# Images Published articles for Images. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## 25 Places Designers Can Still Find Free, Non-AI Images for Commercial Use DevFeed: [25 Places Designers Can Still Find Free, Non-AI Images for Commercial Use]() Original publisher: [Read original article]() Author: Alex Harper Published: 2026-09-17T17:00:00Z Content type: article Language: en Sources: [Web Designer Depot]() Topics: [Image](), [Web](), [Artificial Intelligence]() Tags: [ai](), [ai-images](), [asset](), [cc0-images](), [commercial-use-images](), [creative-commons](), [design-resources](), [free-design-assets](), [free-images-for-designers](), [free-stock-photos](), [human-made-images](), [image-licensing](), [images](), [museum-images](), [non-ai-images](), [open-access-images](), [pexels](), [photography](), [photography-resources](), [pixabay](), [public-domain-images](), [stock-photography](), [unsplash](), [visual-design-resources](), [visual-ui-design](), [web-design-resources]() ### AI overview A guide to 25 sources of free photography, artwork, illustrations, historical imagery, textures, and other visual assets for commercial design projects, with attention to whether assets are human-made and how licensing applies. ### Source excerpt AI images are taking over stock libraries, but the human-made web isn't dead yet. We found 25 places where designers can still find incredible free, real photography, art, and imagery for commercial use. ## New AI technique could make minimally invasive surgeries safer and more precise DevFeed: [New AI technique could make minimally invasive surgeries safer and more precise]() Original publisher: [Read original article]() Author: Adam Zewe | MIT News Published: 2026-09-16T15:00:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [Artificial Intelligence](), [AI Research](), [3D](), [navigation]() Tags: [3d](), [ai](), [artificial-intelligence](), [computer-science-and-artificial-intelligence-laboratory-csail](), [computer-science-and-technology](), [computer-vision](), [electrical-engineering-and-computer-science-eecs](), [health-care](), [images](), [imaging](), [jameel-clinic](), [machine-learning](), [medical-devices](), [medical-imaging](), [minimally-invasive-surgery](), [mit-ibm-computing-research-lab](), [mit-schwarzman-college-of-computing](), [model](), [national-institutes-of-health-nih](), [navigation](), [paper](), [polina-golland](), [precision](), [real-time](), [research](), [school-of-engineering](), [vision](), [vivek-gopalakrishnan]() ### AI overview MIT researchers and collaborators developed xvr, an AI method that adapts to individual patients and rapidly aligns intraoperative X-rays with preoperative 3D medical scans. The technique is intended to improve surgical navigation for minimally invasive procedures. ### Source excerpt This patient-specific method, called xvr, helps doctors use X-rays for surgical navigation in fields such as orthopedics and neurosurgery. ## Making thumbnails fast DevFeed: [Making thumbnails fast]() Original publisher: [Read original article]() Author: Khan Academy Published: 2015-09-14T22:00:00Z Content type: tutorial Language: en Sources: [Khan Academy]() Topics: [Image](), [pixel](), [Server](), [Software]() Tags: [article](), [blog](), [code](), [color](), [components](), [design](), [engineering](), [image](), [images](), [news](), [rgb](), [software](), [web-frontend]() ### AI overview Khan Academy explains how it generated custom video thumbnails by resizing, desaturating, lightening, color-tinting, and overlaying text and branding on source images. The post also explains pixel multiplication and why the team implemented the image operations themselves because its server infrastructure could not use available libraries. ### Source excerpt Note: This post contains quite a bit of LaTeX notation, which is not supported right now on this ... Read more ## How I Used a Pinterest Board to Get Better Visual Results From Claude Design DevFeed: [How I Used a Pinterest Board to Get Better Visual Results From Claude Design]() Original publisher: [Read original article]() Author: Sydney Cole Published: 2026-09-13T12:00:33Z Content type: tutorial Language: en Sources: [Atomic Object]() Topics: [Claude](), [Artificial Intelligence](), [Claude Code](), [Code](), [Website]() Tags: [ai](), [ai-design-tools](), [ai-for-designers](), [claude](), [claude-code](), [code](), [design](), [how-to](), [html](), [images](), [iteration](), [pinterest](), [portfolio](), [prompt](), [website]() ### AI overview An account of using a Pinterest mood board as a visual reference for Claude Design when creating a creative portfolio website. The author reports that the image references produced less generic layouts and helped clarify the intended aesthetic; Claude Code then generated a basic HTML site based on the design. ### Source excerpt I've been building out a portfolio site for my creative work. While I have hesitations about mixing AI with my art, I decided to use this website as an opportunity to try out Claude Design. Like most people who've tried generating a design with AI, I ran into the same issue over and over. I'd [...] The post How I Used a Pinterest Board to Get Better Visual Results From Claude Design appeared first on Atomic Spin. ## Video and image search in Amazon Bedrock Knowledge Base using Marengo 3.0 DevFeed: [Video and image search in Amazon Bedrock Knowledge Base using Marengo 3.0]() Original publisher: [Read original article]() Author: Eric Kim Published: 2026-09-10T21:15:39Z Content type: tutorial Language: en Sources: [Artificial Intelligence]() Topics: [AI search](), [Retrieval Augmented Generation (RAG)](), [Amazon S3](), [AWS IAM]() Tags: [amazon-bedrock](), [amazon-bedrock-knowledge-bases](), [announcements](), [audio](), [embedding](), [how-to](), [images](), [intermediate-200](), [multimodal](), [rag](), [s3](), [search](), [video]() ### AI overview A walkthrough for building an Amazon Bedrock Knowledge Base with TwelveLabs Marengo Embed 3.0 to perform natural-language semantic search across video, images, and audio. ### Source excerpt TwelveLabs Marengo Embed 3.0 is now generally available as an embedding model in Amazon Bedrock Knowledge Bases, bringing fully managed natural language search to video, image, and audio content. This walkthrough shows how to build a knowledge base powered by Marengo 3.0 and run semantic queries against your media. ## GPT Images 2.5 promises edits that leave the rest of your image alone DevFeed: [GPT Images 2.5 promises edits that leave the rest of your image alone]() Original publisher: [Read original article]() Author: Meredith Shubel Published: 2026-09-10T19:46:32Z Content type: news Language: en Sources: [The New Stack]() Topics: [Artificial Intelligence](), [Latency]() Tags: [ai](), [applications](), [cost](), [generation](), [gpt](), [images](), [latency](), [model](), [models](), [openai](), [production](), [prototyping](), [search](), [workflows]() ### AI overview OpenAI's GPT Images 2.5 introduces two image-editing models: Flare, optimized for speed and lower latency, and Sunburst, designed for greater precision and control. Both have the same listed token rates, but OpenAI does not explain their actual token consumption or comparative per-image costs. ### Source excerpt When OpenAI launched GPT Images 2.5 this week, the company promised better results for a common editing task: changing one The post GPT Images 2.5 promises edits that leave the rest of your image alone appeared first on The New Stack. ## Introducing ChatGPT Images 2.5 DevFeed: [Introducing ChatGPT Images 2.5]() Original publisher: [Read original article]() Published: 2026-09-08T11:30:00Z Content type: release Language: en Sources: [OpenAI News]() Topics: [API]() Tags: [api](), [chatgpt](), [codex](), [feature](), [generate](), [generation](), [gpt](), [images](), [latency](), [mobile](), [models](), [product](), [speed](), [web](), [work](), [workflows]() ### AI overview ChatGPT Images 2.5 is a new image model with sharper details, more precise multi-turn editing, improved reference-photo fidelity, richer textures, and up to 50% lower generation latency than Images 2.0. The release adds creative controls in ChatGPT and introduces GPT-Image-2.5 Flare and Sunburst in the API. ### Source excerpt ChatGPT Images 2.5 helps turn your ideas, sketches, and reference photos into more personalized, polished images that better reflect your ideas. ## GPT Image 2.5 Flare and Sunburst now available on AI Gateway DevFeed: [GPT Image 2.5 Flare and Sunburst now available on AI Gateway]() Original publisher: [Read original article]() Author: Jerilyn Zheng Published: 2026-09-08T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Artificial Intelligence](), [OpenAI]() Tags: [ai](), [generation](), [gpt](), [image](), [images](), [models](), [openai](), [playground]() ### AI overview OpenAI's GPT Image 2.5 Flare and GPT Image 2.5 Sunburst are now available through AI Gateway for image generation and editing. Flare emphasizes faster generation, while Sunburst prioritizes editing precision; both support text prompts, reference images, detailed instructions, complex layouts, transparent backgrounds, and targeted edits that preserve the rest of an image. ### Source excerpt GPT Image 2.5 Flare and GPT Image 2.5 Sunburst from OpenAI are now available on AI Gateway. Both models accept text prompts and reference images for generation and editing. They produce natural lighting and textures, follow detailed visual instructions, handle complex layouts and transparent backgrounds, and make targeted edits while preserving the rest of an image. Choose Flare for faster generation and Sunburst when editing precision matters most. For Flare, use the model ID openai/gpt-image-2.5-flare: For Sunburst, use openai/gpt-image-2.5-sunburst. Pass a reference image with the instruction: Try Flare or Sunburst in the model playground, or view all image models available on AI Gateway. Read more ## Building an Infinite Loom: Unravelling Images into Threads with Three.js DevFeed: [Building an Infinite Loom: Unravelling Images into Threads with Three.js]() Original publisher: [Read original article]() Author: Clément Grellier Published: 2026-09-05T12:50:25Z Content type: tutorial Language: en Sources: [Codrops]() Topics: [Web Development]() Tags: [creative-coding](), [creative-web-experiments](), [digital-art](), [frontend-animation](), [generative-art](), [glsl-shaders](), [gsap](), [html](), [image-animation](), [image-distortion](), [image-effects](), [image-slider](), [images](), [infinite-slider](), [interactive-images](), [interactive-web-design](), [javascript-animation](), [marquee](), [playground](), [ribbon-animation](), [shader-effects](), [shaders](), [thread-animation](), [three-js](), [three-js-demo](), [three-js-shaders](), [unraveling-effect](), [webgl](), [webgl-animation](), [webgl-demo]() ### AI overview A Three.js tutorial for an infinite image strip whose cards are split into independently animated horizontal ribbons. It explains how separate geometry and shaders create weaving, unraveling, gaps, fading, and varied thread motion. ### Source excerpt An experimental Three.js demo that transforms images into flowing ribbons, weaving them together and unraveling them as they move across the screen. ## The Pelican comparison grid for Astra is pretty interesting DevFeed: [The Pelican comparison grid for Astra is pretty interesting]() Original publisher: [Read original article]() Author: Simon Willison Published: 2026-09-04T23:59:05Z Content type: opinion Language: en Sources: [Simon Willison]() Topics: [gpt-6-astra]() Tags: [ai](), [ai-2-235](), [comparison](), [cost](), [generative-ai](), [generative-ai-1-981](), [gpt-6-astra](), [gpt-6-astra-9](), [images](), [llms](), [llms-1-947](), [model](), [openai](), [openai-463](), [pelican-riding-a-bicycle](), [pelican-riding-a-bicycle-142](), [reasoning]() ### AI overview The article compares GPT-6 Astra with GPT-5.6 Sol, Terra, and Luna by generating SVG pelicans riding bicycles at different reasoning levels. The author finds Astra's images generally better, while noting that lower reasoning levels can omit pelican legs and that Astra may cost more but use fewer tokens. ### Source excerpt I got access to GPT-6 Astra this afternoon, so naturally I used it to generate SVGs of pelicans riding bicycles - at low, medium, high, xhigh and max reasoning levels (Astra doesn't support reasoning=none). Then I rendered those pelicans in a comparison grid with GPT-5.6 Sol, Terra, and Luna, and beyond being fun the result was surprisingly useful. See the grid for full quality images. Here's the transcript that created the GPT-6 Nova pelicans. There are a few interesting things that stand out from this grid. The Astra pelicans are much better. The very best GPT-5.6-Sol pelican (I liked xhigh better than max) is still pretty clearly a bunch of abstract shapes. Every single one of the Astra pelicans, from low to xhigh, looks better than that. The Astra max one is really good. Astra below max still doesn't reliably get the pelican legs on both sides of the frame. In terms of cost, Astra may be around twice the price of Sol ($10/million input, $50/million output, compared to $5/$30 for Sol), but it uses significantly less tokens at each of the levels, making the prices at the different levels closer than they might otherwise be. Astra low produces a better pelican than ANY of the GPT-5.6 Sol models at any level, for 9.55 cents. Spending 10 cents on any other model gets a much worse result. Look at the input token counts: Astra and Luna both used 16 input tokens, Sol and Terra used 26. That's interesting. I wonder if Astra and Luna are more related to each other than OpenAI let on? You are only seeing the long-form articles from my blog. Subscribe to /atom/everything/ to get all of my posts, or take a look at my other subscription options. ## Rootless Jailbreak Detection: Updating the Signals, Not the Claim DevFeed: [Rootless Jailbreak Detection: Updating the Signals, Not the Claim]() Original publisher: [Read original article]() Author: Shai Almog Published: 2026-09-01T00:00:00Z Content type: release Language: en Sources: [CodeName One]() Topics: [Jailbreak](), [integrity](), [iOS](), [Filesystems](), [mount](), [Processes]() Tags: [filesystem](), [images](), [integrity](), [ios](), [jailbreak](), [mount](), [process]() ### AI overview Codename One updated its iOS integrity checks to detect current rootless jailbreak layouts. The changes cross-check potentially hooked APIs, inspect mounts and loaded images, and rerun detection when the application returns to the foreground. ### Source excerpt Codename One's iOS integrity checks now detect current rootless jailbreak layouts, cross-check hooked APIs, inspect mounts and loaded images, and rerun on foreground entry. ## Secure by default is your only way forward DevFeed: [Secure by default is your only way forward]() Original publisher: [Read original article]() Author: Vishrut Iyengar Published: 2026-08-31T13:00:00Z Content type: opinion Language: en Sources: [Docker]() Topics: [AI-assisted coding]() Tags: [agents](), [code](), [community](), [enterprise](), [images](), [products](), [security](), [solutions](), [supply-chain]() ### AI overview The article argues that AI coding agents amplify existing software supply-chain risks because they build and ship code using unexamined dependencies. It advocates a hardened, minimal, source-built foundation with accountable security practices. ### Source excerpt The newest worker on your team builds with whatever it finds and never asks what deserves your trust. Our answer is a hardened foundation and a boundary built for agents. ## Announcing Chainguard container images for Go 1.27 DevFeed: [Announcing Chainguard container images for Go 1.27]() Original publisher: [Read original article]() Published: 2026-08-31T00:00:00Z Content type: news Language: en Sources: [Chainguard: Unchained]() Topics: [container images](), [Go Language](), [Cryptography](), [Deployment](), [Security, Privacy and Abuse Prevention](), [Post-Quantum]() Tags: [chainguard](), [container](), [container-images](), [cryptography](), [deployment](), [fedramp](), [fedramp-ato](), [fips](), [go](), [hardening](), [images](), [post-quantum](), [release]() ### AI overview Chainguard announces three Go 1.27 container images: go, go-fips, and go-openssl-fips. The options differ in their FIPS-validated cryptography, including whether cryptography is built in or selected at deployment time. ### Source excerpt Chainguard simplifies Go 1.27 with three images and a new option to choose FIPS-validated cryptography at deployment without recompiling. ## Introducing ReactOS 0.4.16 DevFeed: [Introducing ReactOS 0.4.16]() Original publisher: [Read original article]() Published: 2026-08-29T00:00:00Z Content type: release Language: en Sources: [Front Page on ReactOS Website]() Topics: [ReactOS](), [boot](), [Disk image](), [Graphics](), [OpenGL](), [Nvidia]() Tags: [boot](), [free](), [graphics](), [images](), [installation](), [networking](), [nvidia](), [open-source](), [opengl](), [os](), [react](), [reactos](), [release](), [storage](), [win32](), [winapi]() ### AI overview ReactOS 0.4.16 is announced after a year and a half of development. The release adds a graphical installer, combines the bootcd and livecd images, and includes improvements to video, audio, networking, storage, installation, and third-party code synchronization. ### Source excerpt We are pleased to announce the release of ReactOS 0.4.16! After a year and a half of development, we're excited to showcase the improvements we've made between a new graphical installer; a unified bootcd and livecd image; video, audio, networking, and storage stack improvements; a new installation type; and third-party code syncs. ## Luce: Relightable Gaussians for 3D Asset Generation DevFeed: [Luce: Relightable Gaussians for 3D Asset Generation]() Original publisher: [Read original article]() Published: 2026-08-26T00:00:00Z Content type: article Language: en Sources: [Apple Machine Learning Research]() Topics: [Artificial Intelligence](), [Benchmark]() Tags: [3d](), [ai](), [benchmark](), [computer-vision](), [generation](), [images](), [mesh](), [models](), [multimodal](), [techniques](), [vision]() ### AI overview Luce is a multimodal 3D representation for generating relightable assets from a single image. It combines geometry with physically based materials in a voxelized Gaussian cloud, compresses them into a material-aware latent space, and generates relightable PBR Gaussians and optional textured meshes. On Toys4K, it reports a 28% FID improvement over the strongest baseline and improves alignment on an AI-generated image benchmark. ### Source excerpt High-fidelity image-to-3D generation requires a 3D representation that captures both geometry and appearance. To support relighting and integration into standard rendering pipelines, the representation should include physically based rendering (PBR) modalities such as albedo, metallic-roughness, and surface normals. We propose Luce, a 3D representation that unifies geometry and PBR materials within a voxelized multimodal Gaussian cloud, using dedicated Gaussian primitives for each modality. A variational autoencoder compresses this representation into a unified material-aware latent space. A... ## GLM 5.3 Flash now available on AI Gateway DevFeed: [GLM 5.3 Flash now available on AI Gateway]() Original publisher: [Read original article]() Author: Jerilyn Zheng Published: 2026-08-26T00:00:00Z Content type: news Language: en Sources: [Vercel News]() Topics: [AI Chat]() Tags: [agent](), [ai](), [ai-gateway](), [coding](), [flash](), [images](), [language-models](), [model](), [multimodal](), [playground](), [streaming](), [vercel]() ### AI overview GLM 5.3 Flash from Z.ai is now available through AI Gateway. The multimodal coding model supports text and image inputs, function calling, structured output, streaming, and a 1M-token context window. ### Source excerpt GLM 5.3 Flash from Z.ai is now available on AI Gateway as zai/glm-5.3-flash. GLM 5.3 Flash is a multimodal coding model with a 1M-token context window. It accepts both text and image inputs and supports function calling, structured output, and streaming. To include images, pass them with text in a message. A request can include multiple images using URLs, Base64 data URLs, or binary data: To use GLM 5.3 Flash with a coding agent, run vercel ai-gateway coding-agents setup, then select zai/glm-5.3-flash as your agent's model. Try GLM 5.3 Flash in the model playground, or browse all language models. Read more ## 6 Best WordPress Plugins for Improving Website Accessibility in 2026 DevFeed: [6 Best WordPress Plugins for Improving Website Accessibility in 2026]() Original publisher: [Read original article]() Author: Eric Karkovack Published: 2026-08-25T17:09:45Z Content type: article Language: en Sources: [Speckyboy Design Magazine]() Topics: [Accessibility](), [WordPress themes and plugins](), [WordPress](), [alt text](), [Artificial Intelligence]() Tags: [accessibility](), [ai](), [alt-text](), [best-practices](), [content](), [features](), [images](), [learn](), [media](), [post](), [tools](), [web-accessibility](), [wordpress](), [wordpress-plugins]() ### AI overview A guide to six WordPress plugins that can help identify and improve website accessibility issues, including missing attributes, skip links, labels, contrast, and image descriptions. The article notes that automated results require manual verification. ### Source excerpt We have a fantastic collection of WordPress plugins and tools to help you overcome the challenges that come along with website accessibility. The post 6 Best WordPress Plugins for Improving Website Accessibility in 2026 appeared first on Speckyboy Design Magazine. ## jetc.dev Newsletter Issue #328 DevFeed: [jetc.dev Newsletter Issue #328]() Original publisher: [Read original article]() Author: CommonsWare Published: 2026-08-25T14:00:00Z Content type: article Language: en Sources: [jetc.dev | Issues]() Topics: [Jetpack Compose](), [modules](), [API]() Tags: [api](), [batching](), [exceptions](), [images](), [jetpack-compose](), [modules](), [newsletter](), [published](), [videos]() ### AI overview Newsletter Issue #328 covers Jetpack Compose development topics, including API modules and composables, lazy-container lifecycle exceptions, recomposition and state-change batching, and selecting and copying text from images and videos. ### Source excerpt API modules and composables! LazyColumn() exceptions! 'Select and copy text' for images and videos! ## Best WordPress Hosts for Designers & Creatives in 2026 DevFeed: [Best WordPress Hosts for Designers & Creatives in 2026]() Original publisher: [Read original article]() Author: Paul Andrew Published: 2026-08-22T11:45:43Z Content type: comparison Language: en Sources: [Speckyboy Design Magazine]() Topics: [WordPress](), [WordPress Hosting](), [hosting](), [cloud-infrastructure]() Tags: [animation](), [collaboration](), [cost](), [design](), [images](), [performance](), [storage](), [support](), [themes](), [web-design](), [web-hosting](), [wordpress](), [wordpress-hosting]() ### AI overview A comparison of WordPress hosting options for designers, photographers, illustrators, freelancers, studios, and creative agencies. It evaluates performance, media handling, storage, themes and plugins, staging, backups, collaboration, client management, support, and cost, with recommendations for different website and workflow needs. ### Source excerpt Compare the best WordPress hosts for designers and creatives, with options for portfolios, client websites, visual content, and agency work. The post Best WordPress Hosts for Designers & Creatives in 2026 appeared first on Speckyboy Design Magazine. ## AI-Generated Images Can Perform as Well as Stock Photography DevFeed: [AI-Generated Images Can Perform as Well as Stock Photography]() Original publisher: [Read original article]() Author: Rachel Banawa Published: 2026-08-21T17:00:00Z Content type: article Language: en Sources: [NN/g latest articles and announcements]() Topics: [Artificial Intelligence](), [.NET MAUI]() Tags: [ai](), [analysis](), [article](), [collaboration](), [images](), [photography](), [statistical-significance](), [teamwork]() ### AI overview AI-generated hero images did not produce a meaningful perception penalty compared with real stock photography in a study of 77 participants evaluating fictional consulting-firm webpages. Ratings were slightly higher for AI imagery, but only the small authenticity difference reached statistical significance. ### Source excerpt When users didn't know whether an image was AI-generated, the images we tested did not create any perception penalty compared to stock photos. ## Manage Vercel Container Registry with Vercel CLI DevFeed: [Manage Vercel Container Registry with Vercel CLI]() Original publisher: [Read original article]() Author: Andy Waller Published: 2026-08-20T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Vercel](), [Command-line interface](), [Docker](), [Tooling]() Tags: [buildah](), [cli](), [container-registry](), [docker](), [images](), [podman](), [registry](), [vercel]() ### AI overview Vercel CLI now provides a vcr command group for managing Vercel Container Registry. Developers can connect existing container tools, authenticate with a short-lived project-scoped token, build and push images, create repositories, and inspect repositories, images, and tags. ### Source excerpt You can now manage Vercel Container Registry with Vercel CLI. The new vercel vcr command group lets you: Connect your existing container tooling Build and push images in one step Create and inspect repositories, images, and tags Authenticate your container tooling, such as Docker, Podman, or Buildah, with a short-lived token scoped to your project. Then build and push: The credentials go to Docker itself, so your existing tooling can push to VCR with standard commands: Repositories are created automatically the first time you push, or explicitly with vercel vcr add. From there, you can list what's stored and inspect individual images and tags: Update to the latest Vercel CLI with pnpm i -g vercel@latest and read the Container Registry docs to get started. Read more ## How Clario technology detects PHI/PII in DICOM images using Amazon Bedrock DevFeed: [How Clario technology detects PHI/PII in DICOM images using Amazon Bedrock]() Original publisher: [Read original article]() Author: Alex Boudreau Published: 2026-08-19T14:29:31Z Content type: article Language: en Sources: [AWS Architecture Blog]() Topics: [Amazon Bedrock](), [Medical imaging](), [Amazon Textract](), [Amazon Web Services](), [data]() Tags: [amazon](), [amazon-bedrock](), [amazon-textract](), [analysis](), [architecture](), [aws](), [customer-solutions](), [data](), [healthcare](), [images](), [medical-imaging](), [pii](), [technology](), [workflow]() ### AI overview Clario uses Amazon Bedrock and Amazon Textract to automate the detection of PHI and PII in DICOM image slices from clinical trials, including information stored in metadata and text embedded in image pixels. ### Source excerpt Clario, part of Thermo Fisher Scientific, uses Amazon Bedrock and Amazon Textract to automatically detect protected health information (PHI) and personally identifiable information (PII) across thousands of DICOM image slices in clinical trials, covering both metadata tags and text burned into the image pixels. ## Hands-on with Raspberry Pi's CM5 Programming Jig DevFeed: [Hands-on with Raspberry Pi's CM5 Programming Jig]() Original publisher: [Read original article]() Author: jeff@jeffgeerling.com (Jeff Geerling) Published: 2026-08-19T07:13:00Z Content type: article Language: en Sources: [Jeff Geerling]() Topics: [Provisioning](), [Programming](), [Open Source](), [Python]() Tags: [cm5](), [compute-module](), [demo](), [flash](), [images](), [management-tools](), [open-source](), [programming-jig](), [python](), [raspberry-pi](), [raspberry-pi-os](), [testing](), [tools](), [video](), [youtube]() ### AI overview Hands-on evaluation of Raspberry Pi's CM5 Programming Jig for provisioning and flashing Raspberry Pi OS onto multiple Compute Modules. The article covers its workflow, setup, web interface, imaging tools, pricing, and comparison with Everypin's CM5 Flash Jig. ### Source excerpt In the before-times, when Raspberry Pi CM5s were (relatively) affordable, I built a number of Pi clusters (example), and one of the most annoying parts of the build was flashing Raspberry Pi OS to all the Pis. One, two, or even three Pis isn't a big deal, but once you hit 4+, the process of plugging the Compute Module into a carrier board, plugging that into a computer, managing Raspberry Pi Imager, and trying to match up details like a hostname, MAC address, and the physical Pi itself, gets annoying. ## When AI art has no author: Study finds generated images often can't be traced to training data DevFeed: [When AI art has no author: Study finds generated images often can't be traced to training data]() Original publisher: [Read original article]() Author: Rachel Gordon | MIT CSAIL Published: 2026-08-18T16:35:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [Artificial Intelligence](), [AI Research](), [datasets](), [Computer Science and Artificial Intelligence Laboratory (CSAIL)]() Tags: [ablation](), [ai](), [ai-and-copyright-law](), [ai-generated-images](), [ai-governance](), [artificial-intelligence](), [arts](), [arts-technology-and-society](), [attribution-decay](), [causal-inference](), [computer-science-and-artificial-intelligence-laboratory-csail](), [computer-science-and-technology](), [counterfactual-analysis](), [counterfactual-radius](), [data](), [data-attribution](), [datasets](), [david-gifford](), [diffusion-ensembles](), [electrical-engineering-and-computer-science-eecs](), [ethics](), [generative-ai-images](), [generative-diffusion-models](), [image-similarity-metrics](), [images](), [law](), [machine-learning](), [machine-unlearning](), [mit-csail](), [mit-schwarzman-college-of-computing](), [model](), [model-interpretability](), [paper](), [privacy-preserving-machine-learning](), [research](), [school-of-engineering](), [science](), [technology-and-policy](), [technology-and-society](), [training-data-attribution](), [training-data-influence](), [zheng-dai]() ### AI overview MIT CSAIL researchers describe attribution decay, a phenomenon in which the influence of individual training examples on a generative model's outputs diminishes as datasets grow. Their method removes training examples and retrains models to test whether generated samples change. ### Source excerpt A new method for surgically removing training examples from a model reveals that as datasets grow, the link between what a model learns and what it produces dissolves. [Next page]()