# generate Published articles for generate. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Quiz: How to Get Started With Ollama DevFeed: [Quiz: How to Get Started With Ollama]() Original publisher: [Read original article]() Author: Real Python Published: 2026-09-15T12:00:00Z Content type: tutorial Language: en Sources: [Real Python]() Topics: [Ollama](), [Python](), [Code](), [Hardware]() Tags: [chat](), [generate](), [hardware](), [how-to](), [install](), [internet](), [local](), [models](), [ollama](), [python](), [running]() ### AI overview An interactive 10-question quiz tests understanding of installing Ollama, pulling local models, and calling chat and generate functions from Python. It also covers multi-turn conversations, local hardware, and data privacy. ### Source excerpt Check your understanding of installing Ollama, pulling local models, and calling the chat and generate functions from your Python code. ## Figma Is Turning Designers Into Plugin Makers DevFeed: [Figma Is Turning Designers Into Plugin Makers]() Original publisher: [Read original article]() Author: Alex Harper Published: 2026-09-14T15:30:00Z Content type: article Language: en Sources: [Web Designer Depot]() Topics: [Figma](), [Figma plugin](), [Artificial Intelligence](), [shaders](), [shader programming](), [Programming]() Tags: [ai](), [ai-design-tools](), [ai-for-designers](), [ai-plugins](), [artificial-intelligence](), [creative-software](), [design-automation](), [design-tools](), [figma](), [figma-agent](), [figma-ai](), [figma-community](), [figma-plugin](), [figma-plugins](), [figma-shaders](), [future-of-design](), [generate](), [generative-ai](), [generative-plugins](), [no-code-tools](), [procedural](), [shader-programming](), [shaders](), [ui-design](), [ux-design](), [web-design](), [web-development]() ### AI overview Figma is enabling designers to describe and generate coded plugins with AI instead of searching for existing tools. The article explains that these plugins can solve highly specific workflow problems, be published to the Figma Community or shared privately, and include features such as bulk restyling, type-ramp generation, layer renaming, and prototype-flow checking. Figma also offers AI-generated shaders for procedural and interactive visual effects, with code inspection available for shaders and self-created generative plugins. ### Source excerpt Figma is turning a wild idea into reality: instead of searching for the perfect plugin, you can just ask AI to build it. If this catches on, designers may stop choosing the tools in their software--and start inventing them on demand. ## 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. ## What part of 'No!' is so hard for the DNS understand? DevFeed: [What part of 'No!' is so hard for the DNS understand?]() Original publisher: [Read original article]() Author: Geoff Huston Published: 2026-09-04T01:06:30Z Content type: article Language: en Sources: [APNIC Blog]() Topics: [servers](), [Caching](), [DDoS](), [Cybercrime](), [Availability](), [Bot](), [Script]() Tags: [apnic-labs](), [attacks](), [availability](), [bots](), [caching](), [ddos](), [dns](), [generate](), [measurement](), [random](), [server](), [servers](), [tech-matters]() ### AI overview The article explains how random name attacks overwhelm authoritative DNS servers by generating queries for nonexistent names, bypassing recursive resolver caches and potentially causing domain availability failures. It also describes APNIC Labs' measurement work on nonexistent-domain responses to improve DNS resilience. ### Source excerpt At APNIC Labs we've been experimenting with understanding how the DNS handles requests to resolve nonexistent names to make the DNS more resilient to random name attacks. ## Bullshit Management Didn't Die. It Got Automated. DevFeed: [Bullshit Management Didn't Die. It Got Automated.]() Original publisher: [Read original article]() Author: David Pereira Published: 2026-09-03T12:27:11Z Content type: opinion Language: en Sources: [Untrapping Product Teams]() Topics: [Product Management](), [Requirements](), [Artificial Intelligence](), [Large Language Model](), [User Stories]() Tags: [2026](), [generate](), [llms](), [product-management](), [requirements](), [user-stories]() ### AI overview The author revisits the concept of "bullshit management" and argues that practices such as gathering requirements, maintaining extensive backlogs, and producing management reports have persisted while AI has automated or amplified parts of them. The supplied text presents this as an opinion-based critique, emphasizing that polished outputs may conceal limited customer understanding and learning. ### Source excerpt Four years ago I named it. A million reads later, it's back with better tools. ## MiniMax H3 and H3 Max are 50% off on AI Gateway DevFeed: [MiniMax H3 and H3 Max are 50% off on AI Gateway]() Original publisher: [Read original article]() Author: Jerilyn Zheng Published: 2026-08-30T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Artificial Intelligence](), [API](), [API keys](), [dashboards](), [browser]() Tags: [ai](), [ai-gateway](), [api](), [audio](), [browser](), [generate](), [generation](), [image](), [model](), [models](), [pricing]() ### AI overview MiniMax H3 and H3 Max receive a 50% discount on Vercel AI Gateway from August 30 through September 13. H3 supports 2K video generation from text, images, video, and audio inputs, while H3 Max offers faster 480p and 768p rendering from text or a starting image. Existing model IDs remain unchanged, so no code changes are required. ### Source excerpt MiniMax H3 and H3 Max are 50% off on AI Gateway from August 30 through September 13, in partnership with MiniMax. The discount covers requests billed through AI Gateway, at every duration and in every aspect ratio the model supports. H3 generates 2K video from a text prompt, a starting image, a pair of first and last frames, or reference images, video, and audio. H3 Max trades resolution for speed: it renders faster at 480p and 768p, and it takes a text prompt or a starting image. The model IDs (minimax/minimax-h3 and minimax/minimax-h3-max) are unchanged, so requests you already send pick up the discounted rate with no code change: Renders take minutes, so poll runs the generation as a background job and makes short status requests until it lands, rather than holding one long request open. See asynchronous generation for the webhook and start-and-status routes. Get started Create an API key in the AI Gateway section of your dashboard, or generate a clip in the browser first from the model playground. Current rates for every model are on the pricing page. You can view all video models available on AI Gateway. Read more ## Better answers, broader thinking: What students gain from ChatGPT and critical-thinking training DevFeed: [Better answers, broader thinking: What students gain from ChatGPT and critical-thinking training]() Original publisher: [Read original article]() Published: 2026-08-27T09:00:00Z Content type: article Language: en Sources: [OpenAI News]() Topics: [ChatGPT](), [Artificial Intelligence](), [OpenAI]() Tags: [ai](), [analysis](), [business](), [chatgpt](), [company](), [experiment](), [generate](), [gpt](), [marketing](), [openai](), [performance](), [reasoning](), [research](), [training]() ### AI overview Un randomized experiment with more than 1,000 first-year undergraduate students found that ChatGPT access improved the quality, coherence, logic, and professionalism of work on a real-world business assignment. Separate causal-reasoning training increased the originality and variety of ideas, and students receiving both interventions showed both benefits. ### Source excerpt A randomized study of more than 1,000 students examines ChatGPT, critical thinking, originality, and student performance on a real-world university assignment. ## PROOF-Gen: From Optimized Data to Better Distillation DevFeed: [PROOF-Gen: From Optimized Data to Better Distillation]() Original publisher: [Read original article]() Published: 2026-08-26T00:00:00Z Content type: article Language: en Sources: [Apple Machine Learning Research]() Topics: [Fine-tuning](), [Prompt optimization](), [Artificial Intelligence](), [gemma4](), [Programming]() Tags: [agent](), [ai-agents](), [evaluation](), [fine-tuning](), [gemma](), [generate](), [models](), [on-device](), [post-training](), [prompt-optimization]() ### AI overview PROOF-Gen improves tool-calling model distillation by using per-scenario prompt optimization to recover successful trajectories from failed teacher attempts. The method strips corrective guidance before training, producing clean demonstrations and improving benchmark, deployed-pipeline, and on-device model performance. ### Source excerpt Supervised fine-tuning on teacher-generated trajectories is the standard first stage for distilling tool-calling capabilities into deployable models. Post-training pipelines that drive shipped tool-calling agents re-run this stage on a daily or weekly cadence, paying the frontier-teacher cost each cycle, yet the mechanism is generate-and-filter (keep the teacher's passing trajectories, discard the rest) and each cycle leaves behind the same hard scenarios because failures supply no signal. On τ 2-bench, 57% of teacher trials fail, two-thirds of them near-misses (most tool calls correct, undone... ## Using an AI Agent to Convert STL Meshes into Editable CAD DevFeed: [Using an AI Agent to Convert STL Meshes into Editable CAD]() Original publisher: [Read original article]() Author: Shy Ruparel Published: 2026-08-18T00:00:00Z Content type: article Language: en Sources: [Temporal Blog]() Topics: [AI Agent](), [stl](), [3D](), [audit trail](), [retry]() Tags: [3d](), [agent](), [ai-agent](), [audit-trail](), [generate](), [model](), [retry](), [stl](), [temporal-voices]() ### AI overview The article describes using an AI agent to convert triangulated STL meshes into editable CAD and explains why validation mattered more than an autonomous agentic loop. Temporal provided durable execution, retries, progress preservation, and an audit trail, but did not improve the agent's geometric judgment. ### Source excerpt Shy Ruparel tried an AI agent to turn STL files into editable CAD. What worked was less glamorous: generate candidates, measure them, and validate. ## SecretSpec 0.19: Moving and importing secrets between providers DevFeed: [SecretSpec 0.19: Moving and importing secrets between providers]() Original publisher: [Read original article]() Author: domenkozar Published: 2026-08-11T23:15:09Z Content type: release Language: en Sources: [Announcements - NixOS Discourse]() Topics: [configuration](), [Self-hosted](), [servers]() Tags: [announcements](), [config](), [generate](), [json](), [moving](), [providers](), [release](), [secrets](), [self-hosted](), [servers](), [verify]() ### AI overview SecretSpec 0.19 introduces provider-specific secret storage layouts, safer imports with verification before deletion, value transformations, configuration stored alongside secrets, ephemeral values and runtime prompts, Passbolt support, and faster remote-provider operations. ### Source excerpt Hey all, secretspec 0.19 is out with highlights: Provider-specific storage layouts: map one application variable to each provider's native item, field, vault, or path. Safer imports: preflight every source and destination, verify copied values, and only then delete the source. Value transforms: decode Base64 or hexadecimal values and extract fields from JSON documents. Config in secrets: resolve committed, profile-specific configuration alongside provider-backed secrets. Ephemeral values and runtime prompts: generate or securely request values that should exist for only one invocation. Passbolt support: read and write secrets in self-hosted Passbolt servers. Faster remote providers: attach local caches directly to authoritative providers and batch 1Password field reads. Read the full release post: SecretSpec 0.19: Moving and importing secrets between providers | SecretSpec Disclaimer: LLMs have been used 1 post - 1 participant Read full topic ## How to proxy OpenAI image generation on Webflow Cloud without exposing your API key DevFeed: [How to proxy OpenAI image generation on Webflow Cloud without exposing your API key]() Original publisher: [Read original article]() Author: Ismail Ajagbe Published: 2026-08-08T00:00:00Z Content type: tutorial Language: en Sources: [Webflow Blog]() Topics: [API keys](), [OpenAI](), [webflow](), [Artificial Intelligence](), [API](), [Cloudflare Workers](), [Workers](), [Next.js]() Tags: [ai](), [api](), [cli](), [cloudflare-workers](), [deployment](), [generate](), [guide](), [guides](), [how-to](), [images](), [next-js](), [openai](), [validation](), [webflow]() ### AI overview This guide explains how to build and deploy an AI image generator on Webflow Cloud using OpenAI. It uses a Next.js Route Handler on Cloudflare Workers as a server-side proxy so the OpenAI API key remains private while the browser submits prompts and receives generated images. ### Source excerpt Learn how to build an AI image generator on Webflow Cloud using OpenAI. ## Seedance 2.5 now available on Vercel AI Gateway DevFeed: [Seedance 2.5 now available on Vercel AI Gateway]() Original publisher: [Read original article]() Author: Jerilyn Zheng Published: 2026-08-06T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Vercel](), [Artificial Intelligence](), [vercel ai sdk](), [SDKs](), [API]() Tags: [ai](), [ai-gateway](), [api](), [audio](), [generate](), [image](), [model](), [sdk](), [vercel](), [video]() ### AI overview Vercel AI Gateway now offers ByteDance's Seedance 2.5 video model. The model generates clips up to 30 seconds with synchronized audio, supports up to 50 multimodal reference inputs, can extend short clips, and can edit videos while preserving framing, camera movement, and pacing. The article also documents video generation, image and video references, and video editing through the AI SDK. ### Source excerpt Seedance 2.5 from ByteDance is now available on AI Gateway. It can generate up to 30-second clips with synchronized audio, and takes up to 50 reference inputs in one request, spanning images, video, audio, and style. A single clip holds camera movement and continuity without stitching shots together in post, and short clips can be extended, carrying over character, scene, and camera movement. Prompts work in more than ten languages. Seedance 2.5 can also edit a finished video in place, swapping backgrounds, products, or characters while the frame, camera, and pacing stay fixed, so one shoot yields several variants. Generating a video Set model to bytedance/seedance-2.5 and call generateVideo from the AI SDK: Adding image references Pass image URLs in inputReferences and point at them in the prompt with [Image 1], [Image 2]. Tag each entry with its media type. Seedance treats an untagged URL as an image. Combining reference types Mix videos and images in the same request to pull different qualities from each: motion and camera work from a clip, a subject's appearance from a still. Videos go in the same inputReferences array as images, tagged with a video media type. Numbering runs per type so the first video is [Video 1] and the first image is [Image 1], and both can appear in one prompt. Editing a video Referencing and editing use the same setup, so the prompt decides which you get. Ask the model to follow a clip's camera movement and it builds a new video from scratch. Ask it to change something in the clip and it edits the video you gave it. You can reference and edit in one prompt, though results get less predictable, so it helps to be explicit about what each asset is for. For the playground and API reference, see the model page, or browse every video model on AI Gateway. Read more ## Generate Trajectories, Reasoning Traces, and Auto-Labels with NVIDIA Alpamayo 2 Super DevFeed: [Generate Trajectories, Reasoning Traces, and Auto-Labels with NVIDIA Alpamayo 2 Super]() Original publisher: [Read original article]() Author: Elizabeth Goodman Published: 2026-08-04T15:00:00Z Content type: tutorial Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [foundation-models](), [Cosmos](), [model-deployment](), [Reinforcement learning](), [Inference](), [GitHub](), [hugging face](), [Open Source Models & Datasets]() Tags: [accelerate](), [automotive-transportation](), [autonomous](), [benchmarks](), [cosmos](), [customization](), [data](), [developer-tools-techniques](), [developers](), [development](), [diffusion](), [drive](), [driving](), [evaluation](), [featured](), [fine-tuning](), [generate](), [generation](), [github](), [hugging-face](), [inference](), [learning](), [models](), [nvidia](), [reasoning](), [robot-navigation](), [robotics](), [simulation-modeling-design](), [top-stories]() ### AI overview NVIDIA Alpamayo 2 Super is an open 34-billion-parameter reasoning vision-language-action model for autonomous vehicle development. It combines NVIDIA Cosmos 3 Super Reasoner with a diffusion-based Action Expert to generate trajectories, reasoning traces, meta-actions, scene answers, and auto-labels across development workflows. ### Source excerpt Autonomous vehicle (AV) development often relies on separate models for trajectory generation, high-level intent prediction, scene understanding, and data... ## ESP-IDF tutorial series: PWM DevFeed: [ESP-IDF tutorial series: PWM]() Original publisher: [Read original article]() Author: John Lee Published: 2026-08-03T00:00:00Z Content type: tutorial Language: en Sources: [Blog on Developer Portal]() Topics: [ESP-IDF](), [Tutorial](), [Espressif](), [configuration]() Tags: [article](), [blog](), [channel](), [configuration](), [conversion](), [devkit](), [esp-idf](), [espressif](), [generate](), [ledc](), [peripheral](), [pwm](), [signal](), [speed](), [tutorial]() ### AI overview This ESP-IDF tutorial explains pulse-width modulation, including duty cycle, switching frequency, and average voltage. It demonstrates PWM generation with the LEDC peripheral on Espressif devices and describes converting PWM to DC with an RC filter, including ripple and response-speed tradeoffs. ### Source excerpt This article explains what a PWM signal is, and how to generate PWM signal using the ledc peripheral on Espressif devices. It covers the LEDC timer and channel configuration, and shows how to convert a PWM signal into a clean DC value using an RC filter, including the tradeoffs between ripple and response speed. ## We're launching Lyria 3.5 in Google Flow Music, with advances across musicality, lyrics, vocals, and creative control DevFeed: [We're launching Lyria 3.5 in Google Flow Music, with advances across musicality, lyrics, vocals, and creative control]() Original publisher: [Read original article]() Author: Michael Chang Published: 2026-07-29T16:02:10Z Content type: release Language: en Sources: [Google DeepMind News]() Topics: [Google]() Tags: [generate](), [generation](), [google](), [model](), [music](), [none]() ### AI overview Google is launching Lyria 3.5 in Google Flow Music, introducing improvements to musicality, lyrics, vocals, pronunciation, and creative control over tempo and duration. ### Source excerpt Our newest music generation model, Lyria 3.5, delivers significant advancements across musicality, lyrics, and vocal quality, empowering you to craft richer tracks. We'r... ## @clickhouse/rowbinary: when your library is also a parser compiler DevFeed: [@clickhouse/rowbinary: when your library is also a parser compiler]() Original publisher: [Read original article]() Author: Peter Leonov Published: 2026-07-14T20:59:26Z Content type: article Language: en Sources: [ClickHouse Blog]() Topics: [clickhouse](), [Node.js](), [Parser](), [Agent Skill](), [Compiler](), [coding]() Tags: [agent-skill](), [bugs](), [clickhouse](), [coding](), [cost](), [generate](), [javascript](), [node-js]() ### AI overview @clickhouse/rowbinary is a Node.js library for reading and writing ClickHouse RowBinary formats. It also provides an Agent Skill that lets a coding agent generate query-specific parsers from the library's reading primitives, producing faster parsers with less runtime dispatch and reducing risks associated with handwritten binary decoders. ### Source excerpt We've released @clickhouse/rowbinary a Node.js reader and writer for ClickHouse's RowBinary formats. You can import it and call its generic parser like any other library. But it also ships as an Agent Skill: point a coding agent at the bundled `SKILL.md` ## DSLs Enable Reliable Use of LLMs DevFeed: [DSLs Enable Reliable Use of LLMs]() Original publisher: [Read original article]() Author: Martin Fowler (martin@martinfowler.com) Published: 2026-07-14T12:51:00Z Content type: article Language: en Sources: [Martin Fowler]() Topics: [Large Language Model](), [Code](), [Software](), [systems]() Tags: [article](), [code](), [generate](), [llms](), [software](), [source](), [systems]() ### AI overview The article explains how abstractions and Domain-Specific Languages (DSLs) can provide clear boundaries that make LLM-generated code more reliable. Using Tickloom as an example, it presents an LLM as a partner for iteratively developing a DSL and as a natural-language interface to that DSL, which can serve as a source of truth for software systems. ### Source excerpt LLMs generate code incredibly fast, but to ensure they generate exactly what is intended, they need clear boundaries. Abstractions and Domain-Specific Languages (DSLs) provide a strong harness that guides LLMs right from the start. Unmesh Joshi describes how the example of Tickloom - a domain model and DSL for illustrating distributed system behavior - shows how we can use an LLM as a partner to iteratively build a DSL and as a natural language interface to use it. Such a DSL can act as the key source of truth for software systems in the world of LLMs. more... ## 7 of the best AI-powered website builders for 2026 DevFeed: [7 of the best AI-powered website builders for 2026]() Original publisher: [Read original article]() Author: Webflow Team Published: 2026-07-14T00:00:00Z Content type: comparison Language: en Sources: [Webflow Blog]() Topics: [Artificial Intelligence](), [Web](), [web design](), [Content Management System](), [Scalability](), [User Experience](), [hosting]() Tags: [ai](), [design](), [design-patterns](), [digital-experiences](), [features](), [generate](), [guide](), [hosting](), [how-to](), [integrations](), [launch](), [platform](), [scalability](), [user-experience](), [web](), [web-design](), [website-builders]() ### AI overview A comparison of seven AI-powered website builders for 2026, covering ease of use, features, applications, design quality, scalability, content management, hosting, and the role of human review. ### Source excerpt Compare seven of the best AI-powered website builders for 2026. Learn about their ease of use, key features, and applications, then choose the right fit. ## Idempotency Keys in Payment APIs: Prevent Double Charges DevFeed: [Idempotency Keys in Payment APIs: Prevent Double Charges]() Original publisher: [Read original article]() Author: Ayush Agarwal Published: 2026-07-12T00:00:00Z Content type: tutorial Language: en Sources: [Dodo Payments Blog]() Topics: [API](), [SDKs]() Tags: [api](), [apis](), [bugs](), [chargebacks](), [engineering](), [generate](), [how-to](), [learn](), [payment](), [payments](), [scope]() ### AI overview This tutorial explains how idempotency keys prevent duplicate charges in payment APIs by making retries of the same logical operation safe. It covers ambiguous failures, key generation and scope, retry patterns, and implementation details such as time-to-live. ### Source excerpt How idempotency keys stop duplicate charges in payment APIs. Learn what idempotency means, how keys work, retry-safe patterns, key scope and TTL, and how to implement them correctly. ## Introducing Gemini Omni DevFeed: [Introducing Gemini Omni]() Original publisher: [Read original article]() Author: Koray Kavukcuoglu Published: 2026-05-17T19:50:57Z Content type: release Language: en Sources: [Google DeepMind News]() Topics: [AI Chat]() Tags: [audio](), [flash](), [gemini](), [generate](), [google](), [images](), [model](), [multimodal](), [none](), [video](), [youtube]() ### AI overview Gemini Omni is a new multimodal model for generating and conversationally editing videos from image, audio, video, and text inputs. The article announces Gemini Omni Flash for the Gemini app, Google Flow, and YouTube Shorts. ### Source excerpt Introducing Gemini Omni, which allows you to create anything from any input and edit naturally using conversational language. ## Create Vercel Firewall rules with natural language DevFeed: [Create Vercel Firewall rules with natural language]() Original publisher: [Read original article]() Author: Yash Kothari Published: 2026-05-12T19:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Firewall](), [Vercel](), [Command-line interface](), [dashboards](), [Authorization]() Tags: [authorization](), [checkout](), [cli](), [documentation](), [firewall](), [generate](), [ip](), [logging](), [us](), [vercel]() ### AI overview Vercel Firewall now supports creating WAF custom rules from natural-language descriptions. The dashboard or Vercel CLI can generate rules that log, block, challenge, rate limit, or redirect requests based on conditions such as IP address, path, country, and user agent. ### Source excerpt Vercel Firewall now lets you create WAF custom rules using natural language. Describe the behavior you need and the dashboard will generate the rule. Visit the firewall custom rules page to try creating a rate-limiting rule: Or use the Vercel CLI: WAF custom rules let you control traffic to your site by logging, blocking, challenging, rate limiting, or redirecting requests based on conditions like IP address, path, country, user agent, and more. For example, you can: Log all requests to /api/webhook with a missing authorization header Block all requests to /wp-admin Challenge all traffic to /checkout that doesn't come from the US Generate your first rule or learn more in the documentation. Read more ## A tool for generating Google Play feature graphics DevFeed: [A tool for generating Google Play feature graphics]() Original publisher: [Read original article]() Author: Jorge Castillo Published: 2026-05-07T13:41:05Z Content type: release Language: en Sources: [Effective Android]() Topics: [Google Play](), [App](), [Google](), [Publishing]() Tags: [app](), [color](), [feature](), [generate](), [google-play](), [publishing]() ### AI overview The article introduces a tool for generating Google Play feature graphics. Users provide an app name and brief description, then choose a brand color. ### Source excerpt Introducing the fastest way to generate feature graphic for Google Play out there 🔥 ## Four ways Google Research scientists have been using Empirical Research Assistance DevFeed: [Four ways Google Research scientists have been using Empirical Research Assistance]() Original publisher: [Read original article]() Published: 2026-04-29T21:07:00Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Google](), [Artificial Intelligence](), [Data Mining & Modeling](), [datasets](), [Benchmark](), [Monitoring](), [real-time]() Tags: [accelerate](), [ai](), [benchmark](), [data](), [data-mining-modeling](), [experiment](), [general-science](), [generate](), [generative-ai](), [go](), [google](), [insights](), [machine-intelligence](), [monitoring](), [real-time](), [research](), [science](), [software]() ### AI overview Google Research scientists are using Empirical Research Assistance (ERA) to develop expert-level empirical software and explore AI-assisted scientific discovery across epidemiology, geospatial analysis, cosmology, atmospheric monitoring, and neuroscience. The article highlights ERA's use in computational modeling, interpretable solutions, and real-time forecasts for COVID-19, influenza, and RSV. ### Source excerpt Data Mining & Modeling ## Writing with ChatGPT DevFeed: [Writing with ChatGPT]() Original publisher: [Read original article]() Published: 2026-04-10T00:00:00Z Content type: article Language: en Sources: [OpenAI News]() Topics: [ChatGPT](), [Prompt Engineering]() Tags: [chatgpt](), [communication](), [content](), [generate](), [how-to](), [openai-academy](), [prompt-engineering](), [review](), [workflow](), [writing]() ### AI overview Learn how ChatGPT can help draft, revise, and refine workplace writing while preserving clarity, tone, audience awareness, and intent. The article presents a practical Plan -> Draft -> Revise -> Package workflow and emphasizes providing context, constraints, format, and targeted feedback. ### Source excerpt Learn how to use ChatGPT for writing to draft, revise, and refine content with clear structure, tone, and intent. [Next page]()