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Call zone media. You know what time it is. It's your better offline monologue for the week and I'm Ed Zitron. Better offline now. Today's monologue is an attempt to bring you further into my work, which I've kind of already been doing, with multiple listeners materially contributing to the reporting behind this show. So many of you are eager to help, and if you want to help, well, reach out to me with information and do so on signal. Ezitron76 that's ezit R O N or E Z I T R O n if you're Canadian or British. 76 on Signal also, before I go any further, I've had a lot of emails and reddits and the such. If you're wondering about my thoughts on the OpenAI Disney deal, they are as follows. Wow. Disney invested a billion dollars in OpenAI. That's about a month's worth of inference. The Sony delays the inevitable. No one cares. They're threatening Google with legal action. Google will settle and they'll do exactly the same crap with veo. Nothing will happen. A bunch of money will get lost. Similarly, if you've heard about time naming AI executives as its Person of the Year, remember that Marc Benioff of Salesforce, a huge AI booster, owns the publication, literally ran advertorial for Salesforce's agent Force Wank. It's nothing. Nothing's happening. It's just more money being passed around so it can all get blown on nothing. But back to the rest of the monologue. I'm going to tell you about the things I need to do a better job. Not don't literally mean the research. I mean, if you know this stuff, I need your help. Let's start with a big one. If you have firsthand knowledge of GPUs being warehoused, this is Nvidia AI GPUs, please. God, if you reach out with this about gaming GPUs, I'll be genuinely pissed off at you. But I need to know about this. I want pictures if you can get them. I want numbers and I want to know whose GPUs they are and ideally what models. A1 hundreds, H1 hundreds. Probably not going to be that. It's going to be those Blackwell GPUs if you see them. Similarly, if you've heard anything about Nvidia's AI GPUs that might not be well known, reach out. Especially if it pertains to how much they cost to run. Similarly, if you know anything about Nvidia's Blackwell GPUs that you suspect I don't, please do reach out. I had somebody recently tell me about remote remarkable failure rates and I want to know more. Similarly, costs. I cannot ask for costs enough. Help me, please. If you have any information pertaining to the revenues behind OpenAI, Anthropic or any major AI company, please get in touch. Similarly, I want to hear from you if you work at any of the large cloud companies and know anything about the AI revenues or indeed the associated costs of running AI on Google Cloud, Amazon Web Services and Microsoft Azure. And yeah, if you have anything from OpenAI or anthropic about what they might be paying for Azure, Google Cloud or Amazon Web Services, please, please, please reach out to me. Similarly, if you have anything of the same from Core, Weave or Lambda or Nebius or any of those, please reach out. Also, if you work at an AI startup, one that pays OpenAI or Anthropic to use their services or models, please tell me about those costs. We don't know very much about them at all. And your thoughts and your help? Well, it'd be very much respected and loved and you'll be the better offline legend of the week if you can help me out here, maybe even the legend of the year. I'm also looking at any and all information related to data center costs. I want to know the total cost of ownership of any AI GPU, and that includes the A100, the H100, H200, B100, B200, B300 and so on Blackwell, obviously my biggest priority. I want to know how many GPUs hyperscalers have too. So if you work at Amazon, Microsoft or Google, and you know how many of the goddamn GPUs they've got, please reach out. And I want to know the hourly cost of running these GPUs, ideally on a per GPU basis. I'm trying to work out how much it actually costs to run these goddamn things, and it's insane. We don't know. Now, my grail data the things that would materially change my reporting, other than everything I just mentioned, would be the underlying cost of running large language models, which means understanding Both how many GPUs are used to for inference and training and the actual costs of running said GPUs. The costs of running GPUs are at the center of the bubble and I believe that truth will be what bursts in, though I'm repeating myself a little. My other grail data is the underlying cost of running ChatGPT, Google, Gemini, or any other major popular LLM service such as Cursor or Replim. The same goes for Microsoft, Meta, Amazon, Google, Oracle, or really any other major cloud provider. Look, together I believe we can make the world better by providing the public with the truth. And this era is one steeped in outright lies and societal selfishness that deprives good companies of funding and shoves dysfunctional software on millions of people that just wish it would go the fuck away. Now, so many of you have already been so helpful and I hope I can I can hear from more of you as the show continues to grow. It's been a crazy year. I'm insanely grateful to have all of you. And next week we have a three part Nvidia podcast that tells you all about the largest. We're just. We're just. I'm not fixing it. I'm not fixing that. You want the raw stuff. Anyway, Nvidia is the weirdest company in stock market history. Oh God. I'm gonna hear from you all about that one. I really do love hearing from you though. It's been really crazy. 2025 has been crazy and bad and good in many different ways. And I'm sure I'm gonna hear fun stories from you all because a bunch of you reach out no matter what I say to reach out about or not reach out about. And I kind of love it. I love how chatty you all are. So yeah, look forward to hearing from you and I hope you enjoy the podcast about the weirdest company on the stock market.
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Is an iheart podcast. Guaranteed human.
Host: Ed Zitron
Release Date: December 12, 2025
Podcast Network: Cool Zone Media & iHeartPodcasts
In this week’s monologue, host Ed Zitron opens the doors to his investigative process, directly recruiting listeners to help unravel the opaque economic realities at the heart of the AI and tech industry—especially around the costs, revenues, and inner dealings that big tech companies work hard to obscure. Ed discusses the challenges of tracing actual operational costs in AI development, points out contradictions in public narratives, and rattles off a list of data points and sources he’s seeking for future exposés. It’s a candid call to action—the community-powered reporting machine at work.
Ed lays out a set of very specific information requests, inviting insiders and whistleblowers to share details that would “materially change” the show’s reporting:
Ed Zitron’s monologue is direct, irreverent, and transparently collaborative—blending biting skepticism with humor and open-mindedness. He invites listeners to become insiders and partners, not just passive consumers. Cursing, dry sarcasm, and self-awareness keep the edge sharp but relatable.
This Better Offline monologue pulls back the curtain on the process of holding Big Tech accountable. Ed’s crowdsourced approach energizes listeners as critical stakeholders, not merely spectators, in the ongoing wrestle for tech transparency. Taking shots at vapid industry PR and making specific, aspiration-filled requests for hard data, Ed establishes himself as both watchdog and ringleader, teeing up a future exposé on Nvidia with characteristic wit—and a genuine appreciation for his passionate, information-wielding audience.