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  • Meta launch 3D Gen, a text-to-3D model generator

Meta launch 3D Gen, a text-to-3D model generator

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Happy 4th of July, folks. ๐Ÿ‡บ๐Ÿ‡ธ

Good morning, human brains, and welcome back to your daily munch of AI news.

Hereโ€™s whatโ€™s on the menu today:

  • Create high-quality 3D models in 60 seconds ๐ŸงŠ ๐Ÿชฉ

    Meta launched 3D Gen, a text-to-3D model generator.

  • Design your dream home with AI ๐Ÿ  ๐Ÿ”ฅ

    Dune dream house, rainforest retreat, and more.

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MAIN COURSE

High-quality 3D models in 60 secs ๐ŸงŠ ๐Ÿชฉ

On Tuesday, Meta launched 3D Gen. Itโ€™s a text-to-3D asset generation model.

Girl, are you a 3D movie? You're expensive and give me a headache. ๐Ÿค•

How does it work?

It generates a 3D mesh with physically-based rendering (PBR) from text. Then it creates high-quality, detailed textures that combine into a complete 3D model.

Is it any good?

It outperforms top models in speed, quality, versatility, and more. It creates complex characters and entire scenes that closely follow your instructions.

So, what?

You can use this tool to develop games, product prototypes, architectural visualizations, VR and AR assets, and more.

They have VR for cows now. Itโ€™s a moooood enhancer. ๐Ÿ„ โค๏ธ

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YOUR DAILY MUNCH

Think Pieces ๐Ÿง 

How climate-conscious is Googleโ€™s environmental report? It contains more than 80 pages detailing its efforts, but doesnโ€™t say how much energy it uses.

Startup News ๐Ÿ’ฐ

Meta is changing its AI labels from Made with AI to AI Info. It was incorrectly labeling real photos as AI-generated content.

Amazon proposes new benchmarks to evaluate RAG systems. It uses multiple-choice exams to assess how well RAG implementations handle tasks.

Research ๐Ÿ‘จโ€๐Ÿ”ฌ

MMEvalPro โ€” a benchmark designed to provide trustworthy evaluations of multimodal models by eliminating systematic biases and Type-I errors.

We-Math โ€” a benchmark that evaluates large multimodal models (LMMs) on their visual mathematical reasoning skills.

FURRY FRIENDS

Hereโ€™s Dashi. ๐Ÿถ

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MEMES FOR DESSERT

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WHAT WOULD YOU DO?

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Until next time ๐Ÿค–๐Ÿ˜‹๐Ÿง  

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