Recently Chris and Daniel briefly discussed the Open RAIL-M licensing and model releases on Hugging Face. In this episode, Daniel follows up on this topic based on some recent practical experience. Also included is a discussion about graph neural networks, message passing, and tweaking synthesized voices!

The practicalities of releasing models

Making artificial intelligence practical, productive &amp; accessible to everyone.  Practical AI is a show in which technology professionals, business people, students, enthusiasts, and expert guests engage in lively discussions about Artificial Intelligence and related topics (Machine Learning, Deep Learning, Neural Networks, GANs, MLOps, AIOps, LLMs &amp; more). The focus is on productive implementations and real-world scenarios that are accessible to everyone. If you want to keep up with the latest advances in AI, while keeping one foot in the real world, then this is the show for you!

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Software How-To

First there was Mamba… now there is Jamba from AI21. This is a model that combines the best non-transformer goodness of Mamba with good ‘ol attention layers. This results in a highly performant and efficient model that AI21 has open sourced! We hear all about it (along with a variety of other LLM things) from AI21’s co-founder Yoav.

Mamba & Jamba

2024 promises to be the year of multi-modal AI, and we are already seeing some amazing things. In this “fully connected” episode, Chris and Daniel explore the new Udio product/service for generating music. Then they dig into the differences between recent multi-modal efforts and more “traditional” ways of combining data modalities.

Udio & the age of multi-modal AI

Daniel & Chris delight in conversation with “the funniest guy in AI”, Demetrios Brinkmann.  Together they explore the results of the MLOps Community’s latest survey. They also preview the upcoming AI Quality Conference.

RAG continues to rise

In this fully connected episode, Daniel & Chris discuss NVIDIA GTC keynote comments from CEO Jensen Huang about teaching kids to code.  Then they dive into the notion of “community” in the AI world, before discussing challenges in the adoption of generative AI by non-technical people.  They finish by addressing the evolving balance between generative AI interfaces and search engines.

Should kids still learn to code?

Daniel and Chris are out this week, so we’re bringing you conversations all about AI’s complicated relationship to software developers from other Changelog pods: JS Party, Go Time & The Changelog.

The practicalities of releasing models

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