GPT-4.1 just landed in ChatGPT

How OpenAI and Google are racing to reshape how we build and optimize software. Learn here

Author

Jafar Najafov
May 15, 2025 • Read this in 6 minutes

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Hey there, today we’re going to explore the newest frontier in AI from OpenAI’s faster coding models inside ChatGPT to Google’s AlphaEvolve agent that’s literally evolving algorithms for math and hardware.

In today’s post:

  • OpenAI’s GPT-4.1 upgrade

  • Google’s AlphaEvolve breakthrough

  • Trending AI tools + Resources to learn AI

What’s Trending Today

Launch

OpenAI rolls out faster, smarter models for everyone

OpenAI just brought GPT-4.1 and GPT-4.1 mini to ChatGPT. This marks a key update for coders, tinkerers, and teams relying on AI day-to-day.

Here's everything you need to know:

  • GPT-4.1 is now available to ChatGPT Plus, Pro, and Team subscribers.

  • GPT-4.1 mini is rolling out to all users free and paid.

  • OpenAI says GPT-4.1 is faster and better at coding than GPT-4o.

  • The older GPT-4.0 mini model is being retired.

  • These models were first released via API in April, drawing transparency critiques.

  • OpenAI says GPT-4.1 isn't a "frontier model," so full safety reports weren't required.

  • To boost transparency, OpenAI launched a new Safety Evaluations Hub.

Here’s what I think:

OpenAI is threading a needle: upgrading models while managing scrutiny. GPT-4.1 may not be groundbreaking, but it's a clear step toward more capable, responsive tools. It also shows how product updates are now PR events in AI. Worth watching what comes next especially if that $3B Windsurf deal closes.

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Breakthrough

Google’s AlphaEvolve is rewriting the rules of algorithm design

AlphaEvolve isn’t just another coding tool. It’s Google’s new Gemini-powered agent that evolves entire algorithms—and it's already changing how we solve math and computing problems.

Everything about AlphaEvolve:

  • AlphaEvolve uses language models to design and optimize complex algorithms.

  • It combines creative AI output with automated evaluators to test each solution.

  • Already, it's improved Google’s data center scheduling, saving 0.7% compute.

  • In chip design, it rewrote key Verilog code for better TPU performance.

  • It sped up Gemini AI training by 1%, cutting engineering time from weeks to days.

  • AlphaEvolve discovered a faster way to multiply 4x4 complex matrices.

  • It also made progress on open math problems like the kissing number challenge.

Here’s what I think:

AlphaEvolve shows that algorithm design might soon become a collaborative effort between AI and humans. It doesn’t just automate code—it explores and evolves ideas. If this scales, it could change how we think about innovation itself. Keep an eye on its early access rollout.

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Resources

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