Practical AI: Machine Learning, Data Science
Technology:Software How-To
While everyone is super hyped about generative AI, computer vision researchers have been working in the background on significant advancements in deep learning architectures. YOLOv9 was just released with some noteworthy advancements relevant to parameter efficient models. In this episode, Chris and Daniel dig into the details and also discuss advancements in parameter efficient LLMs, such as Microsofts 1-Bit LLMs and Qualcomm’s new AI Hub.
Leave us a comment
Changelog++ members save 3 minutes on this episode because they made the ads disappear. Join today!
Sponsors:
Featuring:
Show Notes:
YOLOv9:
Parameter efficient LLMs:
Something missing or broken? PRs welcome!
Generating "hunches" using smart home data 🏠
Mapping the world
Data science for intuitive user experiences
Going full bore with Graphcore!
Next-gen voice assistants
Women in Data Science (WiDS)
Recommender systems and high-frequency trading
Deep learning technology for drug discovery
Green AI 🌲
Low code, no code, accelerated code, & failing code
The AI doc will see you now
Cooking up synthetic data with Gretel
The nose knows
Accelerating ML innovation at MLCommons
The $1 trillion dollar ML model 💵
Getting in the Flow with Snorkel AI
Engaging with governments on AI for good
From research to product at Azure AI
The world's largest open library dataset
A casual conversation concerning causal inference
Create your
podcast in
minutes
It is Free
Podcast – Kitchen Sink WordPress
The Goat Farm
Away From The Keyboard
Arrested DevOps
Build Phase