AI & ML interests

AI, ML, LLM, NLP

magnisale's activity

jjokahย 
posted an update 6 days ago
view post
Post
2296
# Video Tokenization โ€” for efficient AI video processing

Meet ๐•๐ข๐๐“๐จ๐ค, a new open-source video tokenization technique developed by Microsoft Research to address the computational challenges of processing large volumes of video data. The core problem VidTok tackles is the inefficiency caused by redundant information in raw video pixels.

VidTok converts complex video footage into compact, structured units called tokens, making it easier and more efficient for AI systems to analyze, understand, and generate video content.

Research Paper: https://arxiv.org/abs/2412.13061
VidTok Code: https://github.com/microsoft/VidTok
jjokahย 
posted an update about 2 months ago
view post
Post
4640
The past few years have been a blast for artificial intelligence, with large language models (LLMs) stunning everyone with their capabilities and powering everything from chatbots to code assistants. However, not all applications demand the massive size and complexity of LLMs, the computational power required makes them impractical for many use cases. This is why Small Language Models (SLMs) entered the scene to make powerful AI models more accessible by shrinking in size.

In this article we went through what SLMs are, how they are made small, their benefits and limitations, real-world use cases, and how they can be used on mobile and desktop devices.
https://huggingface.co/blog/jjokah/small-language-model
  • 2 replies
ยท
jjokahย 
posted an update 5 months ago
view post
Post
793
Google's revamped Machine Learning Crash Course covers the recent advances in AI, with an increased focus on interactive learning.

๐Ÿ“ 100+ exercises
๐Ÿ—‚ 12 modules
๐Ÿ•’ 15 hours
๐Ÿ“น Video explainers of ML concepts
๐ŸŒŽ Real-world examples
๐Ÿ“Š Interactive visualizations

Ref:
https://developers.google.com/machine-learning/crash-course
jjokahย 
posted an update 8 months ago
view post
Post
1872
๐Ÿ”— Neural Network โ€€(1 Byte explainer for everybody)

Just like our brain, a Neural Network is made up of interconnected "neurons". These neurons work together by learning from (input) data and getting better at tasks (in the hidden layer) to give (output) predictions or decisions.