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AI Weekly 001

AI Weekly #001

🆕 What's new


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Enjoy last week's new tutorial:

Articles updates:

Community Q&A Highlights:

Q : The size of the output image can be directly adjusted using the Empty latent image. Why is there an upscale latent node and under what circumstances is it necessary to use it? (asked by heiba_wk)

  • Answer from Jimmy: I suggest you take another look at the tutorial about SD principles. Adjusting the size directly with an empty latent image may not produce good results. To explain by comparing it to the stone carving mentioned in the tutorial:

    • The empty latent image is like the stone carved by the sculptor (model). However, some sculptors (models) only carve 512x512 stones (images) during training. If you ask them to carve a 1024x1024 stone (image), they won't be able to do it well, and the result will be poor (for example, in case of a 512 image, the human figure is one head, but in a 1024 image, there are two heads).
    • But what if I want a 1024x1024 image? This is where you need to call on the Upscale sculptor (model). This sculptor (model) is not particularly good at creating, but is very good at proportional upsizing, and even some can add content details while enlarging.

  • Answer from Marc: In terms of code logic, the method used by upscale to enlarge the image actually uses basic image processing methods, such as ["nearest-exact", "bilinear", "area", "bicubic", "bislerp"]. These methods are much more cost-effective for generating large-sized images.

🤩 Weekly‘s AI highlights

If you encounter interesting AI-related articles or perhaps products during your studies, you are welcome to share them on our Discord Share Channel (opens in a new tab), or submit a newsletter Issue (opens in a new tab) on Github. If your submission is accepted, we will feature it in our newsletter to be seen by more people.

📄 Noteworthy papers and technic

Just one image is needed to generate a 3D version of it through AI. You can see some demos here, and the results seem pretty good from the examples. In the future, it may be possible to generate basic 3D models with just one picture, which will greatly enhance the efficiency of model creators.

Generating animation of physics-based characters with intuitive control has long been a desirable task with numerous applications. However, generating physically simulated animations that reflect high-level human instructions remains a difficult problem due to the complexity of physical environments and the richness of human language. In this paper, researcher present InsActor, a principled generative framework that leverages recent advancements in diffusion-based human motion models to produce instruction-driven animations of physics-based characters.

🛠️ Products you should try

  • Pika 1.0 (opens in a new tab) : a text-to-video app is now available to everyone.

  • BabyStoryAI (opens in a new tab): There's a product that uses AI to generate children's stories - what sets it apart from similar products is that it can convert content into speech and automatically add background music. It would be even better if it could generate illustrations based on the plot.


  • Room Renivented (opens in a new tab): The other product is an AI-generated interior design tool. There are many similar products on the market, so why am I sharing this one? Mainly because I think there are still many opportunities in this field. Right now, the biggest problem with most of these products is that the designs are not appealing. This is not just a technical problem, but a crucial one - most people developing these products don't have taste like professional designers. If you have good taste in interior design, you might want to consider this direction.

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