33 min
Edo Liberty: How Vector Data Is Changing The Way We Recommend Everything HumAIn Podcast - Artificial Intelligence, Data Science, Developer Tools, and Technical Education
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Edo Liberty: How Vector Data Is Changing The Way We Recommend Everything
[Audio]
Podcast: Play in new window | Download
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Edo Liberty is the CEO of Pinecone, a company hiring exceptional scientists and engineers to solve some of the hardest and most impactful machine learning challenges of our times. Edo also worked at Amazon Web Services where he managed the algorithms group at Amazon AI.
As Senior Manager of Research, Amazon SageMaker, Edo and his team built scalable machine learning systems and algorithms used both internally and externally by customers of SageMaker, AWS's flagship machine learning platform.
Edo served as Senior Research Director at Yahoo where he was the head of Yahoo's Independent Research in New York with focus on scalable machine learning and data mining for Yahoo critical applications.
Edo is a Post Doctoral Research fellow in Applied Mathematics from Yale University. His research focused on randomized algorithms for data mining. In particular: dimensionality reduction, numerical linear algebra, and clustering. He is also interested in the concentration of measure phenomenon.
Please support this podcast by checking out our sponsors:
Episode Links:
Edo Liberty LinkedIn: https://www.linkedin.com/in/edo-liberty-4380164/
Edo Liberty Twitter: https://twitter.com/pinecone
Edo Liberty Website: https://www.pinecone.io
Podcast Details:
Podcast website: https://www.humainpodcast.com
Apple Podcasts: https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009
Spotify: https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpS
RSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9
YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag
YouTube Clips: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videos
Support and Social Media:
– Check out the sponsors above, it’s the best way to support this podcast
– Support on Patreon: https://www.patreon.com/humain/creators
– Twitter: https://twitter.com/dyakobovitch
– Instagram: https://www.instagram.com/humainpodcast/
– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/
– Facebook: https://www.facebook.com/HumainPodcast/
– HumAIn Website Articles: https://www.humainpodcast.com/blog/
Outline:
Here’s the timestamps for the episode:
(06:02)- It's funny how being a scientist and building applications and building platforms are so different. It's kind of like for me it's just by analogy, I mean, kind of a scientist, if you're looking at some achievement, like technical achievement as being a top of a mountain and a scientist is trying to like hike, they're trying to be the first person to the summit.
(06:28)- When you build an application, you kind of have to build a road, you have to be able to drive them with a car. And when you're building a platform on AWS or at Pinecone, you have to like build a city there. You have to really like, completely like to cover it. For me, the experience of building platforms and AWS was transformational because the way we think about problems is completely different. It's not about proving that something is possible, it is building the mechanisms that make it possible always for, in any circumstance.
(13:43)- And so on and today with machine learning, you don't really have to do any of that. You have pre-trained NLP models that convert a string, like a, take a sentence in English to an embedding, to a high dimensional vector, such that the similarity or either the distance or the angle between them is analogous to the similarity between them in terms of like conceptual smelts semantic similarity.
(18:17)- Almost always Pinecone ends up being a lot easier, a lot faster and a lot more production ready than what they would build in house. A lot more functional. We've spent two and a half years now baking a lot of re
Edo Liberty: How Vector Data Is Changing The Way We Recommend Everything
[Audio]
Podcast: Play in new window | Download
Subscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSS
Edo Liberty is the CEO of Pinecone, a company hiring exceptional scientists and engineers to solve some of the hardest and most impactful machine learning challenges of our times. Edo also worked at Amazon Web Services where he managed the algorithms group at Amazon AI.
As Senior Manager of Research, Amazon SageMaker, Edo and his team built scalable machine learning systems and algorithms used both internally and externally by customers of SageMaker, AWS's flagship machine learning platform.
Edo served as Senior Research Director at Yahoo where he was the head of Yahoo's Independent Research in New York with focus on scalable machine learning and data mining for Yahoo critical applications.
Edo is a Post Doctoral Research fellow in Applied Mathematics from Yale University. His research focused on randomized algorithms for data mining. In particular: dimensionality reduction, numerical linear algebra, and clustering. He is also interested in the concentration of measure phenomenon.
Please support this podcast by checking out our sponsors:
Episode Links:
Edo Liberty LinkedIn: https://www.linkedin.com/in/edo-liberty-4380164/
Edo Liberty Twitter: https://twitter.com/pinecone
Edo Liberty Website: https://www.pinecone.io
Podcast Details:
Podcast website: https://www.humainpodcast.com
Apple Podcasts: https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009
Spotify: https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpS
RSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9
YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag
YouTube Clips: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videos
Support and Social Media:
– Check out the sponsors above, it’s the best way to support this podcast
– Support on Patreon: https://www.patreon.com/humain/creators
– Twitter: https://twitter.com/dyakobovitch
– Instagram: https://www.instagram.com/humainpodcast/
– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/
– Facebook: https://www.facebook.com/HumainPodcast/
– HumAIn Website Articles: https://www.humainpodcast.com/blog/
Outline:
Here’s the timestamps for the episode:
(06:02)- It's funny how being a scientist and building applications and building platforms are so different. It's kind of like for me it's just by analogy, I mean, kind of a scientist, if you're looking at some achievement, like technical achievement as being a top of a mountain and a scientist is trying to like hike, they're trying to be the first person to the summit.
(06:28)- When you build an application, you kind of have to build a road, you have to be able to drive them with a car. And when you're building a platform on AWS or at Pinecone, you have to like build a city there. You have to really like, completely like to cover it. For me, the experience of building platforms and AWS was transformational because the way we think about problems is completely different. It's not about proving that something is possible, it is building the mechanisms that make it possible always for, in any circumstance.
(13:43)- And so on and today with machine learning, you don't really have to do any of that. You have pre-trained NLP models that convert a string, like a, take a sentence in English to an embedding, to a high dimensional vector, such that the similarity or either the distance or the angle between them is analogous to the similarity between them in terms of like conceptual smelts semantic similarity.
(18:17)- Almost always Pinecone ends up being a lot easier, a lot faster and a lot more production ready than what they would build in house. A lot more functional. We've spent two and a half years now baking a lot of re
33 min