The Man Who Calls BS On AI: They’re LYING About AI, 2027 Is When It All Breaks! | Ed Zitron | The Diary Of A CEO

The Gist

Generative AI is an unsustainable corporate con built on massive unprofitable data center spending, fake productivity metrics, and a looming market crash expected by 2027. Despite multi-trillion-dollar valuations and massive hype, AI companies are burning billions of dollars without clear paths to profitability.

Quick Overview

Generative AI is an unsustainable corporate con built on massive unprofitable data center spending, fake productivity metrics, and a looming market crash expected by 2027. Tech critic Ed Zitron exposes how OpenAI, Anthropic, and major tech giants are artificially inflating the AI boom through massive capital expenditures while hiding their actual burn rates and lack of true revenue.

Key Points: OpenAI lost $5.09 billion in 2024 after bringing in $3.7 billion in revenue against $12.48 billion in total expenses, with $5 billion spent strictly on model training. Up to 70 percent of AI revenue across major players comes from companies funding each other, such as Amazon investing $50 billion into OpenAI and Google and Microsoft pumping billions into Anthropic. Data centers built for AI require staggering amounts of energy, with projects like Stargate Abilene in Texas demanding 1.2 gigawatts of power, which is 1.5 times more energy than the entire city of Bristol. Model Evaluation and Research data shows that grounded hallucination rates on simple summarization tasks for top models like ChatGPT and Gemini hover between 0.7 percent and 7 percent, proving they are expensive text-prediction machines prone to error. Venture capital firms and private equity have poured hundreds of billions of dollars into AI infrastructure despite venture capital historically experiencing a low return of 0.81 to 1.21 on invested dollars since 2018. Unlike the internet or mobile technology which eventually found organic consumer demand, generative AI is experiencing forced enterprise spending subsidized by tech monopolies gaming algorithms and attention economies. The looming market crash for the AI bubble is projected for 2026 or 2027 as capital expenditures outpace returns and major tech companies are forced to restate financial realities.