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Contenido proporcionado por Rudderstack. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Rudderstack o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.
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198: Building AI Search and Customer-Enabled Fine-Tuning with Jesse Clark of Marqo.ai

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Manage episode 429303569 series 3264623
Contenido proporcionado por Rudderstack. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Rudderstack o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.

Highlights from this week’s conversation include:

  • Jesse’s background and work in data (0:35)
  • E-commerce Application for Search (1:23)
  • Ph.D. in Physics Experience Then Working in Data (2:27)
  • Early Machine Learning Journey (4:35)
  • Machine Learning at Stitch Fix (7:28)
  • Machine Learning at Amazon (10:39)
  • Myths and Realities of AI (13:49)
  • Bolt-On AI vs. Native AI (17:26)
  • Overview of Marqo (19:46)
  • Product launch and fine-tuning models (23:02)
  • Importance of data quality (25:38)
  • The power of machine learning in search (32:02)
  • Future of domain-specific knowledge and product data (34:08)
  • Unstructured data and AI (37:19)
  • Technical aspects of Marqo's system (39:42)
  • Challenges of vector search (43:27)
  • Evolution of search technology (48:15)
  • Future of search interfaces (50:43)
  • Final thoughts and takeaways (51:53)

The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.

RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com.

  continue reading

394 episodios

Artwork
iconCompartir
 
Manage episode 429303569 series 3264623
Contenido proporcionado por Rudderstack. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Rudderstack o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.

Highlights from this week’s conversation include:

  • Jesse’s background and work in data (0:35)
  • E-commerce Application for Search (1:23)
  • Ph.D. in Physics Experience Then Working in Data (2:27)
  • Early Machine Learning Journey (4:35)
  • Machine Learning at Stitch Fix (7:28)
  • Machine Learning at Amazon (10:39)
  • Myths and Realities of AI (13:49)
  • Bolt-On AI vs. Native AI (17:26)
  • Overview of Marqo (19:46)
  • Product launch and fine-tuning models (23:02)
  • Importance of data quality (25:38)
  • The power of machine learning in search (32:02)
  • Future of domain-specific knowledge and product data (34:08)
  • Unstructured data and AI (37:19)
  • Technical aspects of Marqo's system (39:42)
  • Challenges of vector search (43:27)
  • Evolution of search technology (48:15)
  • Future of search interfaces (50:43)
  • Final thoughts and takeaways (51:53)

The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.

RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com.

  continue reading

394 episodios

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