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Some deals grab attention. Others reshape entire industries. But Nvidia’s reported $100B play with OpenAI?

Let’s just say… it does both — and more.

Here's what we have for you today

💰 Nvidia plans to invest up to $100B in OpenAI to Build Next-Gen AI Factories

Nvidia just put $100 billion on the table for OpenAI. 

Yep, billion with a B. — and this is one of the boldest bets we’ve seen in the entire AI race so far.

So what does that mean for us regular humans trying to make sense of all this? Well, this isn’t just about big numbers flying around Wall Street. This deal could completely reshape how AI is built, who controls it, and how fast it moves into our lives.

Let’s start with the headline: Nvidia isn’t simply cutting a check. The plan is about building 10 gigawatts of AI datacenters.

If that sounds abstract, picture this: 10 gigawatts is enough to power millions of homes. Instead, it’s being re-routed into building the next wave of AI models that will make ChatGPT look like a toy.

These aren’t data centers in the traditional sense — think of them as “AI factories.” Massive GPU clusters designed to train, deploy, and scale the next generation of artificial intelligence.

Now here’s where things get interesting: up until now, OpenAI was basically tethered to Microsoft. That relationship is still crucial, but Nvidia stepping in as a “preferred strategic compute partner”? That’s OpenAI spreading its wings — building independence, diversifying compute power, and making sure no single giant has them on a leash.

But let’s zoom out. Why Nvidia? 

Because in the AI world, GPUs are the real currency. Forget cash, forget clout — raw compute is the real flex. Training these giant models isn’t like running Fortnite on your gaming rig; it’s billions of parallel calculations running nonstop. And Nvidia? They’re basically the main dealer supplying the silicon crack AI labs can’t live without.

And don’t miss the chess move here. This deal not only guarantees OpenAI front-row access to the fastest chips, it also gives Nvidia insider knowledge of what tomorrow’s models will demand. That’s not just selling shovels in a gold rush — that’s owning the mine, the town, and the railroad.

So, what does $100 billion actually get us?

  • Faster training

  • Smarter models

  • Real-time AI that feels less like a chatbot and more like a coworker

But here’s the kicker: all of this comes with a monstrous energy bill. We’re talking billions of watts funneled into AI factories, which raises the uncomfortable question: can AI really keep scaling if it guzzles power like a small country?

Sustainability hasn’t exactly caught up with the hype.

Still, if this $100 billion bet goes through, it will undoubtedly turn the AI arms race into a sprint.

  • OpenAI gets more freedom and the firepower to scale faster.

  • Nvidia locks in its throne as the king of compute.

  • Microsoft? Well… let’s just say they suddenly have to share custody. 👀

If you’re as fascinated by this wild AI chess game as we are — click here to learn more.

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🤖 ChatGPT Prompt Of The Day: Post-Test Analysis & Insights

Yesterday, we shared a powerful prompt for analyzing A/B test results. But reading a prompt and seeing it work on real data are two very different things.

That’s why today, our Premium readers get to see it in action—with real data, real analysis, and real takeaways.

If you’re on free, you’ve got the prompt:

I’m [mention the problem you’re facing in detail with background context]. Act as a data analyst specializing in A/B testing. I will give you test results in this format: [insert sample data, e.g., impressions, clicks, conversions for A vs. B].

Your tasks are:

1. Analyze the results and determine whether the difference is statistically significant.
2. Explain which variation is better and why.
3. Highlight behavioral insights revealed by the data.
4. Provide 3 actionable recommendations for the next round of testing based on these insights.

Format the output as:

1. Quick Summary (plain-language takeaway)
2. Detailed Analysis (math/statistics + behavioral reasoning)
3. Actionable Recommendations (concrete next steps)

Keep the explanation clear, visual if possible (tables, percentages), and aligned with the goal of making smarter test decisions.

Upgrade now to see this whole month’s prompt videos and more, or buy TODAY’S WOD for just $1.99

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