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Throwback: The AI-Native Stack with Mikiko Bazeley, Zain Hasan, and Tuana Celik

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Manage episode 443179562 series 3604986
Content provided by DataStax and Charna Parkey. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by DataStax and Charna Parkey 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.

This episode features a panel discussion with Mikiko Bazeley, Head of MLOps at Featureform; Zain Hasan, Senior Developer Advocate at Weaviate; and Tuana Celik, Developer Advocate at deepset.

In this episode, Mikiko, Zain, and Tuana discuss what open source data means to them, how their companies fit into the AI-first ecosystem, and how jobs will need to evolve with the AI-native stack.

-------------------

“We're almost part of a fancy new AI robot kitchen that you'd find in Tokyo, in some ways. I see a virtual feature store as, yes, you can have a bunch of your ingredients tossed into a closet. Or, what you can do is you can essentially have a nice way to organize them. You can have a way to label them, to capture information.” – Mikiko Bazeley

“I really like that analogy as well. I like how Mikiko put it where a vector search engine is really extracting value from what you've already got. [...] So where I see vector search engines, really, is if we think of these embedding providers as the translators to take all of our unstructured data and bring it into vector space into a common machine language, vector search engines are essentially the workhorses that allow us to compute and search over these objects in vectorized format. They're essentially the calculators of the AI stack.” – Zain Hasan

“Haystack, I would really position as the kitchen. I need Mikiko to bring the apples. I need Zain to bring the pears. I need Hugging Face or OpenAI to bring the oranges to make a good fruit salad. But, Haystack will provide the spoons and the pans and the knives to make that into something that works together.” – Tuana Celik

-------------------

Episode Timestamps:

(02:58): What open source data means to the panelists

(09:11): What interested the panelists about AI/ML

(24:10): Mikiko explains Featureform

(27:00): Zain explains Weaviate

(30:23): Tuana explains deepset

(36:00): The panelists discuss how their companies fit into the AI-first ecosystem

(44:58): How jobs need to evolve with the AI-native stack

(54:35): Executive producer, Audra Montenegro's backstage takeaways

-------------------

Links:

LinkedIn - Connect with Mikiko

Visit Featureform

LinkedIn - Connect with Zain

Visit Weaviate

LinkedIn - Connect with Tuana

Visit deepset

Visit Data-centric AI

  continue reading

97 episodes

Artwork
iconShare
 
Manage episode 443179562 series 3604986
Content provided by DataStax and Charna Parkey. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by DataStax and Charna Parkey 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.

This episode features a panel discussion with Mikiko Bazeley, Head of MLOps at Featureform; Zain Hasan, Senior Developer Advocate at Weaviate; and Tuana Celik, Developer Advocate at deepset.

In this episode, Mikiko, Zain, and Tuana discuss what open source data means to them, how their companies fit into the AI-first ecosystem, and how jobs will need to evolve with the AI-native stack.

-------------------

“We're almost part of a fancy new AI robot kitchen that you'd find in Tokyo, in some ways. I see a virtual feature store as, yes, you can have a bunch of your ingredients tossed into a closet. Or, what you can do is you can essentially have a nice way to organize them. You can have a way to label them, to capture information.” – Mikiko Bazeley

“I really like that analogy as well. I like how Mikiko put it where a vector search engine is really extracting value from what you've already got. [...] So where I see vector search engines, really, is if we think of these embedding providers as the translators to take all of our unstructured data and bring it into vector space into a common machine language, vector search engines are essentially the workhorses that allow us to compute and search over these objects in vectorized format. They're essentially the calculators of the AI stack.” – Zain Hasan

“Haystack, I would really position as the kitchen. I need Mikiko to bring the apples. I need Zain to bring the pears. I need Hugging Face or OpenAI to bring the oranges to make a good fruit salad. But, Haystack will provide the spoons and the pans and the knives to make that into something that works together.” – Tuana Celik

-------------------

Episode Timestamps:

(02:58): What open source data means to the panelists

(09:11): What interested the panelists about AI/ML

(24:10): Mikiko explains Featureform

(27:00): Zain explains Weaviate

(30:23): Tuana explains deepset

(36:00): The panelists discuss how their companies fit into the AI-first ecosystem

(44:58): How jobs need to evolve with the AI-native stack

(54:35): Executive producer, Audra Montenegro's backstage takeaways

-------------------

Links:

LinkedIn - Connect with Mikiko

Visit Featureform

LinkedIn - Connect with Zain

Visit Weaviate

LinkedIn - Connect with Tuana

Visit deepset

Visit Data-centric AI

  continue reading

97 episodes

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