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.
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Show Notes:
YOLOv9:
Parameter efficient LLMs:
Something missing or broken? PRs welcome!
The mathematics of machine learning
Balancing human intelligence with AI
From notebooks to Netflix scale with Metaflow
Trends in data labeling
Stellar inference speed via AutoNAS
Anaconda + Pyston and more
Exploring a new AI lexicon
NLP to help pregnant mothers in Kenya
SLICED - will you make the (data science) cut?
AI is creating never before heard sounds! 🎵
Building a data team
Towards stability and robustness
From symbols to AI pair programmers 💻
Vector databases for machine learning
Multi-GPU training is hard (without PyTorch Lightning)
Learning to learn deep learning 📖
The fastest way to build ML-powered apps
Elixir meets machine learning
Apache TVM and OctoML
25 years of speech technology innovation
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