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Data Center Buildouts for AI

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Manage episode 434147493 series 2285741
Contenu fourni par Massive Studios. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Massive Studios ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.

Scott Jarnagin (Founder/CEO of Caddis Cloud Solutions (Caddis Cloud Solutions)) talks about the challenges of building modern data centers to handle the growing demands of AI.
SHOW: 847
SHOW TRANSCRIPT: The Cloudcast #847 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 NOTES:

Topic 1 - Welcome to the show. Before we jump into Caddis Cloud, let’s talk a little bit about your background and then what led you to start the company.
Topic 2 - Let’s begin by looking at the bigger picture intersection of today’s data centers and the growing demand for AI capabilities. How much of a change will current data centers have to go through to be able to support AI at any sort of scale?
Topic 3 - How are cloud providers, hosting companies and enterprises evolving to meet the increased demands driven by AI and other high-intensity computing processes?
Topic 4 - How would you typically advise an enterprise to think about matching the AI needs to the current and future capabilities of the market? How do they make sure their AI plans aren’t going to get sidetracked with the wrong datacenter/cloud choice?
Topic 5 - Are there elements of government development/involvement for datacenter expansion that companies should be aware of as they make future plans around AI?
Topic 6 - How frameworks does Caddis Cloud typically use to help guide companies that are looking at near-term and long-term data center plans
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893 episodes

Artwork

Data Center Buildouts for AI

The Cloudcast

1,285 subscribers

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Manage episode 434147493 series 2285741
Contenu fourni par Massive Studios. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Massive Studios ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.

Scott Jarnagin (Founder/CEO of Caddis Cloud Solutions (Caddis Cloud Solutions)) talks about the challenges of building modern data centers to handle the growing demands of AI.
SHOW: 847
SHOW TRANSCRIPT: The Cloudcast #847 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 NOTES:

Topic 1 - Welcome to the show. Before we jump into Caddis Cloud, let’s talk a little bit about your background and then what led you to start the company.
Topic 2 - Let’s begin by looking at the bigger picture intersection of today’s data centers and the growing demand for AI capabilities. How much of a change will current data centers have to go through to be able to support AI at any sort of scale?
Topic 3 - How are cloud providers, hosting companies and enterprises evolving to meet the increased demands driven by AI and other high-intensity computing processes?
Topic 4 - How would you typically advise an enterprise to think about matching the AI needs to the current and future capabilities of the market? How do they make sure their AI plans aren’t going to get sidetracked with the wrong datacenter/cloud choice?
Topic 5 - Are there elements of government development/involvement for datacenter expansion that companies should be aware of as they make future plans around AI?
Topic 6 - How frameworks does Caddis Cloud typically use to help guide companies that are looking at near-term and long-term data center plans
FEEDBACK?

  continue reading

893 episodes

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