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!
A developer's toolkit for SOTA AI
Cambrian explosion of generative models
Automated cartography using AI
From ML to AI to Generative AI
AI trends: a Latent Space crossover
Accidentally building SOTA AI
Controlled and compliant AI applications
Data augmentation with LlamaIndex
Creating instruction tuned models
The last mile of AI app development
Large models on CPUs
Causal inference
Capabilities of LLMs 🤯
Computer scientists as rogue art historians
Accelerated data science with a Kaggle grandmaster
Explainable AI that is accessible for all humans
AI search at You.com
End-to-end cloud compute for AI/ML
Success (and failure) in prompting
Applied NLP solutions & AI education
Create your
podcast in
minutes
It is Free
Podcast – Kitchen Sink WordPress
The Goat Farm
Away From The Keyboard
Arrested DevOps
Build Phase