AI Image Generation News
AI image generation news. DALL-E, Midjourney, Stable Diffusion, Flux updates. Visual AI model releases and capabilities.
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Accelerating your marketing ideation with generative AI – Part 1: From idea to generation with the Amazon Nova foundation models
In this post, the first of a series of three, we focus on how you can use Amazon Nova to streamline, simplify, and accelerate marketing campaign creation through generative AI. We show how Bancolombia, one of Colombia’s largest banks, is experimenting with the Amazon Nova models to generate visuals for their marketing campaigns.
New computer vision method links photos to floor plans with pixel-level accuracy
For people, matching what they see on the ground to a map is second nature. For computers, it has been a major challenge. A Cornell research team has introduced a new method that helps machines make these connections—an advance that could improve robotics, navigation systems, and 3D modeling.
Build a multimodal generative AI assistant for root cause diagnosis in predictive maintenance using Amazon Bedrock
In this post, we demonstrate how to implement a predictive maintenance solution using Foundation Models (FMs) on Amazon Bedrock, with a case study of Amazon's manufacturing equipment within their fulfillment centers. The solution is highly adaptable and can be customized for other industries, including oil and gas, logistics, manufacturing, and healthcare.
Splat’s app uses AI to turn your photos into coloring pages for kids
The app turns your own photos into pages for your kids to color, via AI.
Introducing GPT-5.2-Codex
Introducing GPT-5.2-Codex The latest in OpenAI's Codex family of models (not the same thing as their Codex CLI or Codex Cloud coding agent tools). GPT‑5.2-Codex is a version of GPT‑5.2 further optimized for agentic coding in Codex, including improvements on long-horizon work through context compaction, stronger performance on large code changes like refactors and migrations, improved performance in Windows environments, and significantly stronger cybersecurity capabilities. As with some previous Codex models this one is available via their Codex coding agents now and will be coming to the API "in the coming weeks". Unlike previous models there's a new invite-only preview process for vetted cybersecurity professionals for "more permissive models". I've been very impressed recently with GPT 5.2's ability to tackle multi-hour agentic coding challenges. 5.2 Codex scores 64% on the Terminal-Bench 2.0 benchmark that GPT-5.2 scored 62.2% on. I'm not sure how concrete that 1.8% improvement will be! I didn't hack API access together this time (see previous attempts), instead opting to just ask Codex CLI to "Generate an SVG of a pelican riding a bicycle" while running the new model (effort medium). Here's the transcript in my new Codex CLI timeline viewer, and here's the pelican it drew: Tags: ai, openai, generative-ai, llms, pelican-riding-a-bicycle, llm-release, codex-cli, gpt-codex
Gemini 3 Flash
It continues to be a busy December, if not quite as busy as last year. Today's big news is Gemini 3 Flash, the latest in Google's "Flash" line of faster and less expensive models. Google are emphasizing the comparison between the new Flash and their previous generation's top model Gemini 2.5 Pro: Building on 3 Pro’s strong multimodal, coding and agentic features, 3 Flash offers powerful performance at less than a quarter the cost of 3 Pro, along with higher rate limits. The new 3 Flash model surpasses 2.5 Pro across many benchmarks while delivering faster speeds. Gemini 3 Flash's characteristics are almost identical to Gemini 3 Pro: it accepts text, image, video, audio, and PDF, outputs only text, handles 1,048,576 maximum input tokens and up to 65,536 output tokens, and has the same knowledge cut-off date of January 2025 (also shared with the Gemini 2.5 series). The benchmarks look good. The cost is appealing: 1/4 the price of Gemini 3 Pro ≤200k and 1/8 the price of Gemini 3 Pro >200k, and it's nice not to have a price increase for the new Flash at larger token lengths. It's a little more expensive than previous Flash models - Gemini 2.5 Flash was $0.30/million input tokens and $2.50/million on output, Gemini 3 Flash is $0.50/million and $3/million respectively. Google claim it may still end up cheaper though, due to more efficient output token usage: > Gemini 3 Flash is able to modulate how much it thinks. It may think longer for more complex use cases, but it also uses 30% fewer tokens on average than 2.5 Pro. Here's a more extensive price comparison on my llm-prices.com site. Generating some SVGs of pelicans I released llm-gemini 0.28 this morning with support for the new model. You can try it out like this: llm install -U llm-gemini llm keys set gemini # paste in key llm -m gemini-3-flash-preview "Generate an SVG of a pelican riding a bicycle" According to the developer docs the new model supports four different thinking level options: minimal, low, medium, and high. This is different from Gemini 3 Pro, which only supported low and high. You can run those like this: llm -m gemini-3-flash-preview --thinking-level minimal "Generate an SVG of a pelican riding a bicycle" Here are four pelicans, for thinking levels minimal, low, medium, and high: I built the gallery component with Gemini 3 Flash The gallery above uses a new Web Component which I built using Gemini 3 Flash to try out its coding abilities. The code on the page looks like this: <image-gallery width="4"> <img src="https://static.simonwillison.net/static/2025/gemini-3-flash-preview-thinking-level-minimal-pelican-svg.jpg" alt="A minimalist vector illustration of a stylized white bird with a long orange beak and a red cap riding a dark blue bicycle on a single grey ground line against a plain white background." /> <img src="https://static.simonwillison.net/static/2025/gemini-3-flash-preview-thinking-level-low-pelican-svg.jpg" alt="Minimalist illustration: A stylized white bird with a large, wedge-shaped orange beak and a single black dot for an eye rides a red bicycle with black wheels and a yellow pedal against a solid light blue background." /> <img src="https://static.simonwillison.net/static/2025/gemini-3-flash-preview-thinking-level-medium-pelican-svg.jpg" alt="A minimalist illustration of a stylized white bird with a large yellow beak riding a red road bicycle in a racing position on a light blue background." /> <img src="https://static.simonwillison.net/static/2025/gemini-3-flash-preview-thinking-level-high-pelican-svg.jpg" alt="Minimalist line-art illustration of a stylized white bird with a large orange beak riding a simple black bicycle with one orange pedal, centered against a light blue circular background." /> </image-gallery> Those alt attributes are all generated by Gemini 3 Flash as well, using this recipe: llm -m gemini-3-flash-preview --system ' You write alt text for any image pasted in by the user. Alt text is always presented in a fenced code block to make it easy to copy and paste out. It is always presented on a single line so it can be used easily in Markdown images. All text on the image (for screenshots etc) must be exactly included. A short note describing the nature of the image itself should go first.' \ -a https://static.simonwillison.net/static/2025/gemini-3-flash-preview-thinking-level-high-pelican-svg.jpg You can see the code that powers the image gallery Web Component here on GitHub. I built it by prompting Gemini 3 Flash via LLM like this: llm -m gemini-3-flash-preview ' Build a Web Component that implements a simple image gallery. Usage is like this: <image-gallery width="5"> <img src="image1.jpg" alt="Image 1"> <img src="image2.jpg" alt="Image 2" data-thumb="image2-thumb.jpg"> <img src="image3.jpg" alt="Image 3"> </image-gallery> If an image has a data-thumb= attribute that one is used instead, other images are scaled down. The image gallery always takes up 100% of available width. The width="5" attribute means that five images will be shown next to each other in each row. The default is 3. There are gaps between the images. When an image is clicked it opens a modal dialog with the full size image. Return a complete HTML file with both the implementation of the Web Component several example uses of it. Use https://picsum.photos/300/200 URLs for those example images.' It took a few follow-up prompts using llm -c: llm -c 'Use a real modal such that keyboard shortcuts and accessibility features work without extra JS' llm -c 'Use X for the close icon and make it a bit more subtle' llm -c 'remove the hover effect entirely' llm -c 'I want no border on the close icon even when it is focused' Here's the full transcript, exported using llm logs -cue. Those five prompts took: 225 input, 3,269 output 2,243 input, 2,908 output 4,319 input, 2,516 output 6,376 input, 2,094 output 8,151 input, 1,806 output Added together that's 21,314 input and 12,593 output for a grand total of 4.8436 cents. The guide to migrating from Gemini 2.5 reveals one disappointment: Image segmentation: Image segmentation capabilities (returning pixel-level masks for objects) are not supported in Gemini 3 Pro or Gemini 3 Flash. For workloads requiring native image segmentation, we recommend continuing to utilize Gemini 2.5 Flash with thinking turned off or Gemini Robotics-ER 1.5. I wrote about this capability in Gemini 2.5 back in April. I hope they come back in future models - they're a really neat capability that is unique to Gemini. Tags: google, ai, web-components, generative-ai, llms, llm, gemini, llm-pricing, pelican-riding-a-bicycle, llm-release
The new ChatGPT Images is here
The new ChatGPT Images is here OpenAI shipped an update to their ChatGPT Images feature - the feature that gained them 100 million new users in a week when they first launched it back in March, but has since been eclipsed by Google's Nano Banana and then further by Nana Banana Pro in November. The focus for the new ChatGPT Images is speed and instruction following: It makes precise edits while keeping details intact, and generates images up to 4x faster It's also a little cheaper: OpenAI say that the new gpt-image-1.5 API model makes image input and output "20% cheaper in GPT Image 1.5 as compared to GPT Image 1". I tried a new test prompt against a photo I took of Natalie's ceramic stand at the farmers market a few weeks ago: Add two kakapos inspecting the pots Here's the result from the new ChatGPT Images model: And here's what I got from Nano Banana Pro: The ChatGPT Kākāpō are a little chonkier, which I think counts as a win. I was a little less impressed by the result I got for an infographic from the prompt "Infographic explaining how the Datasette open source project works" followed by "Run some extensive searches and gather a bunch of relevant information and then try again" (transcript): See my Nano Banana Pro post for comparison. Both models are clearly now usable for text-heavy graphics though, which makes them far more useful than previous generations of this technology. Update 21st December 2025: I realized I already have a tool for accessing this new model via the API. Here's what I got from the following: OPENAI_API_KEY="$(llm keys get openai)" \ uv run openai_image.py -m gpt-image-1.5\ 'a raccoon with a double bass in a jazz bar rocking out' Total cost: $0.2041. Tags: ai, kakapo, openai, generative-ai, text-to-image, nano-banana
The new ChatGPT Images is here
The new ChatGPT Images is powered by our flagship image generation model, delivering more precise edits, consistent details, and image generation up to 4× faster. The upgraded model is rolling out to all ChatGPT users today and is also available in the API as GPT-Image-1.5.
The great AI hype correction of 2025
Some disillusionment was inevitable. When OpenAI released a free web app called ChatGPT in late 2022, it changed the course of an entire industry—and several world economies. Millions of people started talking to their computers, and their computers started talking back. We were enchanted, and we expected more. We got it. Technology companies scrambled to…
Teaching AI to see the world more like we do
Our new paper analyzes the important ways AI systems organize the visual world differently from humans.
Import AI 433: AI auditors; robot dreams; and software for helping an AI run a lab
Would Alan Turing be surprised?
Exploring the context of online images with Backstory
New experimental AI tool helps people explore the context and origin of images seen online.
Image editing in Gemini just got a major upgrade
Transform images in amazing new ways with updated native image editing in the Gemini app.
Taste is your moat — with Dylan Field, Figma
Letting designers build with Figma Make, how Figma can be the context repository for aesthetic in the age of vibe coding, and why design is your only differentiator now
Creating a safe, observable AI infrastructure for 1 million classrooms
Discover how SchoolAI, built on OpenAI’s GPT-4.1, image generation, and TTS, powers safe, teacher-guided AI tools for 1 million classrooms worldwide—boosting engagement, oversight, and personalized learning.
A Technical History of Generative Media — with Gorkem and Batuhan from Fal.ai
From Stable Diffusion to Veo3, why generative media is completely different than LLM inference, and how to scale to $100M ARR while writing custom kernels
Import AI 426: Playable world models; circuit design AI; and ivory smuggling analysis
Do you talk to synths?
Import AI 424: Facebook improves ads with RL; LLM and human brain similarities; and mental health and chatbots
Are you living as though the singularity is imminent?
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