Episode 167: Latest Sports Streaming Viewership Numbers; Oracle Layoffs; The Problem With AI Capex Spending episode artwork

EPISODE · Apr 5, 2026 · 40 MIN

Episode 167: Latest Sports Streaming Viewership Numbers; Oracle Layoffs; The Problem With AI Capex Spending

from The Dan Rayburn Podcast · host Dan Rayburn

This week, we detail viewership numbers from Netflix, NBC Sports and Peacock for MLB's opening week, highlighting the multiple issues with how the data is collected and presented, leading to impossible comparisons. We also discuss OpenAI's hiring of Indian streaming giant JioStar to lead its Asia-Pacific operations and news that Main Street Sports Group lenders have formally signed paperwork to close the business after the first round of the NHL playoffs.Finally, we discuss Oracle's recent round of layoffs and break down the balance sheet numbers that led to them, including $58 billion in new debt, net income, operating cash flow and $50 billion in capital expenditures expected during fiscal 2026. Dan argues that all this reckless spending on AI isn't innovation but rather financial engineering dressed up as leadership, with no accountability, no consequences and a lack of leaders who manage with discipline.Podcast produced by Security Halt Media

This week, we detail viewership numbers from Netflix, NBC Sports and Peacock for MLB's opening week, highlighting the multiple issues with how the data is collected and presented, leading to impossible comparisons. We also discuss OpenAI's hiring of Indian streaming giant JioStar to lead its Asia-Pacific operations and news that Main Street Sports Group lenders have formally signed paperwork to close the business after the first round of the NHL playoffs. Finally, we discuss Oracle's recent ...

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Episode 167: Latest Sports Streaming Viewership Numbers; Oracle Layoffs; The Problem With AI Capex Spending

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This episode was published on April 5, 2026.

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This week, we detail viewership numbers from Netflix, NBC Sports and Peacock for MLB's opening week, highlighting the multiple issues with how the data is collected and presented, leading to impossible comparisons. We also discuss OpenAI's hiring of...

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