LLM Image Generation Breakthrough in 2024

llm image generation
April 17, 20246 min
Adi Nisman photo
Adi Nisman

The impact of LLM image generation on the food industry has been profound in recent years. As social media platforms like TikTok, Instagram, Facebook, and Pinterest rise in popularity, captivating food images have become crucial to the success of restaurants and food brands.

This article delves into how LLM image generation has revolutionized the food industry, examining its effects on businesses and consumers alike.

What is LLM?

LLM stands for “Large Language Model”, a type of artificial intelligence (AI) technology that can generate human-like text and images. LLM image generation uses deep learning algorithms to analyze patterns in large datasets of food images and then creates new, realistic-looking images based on those patterns. This allows the AI to generate high-quality, visually appealing food images that are almost indistinguishable from ones taken by humans.

What is LLM Image Generation?

LLM image generation has many applications, but its use in the food industry has been particularly noteworthy. With social media becoming a major marketing platform for restaurants and food brands, having a strong visual presence is crucial. LLM-generated images can be used for menu designs, social media posts, advertisements, and more.

Advantages of LLM Image Generation

There are several advantages to using LLM image generation in the food industry:

  • Cost-effective: Creating high-quality images can be expensive and time-consuming. However, with LLM image generation, businesses can generate an unlimited number of realistic-looking images at a fraction of the cost.
  • Time-saving: As mentioned, creating visually appealing food images can be a time-consuming process. With LLM image generation, businesses can quickly generate high-quality images without the need for photographers or stylists.
  • Versatility: LLM-generated images can be used for various purposes, from marketing materials to product packaging. This versatility allows businesses to use the same image in different contexts, saving time and resources.
  • Consistency: With humans taking photos, there may be slight variations in lighting, angle, and presentation. However, LLM-generated images are consistent and uniform, allowing for a cohesive brand image across all platforms.

Limitations of LLM Image Generation

Although LLM image generation has many advantages, there are also some limitations to consider:

  • Limited creativity: While LLM algorithms can produce realistic-looking images, they may lack the creativity and artistry that human photographers possess. This could result in generic or repetitive images.
  • Lack of customization: With LLM-generated images, businesses have limited control over specific details such as plating, garnishes, and backgrounds. This could be an issue for brands with a distinct aesthetic.
  • Ethical concerns: The use of AI technology raises ethical questions surrounding ownership and copyright. As more businesses turn to LLM image generation, it is essential to consider the implications and potential consequences of using AI-generated content.

The Challenge of Production-Grade AI Use

Most people playing with AI image generators have the luxury of trial and error. They can tweak prompts or switch models until they get the perfect image. The stakes are much higher in a production environment, where we use these models to generate images for any user query instantly.

Our previous images were good, but “good” isn’t good enough. We needed to guarantee top-notch, realistic images for even the most specific and uncommon requests.

The AI Image Generation Problem

The solution required an innovative approach. We couldn’t just feed prompts into the model; we had to ensure these prompts were tailored to produce the best possible outcome every time. So, we integrated LLMs like ChatGPT to refine and structure the prompts for our image generator.

However, despite these efforts, the “no parameter” setting in these models does not inherently guide what to include, only what to exclude. This means they do not “understand” text how humans do (Midjourney No Parameter, n.d.). They give weight to each word, meaning our prompts must be precise and informative.

For instance, our approach has significantly enhanced the accuracy of image generation across a variety of scenarios. To clarify, two illustrative examples: Initially, when we requested images of french fries without ketchup (Image 1), the model persisted in including ketchup, revealing its limitations in understanding the text as humans do.

Image 1

AI Images

Prompt: french fries. without ketchup

A more intricate challenge arose with the idea of an innovative bagel (Image 2). Simply providing a basic prompt often resulted in ambiguity, particularly regarding whether the innovation pertained to the bagel dough or its filling.

Image 2

AI Images

Prompt: Ramp bagel. Plated

Two of the results are plain bagel and the other two show bagels as sandwiches.

Our AI Image Generation Solution: An LLM Innovation

To address these challenges, we explained to an LLM how to transform our ideas into precise, unambiguous prompts. This strategy enabled the image generation model to accurately produce visuals that matched our specific intentions, ranging from ketchup-free french fries (Image 3) to uniquely innovative bagels (Image 4).

These examples underscore the model’s occasional misinterpretation of our requests. A practical scenario further illustrating this point is when we suggest adding white chocolate to a cookie.

Image 3

AI Images

This image showcases the model’s ability to showcase realistic textures and variations in shape for a common food, and make it more interesting.

Image 4

AI Images

This image highlights the model’s capacity to create detailed textures for baked goods, balancing the filling inside and crispy exterior.

Image 5

AI Images

The model needs clear guidance on whether the white chocolate should flavor the cookie, serve as a topping, fill, or be integrated as chunks (Image 5 and Image 6).

Image 6

AI Images

Here, the model showcases its ability to change how the food looks based on prompts, where the white chocolate is integrated into the cookie itself.

Midjourney no parameter. (n.d.).

These refinements demonstrate our commitment to ensuring that every image precisely conveys our suggestions, enhancing user understanding and interaction with our content.

Looking Forward

Our work doesn’t stop here. The goal is to keep pushing the boundaries of what AI image generation can achieve, ensuring our images are realistic and portray what we want to show. We’re dedicated to continuous improvement, aiming always to surpass user expectations. In this case, we are just speaking about images but we have more interesting things coming down the line like videos and who knows what else?

In sum, having an LLM create our prompt for our AI image generation models is crucial to enhancing our visuals’ quality and realism. We need an excellent alignment between our text and images because it directly impacts user satisfaction and engagement.

What can food intelligence do for you?