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Massive Studios에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Massive Studios 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
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The Evolution of Data Platforms

38:22
 
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Manage episode 431558919 series 2285741
Massive Studios에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Massive Studios 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

Jeff Denworth, (@JeffDenworth, Co-Founder of @VAST_Data) talks about building data platforms for new AI application demands.
SHOW:
843
SHOW TRANSCRIPT: The Cloudcast #843 Transcript
SHOW VIDEO: https://youtube.com/@TheCloudcastNET
CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotw
NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST: "CLOUDCAST BASICS"
SHOW SPONSOR:


SHOW NOTES
:

Topic 1 - Welcome to the show. Before we jump into VAST Data, let’s talk a little bit about your background and then what led you to start the company.
Topic 2 - As we talk about datacenter or cloud architectures, right now GPUs are king. This is causing a complete rethinking of data center architectures. But what is this doing to the storage side of the equation?
Topic 3 - To a certain extent (in the context of AI), GPUs are this massive change from CPUs in that cost almost isn’t considered because of the great fear of falling behind in AI model building/usage. But storage has always been a performance+price discussion. Does that discussion still exist when companies must choose all-flash storage to keep up with GPU IO demands?
Topic 4 - We’ve obviously seen a lot of new innovation around GenAI models over the last couple years, but what have you seen from Enterprise companies in terms of real adoption, AI use-cases, etc?
Topic 5 - How are you finding Enterprise companies balancing the current requirements around infrastructure modernization (maybe driven by new VMware licensing, etc.) with AI demands?
Topic 6 - Do you find that data platform teams are having to make many adjustments to their environments or skills, especially since all-flash technology has been around for at least a decade?
FEEDBACK?

  continue reading

893 에피소드

Artwork

The Evolution of Data Platforms

The Cloudcast

1,285 subscribers

published

icon공유
 
Manage episode 431558919 series 2285741
Massive Studios에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Massive Studios 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

Jeff Denworth, (@JeffDenworth, Co-Founder of @VAST_Data) talks about building data platforms for new AI application demands.
SHOW:
843
SHOW TRANSCRIPT: The Cloudcast #843 Transcript
SHOW VIDEO: https://youtube.com/@TheCloudcastNET
CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotw
NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST: "CLOUDCAST BASICS"
SHOW SPONSOR:


SHOW NOTES
:

Topic 1 - Welcome to the show. Before we jump into VAST Data, let’s talk a little bit about your background and then what led you to start the company.
Topic 2 - As we talk about datacenter or cloud architectures, right now GPUs are king. This is causing a complete rethinking of data center architectures. But what is this doing to the storage side of the equation?
Topic 3 - To a certain extent (in the context of AI), GPUs are this massive change from CPUs in that cost almost isn’t considered because of the great fear of falling behind in AI model building/usage. But storage has always been a performance+price discussion. Does that discussion still exist when companies must choose all-flash storage to keep up with GPU IO demands?
Topic 4 - We’ve obviously seen a lot of new innovation around GenAI models over the last couple years, but what have you seen from Enterprise companies in terms of real adoption, AI use-cases, etc?
Topic 5 - How are you finding Enterprise companies balancing the current requirements around infrastructure modernization (maybe driven by new VMware licensing, etc.) with AI demands?
Topic 6 - Do you find that data platform teams are having to make many adjustments to their environments or skills, especially since all-flash technology has been around for at least a decade?
FEEDBACK?

  continue reading

893 에피소드

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