Discover a whole new take on Artificial Intelligence with Squirro's educational podcast! Join host Lauren Hawker Zafer, a top voice in Artificial Intelligence on LinkedIn, for insightful chats that unravel the fascinating world of tech innovation, use case exploration and AI knowledge. Dive into candid discussions with accomplished industry experts and established academics. With each episode, you'll expand your grasp of cutting-edge technologies and their incredible impact on society, and y ...
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Evaluating and Building AI Systems - ML 166
MP3•Episod hem
Manage episode 441419301 series 2977446
Innehåll tillhandahållet av Charles M Wood. Allt poddinnehåll inklusive avsnitt, grafik och podcastbeskrivningar laddas upp och tillhandahålls direkt av Charles M Wood eller deras podcastplattformspartner. Om du tror att någon använder ditt upphovsrättsskyddade verk utan din tillåtelse kan du följa processen som beskrivs här https://sv.player.fm/legal.
Michael Berk dives deep into the adventures of AI and machine learning with our special guest, Richmond Alake, a staff developer advocate at MongoDB. Richmond's journey from web development to AI was driven by a quest for excitement and new challenges. In this episode, he shares how he transitioned into the AI field, his passion for using writing as a learning tool, and the importance of continuous learning in evolving tech landscapes.
They explore the intricacies of building and evaluating Retrieval-Augmented Generation (RAG) systems, the benefits of MongoDB's versatile database functionalities, and the pressing challenges in machine learning data collection and evaluation. Richmond also gives us a peek into MongoDB's advanced solutions for AI application development and how strategic data chunking can impact efficiency.
Whether you're a budding AI enthusiast or an experienced developer looking to expand your horizons, this episode is packed with practical advice, career insights, and the latest trends in AI and machine learning. Stay tuned as we uncover how to navigate the complexity of RAG pipelines and the evolving landscape of generative AI. Let's get started!
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Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
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continue reading
They explore the intricacies of building and evaluating Retrieval-Augmented Generation (RAG) systems, the benefits of MongoDB's versatile database functionalities, and the pressing challenges in machine learning data collection and evaluation. Richmond also gives us a peek into MongoDB's advanced solutions for AI application development and how strategic data chunking can impact efficiency.
Whether you're a budding AI enthusiast or an experienced developer looking to expand your horizons, this episode is packed with practical advice, career insights, and the latest trends in AI and machine learning. Stay tuned as we uncover how to navigate the complexity of RAG pipelines and the evolving landscape of generative AI. Let's get started!
Socials
Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
197 episoder
MP3•Episod hem
Manage episode 441419301 series 2977446
Innehåll tillhandahållet av Charles M Wood. Allt poddinnehåll inklusive avsnitt, grafik och podcastbeskrivningar laddas upp och tillhandahålls direkt av Charles M Wood eller deras podcastplattformspartner. Om du tror att någon använder ditt upphovsrättsskyddade verk utan din tillåtelse kan du följa processen som beskrivs här https://sv.player.fm/legal.
Michael Berk dives deep into the adventures of AI and machine learning with our special guest, Richmond Alake, a staff developer advocate at MongoDB. Richmond's journey from web development to AI was driven by a quest for excitement and new challenges. In this episode, he shares how he transitioned into the AI field, his passion for using writing as a learning tool, and the importance of continuous learning in evolving tech landscapes.
They explore the intricacies of building and evaluating Retrieval-Augmented Generation (RAG) systems, the benefits of MongoDB's versatile database functionalities, and the pressing challenges in machine learning data collection and evaluation. Richmond also gives us a peek into MongoDB's advanced solutions for AI application development and how strategic data chunking can impact efficiency.
Whether you're a budding AI enthusiast or an experienced developer looking to expand your horizons, this episode is packed with practical advice, career insights, and the latest trends in AI and machine learning. Stay tuned as we uncover how to navigate the complexity of RAG pipelines and the evolving landscape of generative AI. Let's get started!
Socials
Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
…
continue reading
They explore the intricacies of building and evaluating Retrieval-Augmented Generation (RAG) systems, the benefits of MongoDB's versatile database functionalities, and the pressing challenges in machine learning data collection and evaluation. Richmond also gives us a peek into MongoDB's advanced solutions for AI application development and how strategic data chunking can impact efficiency.
Whether you're a budding AI enthusiast or an experienced developer looking to expand your horizons, this episode is packed with practical advice, career insights, and the latest trends in AI and machine learning. Stay tuned as we uncover how to navigate the complexity of RAG pipelines and the evolving landscape of generative AI. Let's get started!
Socials
Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
197 episoder
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