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Here’s what we got for you today:
MIT Teaches AI to Train Itself
OpenAI Just Entered the Toy Business
Programmatic SEO: What It Is—and When to Use It
MIT Teaches AI to Train Itself
MIT researchers have introduced SEAL (Self-Adapting LLMs), a new framework that enables language models to self-improve—generating their own training data and instructions to update themselves autonomously.
How it works: SEAL empowers models to write their own “self-edits”—custom instructions for synthesizing data and adjusting internal parameters. It uses a reinforcement learning loop, rewarding the model for edits that improve performance through trial and error.
Results:
In knowledge tasks, SEAL-trained models outperformed those trained with GPT-4.1-generated material—by learning from their own notes.
On puzzle-solving benchmarks, performance jumped from 0% to 72.5% using self-training strategies.
Why it matters: This kind of self-improvement hints at a foundational shift in AI: models that can evolve without human intervention. While frameworks like SEAL and Sakana’s DGM aren’t superintelligence yet, they mark real steps toward autonomous AI systems that can optimize themselves far beyond their original programming.
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OpenAI Just Entered the Toy Business
Mattel brings GenAI to playtime.
Mattel has officially teamed up with OpenAI—marking the first time the AI powerhouse has partnered with a toymaker. While OpenAI has already made waves in publishing and enterprise, this deal brings its tech into the world of toys, entertainment, and consumer creativity.
And Mattel is no longer just a toy company. After Barbie’s box office success, it's expanding into films (Hot Wheels, Barney, Polly Pocket), launching its first self-published game in 2026, and now... integrating AI.
Here’s what’s happening:
Mattel’s teams will use ChatGPT Enterprise to fuel product development and creative brainstorming.
AI-powered toys and content are slated to launch later in 2024.
The collaboration supports Mattel’s push into entertainment and gaming.
All AI work will be guided by a “safe, thoughtful, and responsible” design framework.
Why it matters: This isn’t just a tech upgrade—it’s a rebrand of childhood. From physical toys to digital games, Mattel is weaving AI into the fabric of play. And with OpenAI in the mix, don’t be surprised if your next action figure can hold a conversation.
Still waiting for Ken to ask ChatGPT why he was never CEO of Barbie Land.
Programmatic SEO: What It Is—and When to Use It
Scale your content, not your workload.
Imagine ranking for every keyword in your niche. That’s the promise of programmatic SEO (pSEO)—but it only works if you do it right.
Chris Hanna recently broke it down. Here’s the TL;DR:
What is Programmatic SEO?
Programmatic SEO is the practice of using templates and structured data to generate landing pages at scale. Instead of writing individual pages by hand, you automate the process—swapping in keyword variations and data while keeping the core structure consistent.
Think: thousands of pages, built around intent, with minimal manual effort.
One standout example? Wise. They’ve built over 8.5 million currency converter pages—each tailored to specific currencies and amounts. These pages aren’t fluff, either. They include real-time exchange rates, calculators, bank comparisons, and historical trends—all tied into actual transactions.
That’s how Wise ranks for 36,000+ “convert” keywords alone.
When to use (and avoid) pSEO
pSEO works best when you’ve got:
Large datasets
Strong keyword variation
Clear user intent
Meaningfully different content
If you're just swapping out a city name 500 times with no added value? That’s not pSEO—that’s spam.
But if you’ve got unique data, useful tools, or helpful comparisons to plug in, pSEO can unlock serious traffic at scale.
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