Conversations about science, technology, history, philosophy and the nature of intelligence, consciousness, love, and power. Lex is an AI researcher at MIT and beyond.
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Multimodal AI Models on Apple Silicon with MLX with Prince Canuma - #744
Manage episode 502573888 series 2355587
Content provided by TWIML and Sam Charrington. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by TWIML and Sam Charrington or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
Today, we're joined by Prince Canuma, an ML engineer and open-source developer focused on optimizing AI inference on Apple Silicon devices. Prince shares his journey to becoming one of the most prolific contributors to Apple’s MLX ecosystem, having published over 1,000 models and libraries that make open, multimodal AI accessible and performant on Apple devices. We explore his workflow for adapting new models in MLX, the trade-offs between the GPU and Neural Engine, and how optimization methods like pruning and quantization enhance performance. We also cover his work on "Fusion," a weight-space method for combining model behaviors without retraining, and his popular packages—MLX-Audio, MLX-Embeddings, and MLX-VLM—which streamline the use of MLX across different modalities. Finally, Prince introduces Marvis, a real-time speech-to-speech voice agent, and shares his vision for the future of AI, emphasizing the move towards "media models" that can handle multiple modalities, and more.
The complete show notes for this episode can be found at https://twimlai.com/go/744.
772 episodes
Multimodal AI Models on Apple Silicon with MLX with Prince Canuma - #744
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Share
Manage episode 502573888 series 2355587
Content provided by TWIML and Sam Charrington. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by TWIML and Sam Charrington or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
Today, we're joined by Prince Canuma, an ML engineer and open-source developer focused on optimizing AI inference on Apple Silicon devices. Prince shares his journey to becoming one of the most prolific contributors to Apple’s MLX ecosystem, having published over 1,000 models and libraries that make open, multimodal AI accessible and performant on Apple devices. We explore his workflow for adapting new models in MLX, the trade-offs between the GPU and Neural Engine, and how optimization methods like pruning and quantization enhance performance. We also cover his work on "Fusion," a weight-space method for combining model behaviors without retraining, and his popular packages—MLX-Audio, MLX-Embeddings, and MLX-VLM—which streamline the use of MLX across different modalities. Finally, Prince introduces Marvis, a real-time speech-to-speech voice agent, and shares his vision for the future of AI, emphasizing the move towards "media models" that can handle multiple modalities, and more.
The complete show notes for this episode can be found at https://twimlai.com/go/744.
772 episodes
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Similar to The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Conversations about science, technology, history, philosophy and the nature of intelligence, consciousness, love, and power. Lex is an AI researcher at MIT and beyond.
…
continue reading
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…
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TechStuff is getting a system update. Everything you love about Tech Stuff now twice the bandwidth with new hosts, Oz Woloshyn (Sleepwalkers) and Karah Preiss (Sleepwalkers). Oz and Karah bring humour and wit to the table as they break down what's happening in tech...and what it says about us. TechStuff is the podcast where technology meets culture. We speak to the folks building the future to understand what tomorrow will look like and how our technology is changing us: how we live, how we ...
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