The Cloudcast

Scott Jarnagin, Founder and CEO of Caddis Cloud Solutions, dives into the evolving landscape of data centers in response to the AI boom. He discusses how current infrastructures must transform to meet rising power and cooling demands. Scott elaborates on the vital strategic decisions enterprises face while planning their AI needs, highlighting the importance of choosing the right data center. He also touches on the involvement of nuclear energy in data center expansion and the implications of government regulations. A must-listen for tech enthusiasts!

Explore five pivotal storylines poised to shape the cloud and AI landscape in late 2024. The discussion delves into how venture capital dynamics may shift, alongside the rising tide of tech antitrust debates linked to US elections. Insights on the financial health of major cloud players reveal AI's impact on their earnings. Plus, the potential for new contenders to challenge established virtualization giants like VMware is brought to light. Get ready for a fascinating look at technology’s evolving role in our economy!

Brian Gracely, a cloud and AI commentator; Aaron Delp, a cloud industry analyst; and Brandon Whichard, a tech news expert, dive into July 2024's cloud and AI happenings. They discuss the chaotic impact of CrowdStrike's outage and legal troubles with Delta Airlines, as well as challenges in chip manufacturing with Intel. The trio also explores the optimism in emerging tech job opportunities, AI's genuine impact versus hype, and strategies for navigating current political and professional uncertainties.

Silicon Valley is shaking off its apolitical image as venture capitalists become increasingly vocal in politics. This shift comes in the wake of growing tech influence on social issues, with social media playing a crucial role in elections. The rise of cryptocurrencies adds another layer to the discussion on regulation. The podcast delves into how billionaires wield power akin to nation states, raising questions about responsibility and accountability amid their political engagements. Antitrust concerns and future tech developments further complicate this evolving narrative.

Jeff Denworth, Co-Founder of VAST Data, discusses the dynamic landscape of data platforms shaped by AI demands. He highlights the impact of GPUs on data center architectures, raising questions about storage performance and price in an AI-driven world. Denworth explores the real-world adoption of AI in enterprises and the modernization of infrastructure to meet these demands. He also emphasizes the transition to all-flash storage systems, addressing the evolving skills needed in data management amidst these technological shifts.

Recent global outages highlight a worrying trend: the basics of high availability are slipping through the cracks. As network engineering faces decline, essential skills are undermined by a rush towards new technologies. The discussion reveals that foundational knowledge is overlooked, raising concerns for future tech reliability. It makes a strong case for the need to revive basic training to balance innovation with stability. Prepare for a thought-provoking exploration of why remembering the fundamentals is more crucial than ever.

Scott Stephenson, CEO of Deepgram, discusses the evolution and business applications of Voice AI, exploring its value in applications and common use cases. He also delves into the process of adding Voice AI to existing applications and collecting user feedback for voice-centric interactions.

The podcast discusses the importance of modern platforms for application development, addressing hurdles like standardization, costs, organizational alignment, and balancing innovation with stability. It explores Cisco's Cloud Application Security Solution and emphasizes the need for developers to focus on application development over infrastructure.

In this podcast, they discuss the evolution of cloud and AI in 2024, Amazon's advancements in GenAI, potential winners and losers in the AI industry, impact of layoffs on IT organizations, and speculation on the future of GenAI. They also touch on the challenges of implementing DevOps and the competition in large language models among tech giants.

Discussing the market for AI in Private Cloud, concerns about data mixing with public clouds, and measuring success in GenAI projects. Exploring the challenges of integrating private cloud AI in enterprises and addressing accuracy and biases of AI models.