AI Race: Meta's $15B Shock

$15B to control AI data? Here’s what it means for your marketing playbook.

Author

Rivet Media
June 11, 2025

Good morning. Today we have seven incredible prompts along with the latest AI insights and news.

Plus, you’ll discover how Meta’s $15B bet on AI data could reshape your content strategy and what to do now. Let’s get started!

  1. LinkedIn Connect

    This prompt helps you create personalized and engaging LinkedIn messages aimed at professionals, focusing on professionalism and connection. Simply add recipient details and company information for a compelling invitation that sparks conversations and opens doors to new opportunities.

  2. Linkedin Post Generator
    This prompt will help you create a captivating and attention-grabbing LinkedIn post that makes your content stand out. Elevate your LinkedIn presence effortlessly with this feature, which generates a hook, body content, and a question for your audience. Just provide a specific subject and details for the post, and watch the transformation happen.

  3. Linkedin Post (From YouTube video)

    With this prompt, you can transform a YouTube video into a compelling LinkedIn post that resonates with your target audience. Simply include the link to the video, and watch your network grow as your interactions increase.

Why Meta’s $15B AI Deal Should Scare (and Excite) You

Let’s not sugarcoat it: Meta just dropped $15 billion into Scale AI, and it’s not just about making smarter chatbots.

This is about owning the pipelines of training data—and that changes the game for anyone using AI to create, market, or communicate.

Meta isn’t buying compute power. They’re buying the upstream source: the human-annotated data that trains the LLMs you're using to write content, schedule posts, and run ads. And they’re getting it from Rivet—Scale AI’s education-focused arm that collects “high-quality data” by paying students to annotate AI outputs across STEM, law, healthcare, and more.

If you're a marketer, here’s why this matters: the quality of generative output is directly tied to the quality of training data. Meta is betting that future content performance, even ad relevance, will rely on human-vetted data—data they now have a lock on.

What To Do With This As a Content Pro First, stop treating all AI models as equal.

Meta’s model (LLaMA 3 and beyond) will now be trained on high-resolution, human-labeled datasets that others might not have access to. That means their tools might outperform others in accuracy, tone, and nuance—especially in specialized content like legal, financial, or healthcare.

Has Meta pulled ahead in the AI race?

Second, think like a strategist, not a tool user.

If you’re using ChatGPT, Claude, or Gemini, understand what kind of data those models were trained on. OpenAI hasn’t bought $15B worth of labeled educational data. Meta has. Expect future Meta tools to become surprisingly competent at deep content creation—and possibly better at aligning to brand tone and context.

Lastly, consider your own data.

Are you training custom GPTs or internal LLMs on generic web-scraped content? You’re playing a different game. If productivity is your north star, clean, labeled, domain-specific data will soon be your biggest asset—not just prompts.

TL;DR: The AI arms race isn’t about features. It’s about who owns the upstream data. Meta just pulled ahead. If you’re not thinking about data quality, you’re already behind.

Alexandr Wang, CEO of Scale AI will head Meta’s new ‘superintelligence’ lab.

Use This Before Meta Uses It Against You

If Meta is quietly cornering the market on elite training data, it’s only a matter of time before content generated through their stack (LLaMA models, Instagram AI features, ad targeting) starts outperforming everyone else’s.

But you don’t need to wait.

Here’s how to use this moment to level up your marketing output now—with smarter prompts and sharper content strategy.

1. Prompt for Tone Accuracy

Meta’s data play is all about human-verified tone, clarity, and context.

You can simulate that by forcing precision in your prompts:

Prompt:
“You are a senior copywriter for a fast-growing skincare brand. Write 3 Instagram captions that blend educational tone with Gen Z humor, without sounding forced. Include one emoji per caption.”

Why it works: You’re giving it a role, a tone, an audience, and constraints. That mimics the kind of labeled input Meta is collecting—and yields higher quality output even outside Meta’s models.

2. Prompt for Audience Fit

Meta’s tools are designed to hyper-personalize content. You can do the same—even without Meta's engine:

Prompt:
“Re-write this LinkedIn post for three segments: (1) marketing execs at startups, (2) CMOs at Fortune 500s, (3) solo creators trying to scale. Keep the core idea the same, but change tone, jargon, and examples.”

Why it matters: This helps you test content resonance like a pro. Meta’s AI will soon do this for advertisers. Get ahead by training yourself (and your models) to do it now.

3. Build a Mini Data Advantage

Start collecting your own “Scale AI” by saving your best-performing posts, ads, emails, and their metrics. Then, use them to train a custom GPT:

Prompt to upload into GPT memory:
“These are our highest-performing posts in Q1. Find the tone, structure, and topic commonalities. Use those patterns in future content.”

Result: A model that writes with your brand’s proven voice—something Meta’s Rivet-trained models will also be optimizing for at scale.

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