Hi fam!
Happy Friday! ☀️
While temperatures across Europe keep climbing, the AI world isn't exactly cooling down either.
This week brought another wave of new models, bold announcements, and thought-provoking developments. We've also got a practical prompt to help you build better ideas—and a look at why so much AI-generated content is starting to feel surprisingly... familiar.
Grab a cold drink, find a bit of shade, and let's dive in. 🚀
The future of AI feels Like Magic, and it’s here!
Over the past few days, we've seen fresh developments in AI hardware, regulation, and global competition—another reminder that the AI landscape is evolving at an incredible pace.
Here's what caught our attention this week. 🚀
OpenAI introduced its first in-house AI chip, Jalapeño, developed with Broadcom. The chip is designed to run AI models more efficiently and marks OpenAI's first major step toward reducing its reliance on NVIDIA hardware.
Why this matters: The AI race is no longer just about better models. It's increasingly about who controls the infrastructure that powers them.
Chinese startup Z.ai announced plans for a dual stock market listing after releasing its new GLM-5.2 model, which reportedly rivals leading Western AI models while running at a fraction of the cost.
Why this matters: The global AI race is becoming more competitive, with Chinese companies rapidly closing the gap in performance while focusing on lower costs.
According to TechCrunch, the White House has asked OpenAI to slow the rollout of its next frontier model while additional safety evaluations are completed.
Why this matters: Governments are becoming increasingly involved in AI development, and safety discussions are starting to influence product release timelines.
Alphabet has come under renewed pressure after losing several high-profile AI researchers to competitors, raising fresh questions about its ability to retain top talent. Investors are also watching closely as AI spending continues to rise across the industry.
Why this matters: Winning the AI race isn't just about building better models—it's also about attracting and keeping the researchers who create them.
A new study by researchers at the European Central Bank found that intensive AI adoption remains surprisingly rare among companies in the eurozone. While many businesses are experimenting with AI, only a small percentage have integrated it deeply into their day-to-day operations.
Why this matters: Despite the excitement around AI, widespread adoption is taking longer than many expected. The biggest challenge is no longer access to AI tools—it's figuring out how to use them effectively in real business workflows.
The Steal Like an Artist Prompt
Almost nobody wakes up with a completely original idea.
Most great ideas are simply old ideas mixed together in a new way.
The next time you're starting a project, don't ask AI to invent something from scratch.
Ask this instead:
"Show me three successful examples I can learn from, and explain what makes each one work. Then suggest how I could combine the best ideas into something original."
For example:
"I want to start an AI newsletter. Show me three successful newsletters, explain why people love them, and suggest how I could combine their best ideas into something unique."
Or:
"I want to launch a productivity app. Show me three successful apps, explain what each one does well, and suggest how I could create something different."
Notice what you're not asking AI to do.
You're not asking it to copy.
You're asking it to identify patterns.
The best creators rarely invent everything from scratch. They study what already works, borrow the principles—not the product—and build something that reflects their own style.
Because originality isn't about pretending nobody has had your idea before.
It's about combining familiar ideas in a way that only you would.
Now go steal... responsibly. 😉
How to Make AI Content Stand Out
Remember when AI-generated content felt fresh?
Yeah... that lasted about five minutes.
These days, it's getting harder to scroll through LinkedIn without seeing the same headlines, the same illustrations, and the same "game-changing" insights written in exactly the same style. It's almost as if millions of people hired the very same copywriter.
Well... they kind of did.
Today, we're exploring why so much AI-generated content is starting to look alike—and, more importantly, how you can avoid becoming part of the AI copy-and-paste crowd.
Because in a world where everyone has access to the same tools, being different may become your biggest competitive advantage.
👉 Read the full article: How to Make AI Content Stand Out
From The Archive: Video-Making App That Even Gen Z Likes
Back in 2024, we reviewed CapCut and asked whether it had become the video editing app that even Gen Z couldn't live without.
Looking back from 2026, that prediction has aged remarkably well.
CapCut is still one of the world's most popular video editing apps, but the landscape has changed dramatically. AI video editing has gone from being a nice bonus feature to something users simply expect. Today, nearly every major editing platform offers AI-powered tools for generating captions, removing backgrounds, creating B-roll, translating videos, and even editing with simple text prompts.
CapCut is no longer the only player in town, but it helped set the standard for what modern video editing should feel like: fast, intuitive, and AI-assisted.
The question is no longer whether AI belongs in video editing.
It's which AI editor fits your workflow best.
Text generation | Image Generation | LMAI recommends |
|---|---|---|
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