Data Science Books for Experts and Beginners
By
–
Best Data Science Books for Experts and Novices! #BigData #Analytics #DataScience #IoT #IIoT #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Books #Programming #Coding #100DaysofCode https://
geni.us/KSNMedia