The Return of The King of AI: Google Is Back

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Hi everyone,

This is Lore, the newsletter that helps you thrive in the age of AI.  

Thank you for being a part of 23k+ techno-optimists and growing. 🙏

P.S. Watch the latest episode of The Next Wave where Matt showed off an early access demo of Google’s Project Astra!

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1) Things Are Getting Better

OpenAI’s o1-preview—not even the full-fledged o1 or o1 Pro models—has already scored 80% on a test designed to identify hard-to-diagnose medical issues. For comparison, the average human doctor scores around 30%.

In other words: AI is already better at diagnosing diseases than the average doctor. This is the worst it’s ever going to be…

2) The Return of The King of AI: Google Is Back

I need to admit something: I was wrong about Google.

For two years, I’ve been openly skeptical. Here was the company that created the transformer technology behind ChatGPT—and yet, when consumer AI started to take off, they were nowhere to be seen. And when they finally released something, it was an overly woke product that had a lot of hilariously bad results.

That skepticism began to crack with the debut of Notebook LM, their AI-powered podcast creation tool, which still is one of the most magical AI products I’ve used. But this week, I became convinced: Google is not just back, they’re here to take the crown off OpenAI’s head.

The last few product announcements in the last week have shown a company fully committed to the AI arms race, and they’re moving fast.

Veo 2:
The most visually compelling AI video model I’ve tested yet, Veo 2, was just revealed. You can join the waitlist here.

Compared side-by-side with OpenAI’s Sora Turbo, Veo 2’s outputs border on photorealistic. Whereas Sora has major issues with gravity and clipping. Check out this comparison video.

I’m really excited by the significant leap in quality with Veo 2—one that could rapidly accelerate the practical use of AI-generated video in everything from entertainment to product marketing. I’m now convinced, in 2025-26 we’re going to have full-blown AI movies.

I’ve created a thread on X with a lot of great examples.

Gemini 2.0:
This new multimodal model goes beyond just text and images. Gemini 2.0 can handle audio input, complex reasoning, and fully integrate with your workflow. While it’s not as good as OpenAI’s best models yet, it’s not far behind. I’m hearing from developers that the cost/quality ratio is the best out there so many developers are switching over.

You can try Gemini 2.0 in the Google AI Studio.

Project Astra:
This is a leap toward ambient computing. Astra runs directly on your phone and integrates with experimental AR glasses. It “sees” what you see, can retain context for up to 10 minutes, and taps into Google’s ecosystem—Search, Maps, Lens—to deliver real-time, personalized assistance. With an early-access demo on this week’s episode of The Next Wave, we saw a glimpse of a future where AI doesn’t just respond—it proactively enhances your day-to-day experiences, blending digital services seamlessly into the physical world.

My podcast co-host Matt Wolfe demoed Project Astra this week exclusively on The Next Wave podcast:

I’ve been critical of Google’s early stumbles in the AI race, but it’s only fair to acknowledge when the tide turns. They’re not just catching up to OpenAI and Anthropic—they’re charting new territory. For anyone who values rapid progress and open competition, this is great news. The creative friction between industry giants will only accelerate breakthroughs, driving down costs, increasing capabilities, and ultimately delivering more powerful AI tools for all of us.

2025 is going to be an insane year for AI. I can’t wait.

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3) Things I’m Testing Out

• Dan Shipper has announced Cora, an entirely new take on email where you receive a summary of most of your emails. And you only receive the most important emails. Super interesting approach I’ve signed up to try. (link)

• OpenAI has made o1 available in the API with a 200k context window and vision. Can now use it in Cursor for coding! (link)

• Open-source train-time compute (an o1 type approach) with LLaMA 1B is now on HuggingFace. It beats the LLaMA 8B model! 🤯 (link)

4) Things I’m Learning From

That’s all for today. Please consider sharing the newsletter with your friends if you think they’d enjoy it. 🙏

Please give me feedback on Twitter. I am still figuring out the best format for this newsletter. Which part did you like? Dislike? Do you have other suggestions? Please let me know—just tweet @NathanLands.

-Nathan