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SaaStr 114: Redpoint's Tom Tunguz on The Rise of Machine Learning In Enterprise SaaS & How Existing SaaS Startups Can Incorporate ML Into Their Offering?

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Manage episode 177230114 series 126113
Content provided by SaaStr. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by SaaStr 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://player.fm/legal.

Tom Tunguz is a Partner at Redpoint Ventures and one of the pre-eminent thought leaders in the rise of SaaS. Tom has made investments in the likes of Demio, Axial, Chorus.ai and more incredible companies. Tomasz is also the co-author of Winning with Data: which explores the cultural changes big data brings to business, and shows you how to adapt your organization to leverage data to maximum effect. Before joining Redpoint, Tomasz was the product manager for Google’s AdSense social-media products and AdSense internationalization. If you have not checked out Tom’s blog that is a must and can be found here.

In Today’s Episode You Will Learn:

  • What are the 4 dominant ways startups are incorporating machine learning into their feature set? Why does Tom not believe in AI and discuss prefers to discuss machine learning?
  • What 3 things have caused the rise of machine learning? Why now will machine learning happen in core categories in SaaS? What role does deep learning play in this rise?
  • What are the 5 precepts of the type of companies that Tom wants to invest in using ML in SaaS? Why should startups discuss their value proposition over their technology?
  • How does Tom advise startups can gain access to proprietary datasets? How would Tom like to see data access change in the coming years?
  • How does Tom approach the aspect of building out a team of experts in machine learning for your startup? What should founders look for?

If you would like to find out more about the show and the guests presented, you can follow us on Twitter here:

Jason Lemkin

Harry Stebbings

SaaStr

Tomasz Tunguz

  continue reading

737 episodes

Artwork
iconShare
 
Manage episode 177230114 series 126113
Content provided by SaaStr. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by SaaStr 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://player.fm/legal.

Tom Tunguz is a Partner at Redpoint Ventures and one of the pre-eminent thought leaders in the rise of SaaS. Tom has made investments in the likes of Demio, Axial, Chorus.ai and more incredible companies. Tomasz is also the co-author of Winning with Data: which explores the cultural changes big data brings to business, and shows you how to adapt your organization to leverage data to maximum effect. Before joining Redpoint, Tomasz was the product manager for Google’s AdSense social-media products and AdSense internationalization. If you have not checked out Tom’s blog that is a must and can be found here.

In Today’s Episode You Will Learn:

  • What are the 4 dominant ways startups are incorporating machine learning into their feature set? Why does Tom not believe in AI and discuss prefers to discuss machine learning?
  • What 3 things have caused the rise of machine learning? Why now will machine learning happen in core categories in SaaS? What role does deep learning play in this rise?
  • What are the 5 precepts of the type of companies that Tom wants to invest in using ML in SaaS? Why should startups discuss their value proposition over their technology?
  • How does Tom advise startups can gain access to proprietary datasets? How would Tom like to see data access change in the coming years?
  • How does Tom approach the aspect of building out a team of experts in machine learning for your startup? What should founders look for?

If you would like to find out more about the show and the guests presented, you can follow us on Twitter here:

Jason Lemkin

Harry Stebbings

SaaStr

Tomasz Tunguz

  continue reading

737 episodes

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