# Ads Published articles for Ads. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Atomic macOS (AMOS) Stealer Activity DevFeed: [Atomic macOS (AMOS) Stealer Activity]() Original publisher: [Read original article]() Author: Bradley Duncan Published: 2026-09-16T10:00:06Z Content type: article Language: en Sources: [Unit 42]() Topics: [Malware](), [Aeternum](), [macOS](), [sensitive data](), [Zsh](), [ClickFix](), [cURL]() Tags: [ads](), [clickfix](), [credentials](), [cryptocurrency](), [curl](), [general](), [insights](), [macos](), [malware](), [sensitive-data](), [threat-intelligence](), [unit-42](), [zsh]() ### AI overview This article analyzes a laboratory-generated Atomic macOS (AMOS) stealer infection observed on Aug. 5, 2026. It describes a deceptive macOS toolkit installation page that led users to paste a command into Terminal, retrieving a Zsh script containing an encoded compressed payload and a follow-up script designed to run a Mach-O binary. AMOS targets macOS and can exfiltrate system information, login credentials, and sensitive data from applications including browsers and cryptocurrency wallets. ### Source excerpt Modern macOS malware uses deceptive setup guides to steal credentials and sensitive user data. Learn how to identify and block these threats. The post Atomic macOS (AMOS) Stealer Activity appeared first on Unit 42. ## StreamRat Android malware spreads through Meta and TikTok ads DevFeed: [StreamRat Android malware spreads through Meta and TikTok ads]() Original publisher: [Read original article]() Author: Pieter Arntz Published: 2026-09-03T16:04:24Z Content type: news Language: en Sources: [Malwarebytes]() Topics: [StreamRAT](), [Malware](), [Social engineering](), [passwords]() Tags: [ads](), [advertising](), [android](), [browser](), [malware](), [meta](), [news](), [passwords](), [scam](), [security](), [social-media](), [streaming](), [streamrat](), [threat-intel](), [tiktok]() ### AI overview A malicious ad campaign used fake streaming-service promotions on Meta and TikTok to distribute the StreamRat Android banking Trojan. The campaign directed Android users to a tailored download page that coached them past security warnings and enabled credential theft and remote device control. ### Source excerpt Social media ads for a free streaming service exposed roughly 570,000 people to StreamRat, a banking Trojan that can take control of infected phones. ## Pi-hole vs AdGuard Home vs Technitium: which DNS ad-blocker to run DevFeed: [Pi-hole vs AdGuard Home vs Technitium: which DNS ad-blocker to run]() Original publisher: [Read original article]() Author: Shed Stack Published: 2026-09-02T18:00:00Z Content type: comparison Language: en Sources: [Shed Stack]() Topics: [Pi-hole](), [Homelab](), [DNSSEC](), [Go Language]() Tags: [ads](), [comparison](), [dns](), [dnssec](), [features](), [go](), [homelab](), [self-hosted]() ### AI overview Practical comparison of Pi-hole, AdGuard Home, and Technitium as self-hosted DNS ad-blockers. Pi-hole emphasizes its mature blocklist ecosystem, AdGuard Home offers a broader built-in feature set and modern interface, and Technitium provides a full DNS server with blocking capabilities for users who want greater control over DNS. ### Source excerpt A practical breakdown of the three self-hosted DNS ad-blockers, from a homelab that actually ran all of them. ## A milestone in expanding access to AI DevFeed: [A milestone in expanding access to AI]() Original publisher: [Read original article]() Published: 2026-08-31T04:00:00Z Content type: article Language: en Sources: [OpenAI News]() Topics: [Artificial Intelligence](), [ChatGPT](), [OpenAI]() Tags: [ads](), [advertising](), [ai](), [chatgpt](), [global](), [openai](), [product](), [revenue]() ### AI overview ChatGPT Ads has reached a $1 billion annualized revenue run rate in less than 200 days and is expanding globally. OpenAI says advertising supports a diversified business model and helps sustain an advertising-supported free tier, while ads remain labeled separately from answers and users retain control over personalization. ### Source excerpt ChatGPT Ads reaches $1 billion in annualized revenue run rate and expands globally, supporting broader access to AI through free and affordable options. ## ChatGPT Ads expands across Europe DevFeed: [ChatGPT Ads expands across Europe]() Original publisher: [Read original article]() Published: 2026-08-18T22:00:00Z Content type: news Language: en Sources: [OpenAI News]() Topics: [ChatGPT](), [OpenAI](), [personalization]() Tags: [ads](), [advertising](), [business](), [chatgpt](), [cost](), [customer](), [enterprise](), [europe](), [norway](), [openai](), [personalization](), [platform](), [product](), [subscriptions]() ### AI overview ChatGPT Ads is expanding to 31 European markets, with access initially provided through OpenAI's ads team and partners and self-service access now available through Ads Manager. Ads appear only for Free and Go users, while paid plans remain ad-free. OpenAI says ads are labeled, separate from answers, and designed to preserve conversation privacy and user control over personalization. ### Source excerpt ChatGPT Ads is expanding to 31 European markets. Learn how advertisers can reach people as they explore, compare options, and make decisions. ## One line of Python, and a 3x drop in p99 DevFeed: [One line of Python, and a 3x drop in p99]() Original publisher: [Read original article]() Published: 2026-08-11T00:00:00Z Content type: article Language: en Sources: [SoundCloud Backstage Blog]() Topics: [Latency](), [Back end](), [bug](), [cpu](), [API](), [Python](), [Code]() Tags: [ads](), [api](), [backend](), [bug](), [code](), [cpu](), [engineering](), [latency](), [logging](), [measurement](), [monitoring](), [performance](), [python]() ### AI overview The article describes removing one log statement from a service's hot path, which substantially reduced 99th-percentile response latency and CPU usage. The service supports ad-serving decisions through an internal API, and the investigation found that validation warnings and metric increments were being emitted for expected requests from fixed-policy callers that supplied no Bayesian posterior state. ### Source excerpt We removed one log statement from a service's hot path this week. Its 99th-percentile response latency fell from a steady to , and CPU... ## TIME serves bots a different website, and User-Agent is now a billing identity DevFeed: [TIME serves bots a different website, and User-Agent is now a billing identity]() Original publisher: [Read original article]() Author: WorkOS Published: 2026-08-06T01:46:28Z Content type: opinion Language: en Sources: [WorkOS Blog]() Topics: [AI Bots](), [Bot](), [Crawler](), [SIEM, Security, Observability]() Tags: [ads](), [billing](), [bots](), [curl](), [logs](), [measurement](), [openai](), [routing]() ### AI overview The article examines how TIME serves different content to crawlers based on User-Agent headers and records bot reads as billable ad impressions. It argues that because clients can freely change the header, crawler identity is an unreliable basis for billing and measurement. ### Source excerpt TIME forks its content per crawler and logs each bot read as a billable ad impression. The routing key for that whole ledger is a header any client can type. ## From User Sequences to Scaling Laws: A Multi-Stage Architecture for Meta's Ads Ranking DevFeed: [From User Sequences to Scaling Laws: A Multi-Stage Architecture for Meta's Ads Ranking]() Original publisher: [Read original article]() Author: Steven De Gryze; Parshva Doshi; Sean O'Byrne; Arnold Overwijk; Dinesh Ramasamy; Lee Xiong Published: 2026-08-05T19:20:20Z Content type: article Language: en Sources: [Engineering at Meta](), [Meta ML Applications]() Topics: [recommendation systems](), [Temporal data]() Tags: [ads](), [architecture](), [data-infrastructure](), [meta](), [ml-applications](), [production-engineering](), [recommendation-systems](), [scaling-laws](), [tokenization]() ### AI overview Meta describes a multi-stage sequence-model architecture for ads ranking that separates offline user modeling from lightweight online ranking. It also uses dense tokenization and target-aware attention to learn feature interactions, with reported conversion and ad-click lifts across Instagram and Facebook. ### Source excerpt Every day, Meta's recommendation platforms handle billions of user interactions, generating rich temporal signals that capture individual preferences and intent across products, ads, and content. In our 2024 post on sequence learning for ads recommendations, we showed how modeling the order and timing of user actions (rather than relying on static, manually engineered sparse features) [...] Read More... The post From User Sequences to Scaling Laws: A Multi-Stage Architecture for Meta's Ads Ranking appeared first on Engineering at Meta. ## GEM Training: How Meta Doubled the Efficiency of Its LLM-Scale Ads Foundation Model DevFeed: [GEM Training: How Meta Doubled the Efficiency of Its LLM-Scale Ads Foundation Model]() Original publisher: [Read original article]() Author: Darren Liu; Huayu Li; Raghav Boinepalli; Yuzhen Huang; Jackie (Jiaqi) Xu; Richard Qiu; Chunzhi Yang; Rich Zhu; Dev (Devashish) Shankar; Huaqing Xiong Published: 2026-08-03T18:00:17Z Content type: article Language: en Sources: [Engineering at Meta](), [Meta AI Research](), [Meta ML Applications]() Topics: [recommendation systems](), [networking]() Tags: [ads](), [ai-infrastructure](), [ai-research](), [data-infrastructure](), [gpu](), [hardware](), [kernels](), [llm](), [meta](), [ml-applications](), [networking](), [recommendation-systems](), [training]() ### AI overview Meta describes training its GEM ads recommendation foundation model at LLM scale. The article covers recommendation-specific kernels, ultra-low-precision training, and topology-aware parallelism that doubled end-to-end training efficiency to 20-25% MFU while increasing training FLOPs fourfold. ### Source excerpt Meta's Generative Ads Recommendation Model (GEM), the foundation model behind ads recommendations across Instagram and Facebook, now trains at LLM scale on several thousand of the latest-generation GPUs. This post goes into the details on how we achieved: doubling end-to-end (E2E) training efficiency to 20-25% Model FLOPs Utilization (MFU) while scaling training FLOPs 4x in [...] Read More... The post GEM Training: How Meta Doubled the Efficiency of Its LLM-Scale Ads Foundation Model appeared first on Engineering at Meta. ## Introducing Graph API v26.0 and Marketing API v26.0 DevFeed: [Introducing Graph API v26.0 and Marketing API v26.0]() Original publisher: [Read original article]() Published: 2026-07-29T17:00:36Z Content type: release Language: en Sources: [Facebook Developers]() Topics: [API](), [changelog]() Tags: [ads](), [api](), [changelog](), [checkout](), [deprecated](), [errors](), [facebook](), [instagram](), [whatsapp]() ### AI overview Graph API v26.0 and Marketing API v26.0 introduce new capabilities, deprecations, and breaking changes. The article highlights WhatsApp Status ad capabilities, removal of deprecated delivery estimate fields, and deprecation of Commerce Order Management API endpoints for the sunset Facebook and Instagram Shops checkout experience. ### Source excerpt Graph API v26.0 and Marketing API v26.0 include new capabilities, deprecations, and breaking changes. Review the highlights below and visit the V26.0 changelog for the complete list of changes and details. ## Why I Stopped Using Pi-Hole on My Network DevFeed: [Why I Stopped Using Pi-Hole on My Network]() Original publisher: [Read original article]() Author: Patrick Fromaget Published: 2026-07-29T05:00:00Z Content type: opinion Language: en Sources: [RaspberryTips]() Topics: [Pi-hole](), [Network](), [browser]() Tags: [ads](), [analytics](), [network](), [quick-tips](), [raspberry-pi](), [server](), [tool](), [tutorial]() ### AI overview The author explains why they stopped using Pi-hole on their home network. Although it blocks ads across devices by filtering DNS, it interferes with website development and creates troubleshooting overhead; the article argues that popular projects should be chosen according to personal needs rather than popularity. ### Source excerpt Pi-Hole, with Retropie or Magic Mirror, is one of those projects that somehow always makes it to the "best Raspberry Pi projects" lists. If you have a Raspberry Pi, it's hard not to know about it. So obviously, I'm a big fan and using it myself at home, right? Well, not so fast... Setting up... ## Meta's ads MCP server is now available for developers DevFeed: [Meta's ads MCP server is now available for developers]() Original publisher: [Read original article]() Published: 2026-07-16T17:45:00Z Content type: release Language: en Sources: [Facebook Developers]() Topics: [MCP Server](), [Meta](), [MCP](), [Artificial Intelligence]() Tags: [ads](), [advertising](), [ai](), [developers](), [mcp](), [mcp-server](), [meta](), [performance]() ### AI overview Meta has opened its ads MCP server to developers with their own Meta app. AI applications can use it to create and optimize advertising campaigns, retrieve performance insights, and manage product catalogs through natural language. ### Source excerpt You can now connect your AI application directly to Meta's advertising capabilities, enabling your users to create and optimize campaigns, pull performance insights, manage product catalogs, and more through natural language. ## Exploring Hierarchical Interest Representation For Meta Ads Deep Funnel Optimization DevFeed: [Exploring Hierarchical Interest Representation For Meta Ads Deep Funnel Optimization]() Original publisher: [Read original article]() Author: Yuhui Ouyang; Di Wang; Sreedal Menon; Jie Tian Published: 2026-07-15T17:00:52Z Content type: article Language: en Sources: [Engineering at Meta](), [Meta AI Research]() Topics: [Optimization](), [Embeddings](), [Graphs](), [recommendation systems](), [LLMs](), [Artificial Intelligence](), [Transformer](), [data]() Tags: [ads](), [ai](), [ai-research](), [data](), [embeddings](), [engineering](), [frontier-ai](), [generative](), [learning](), [meta](), [optimization](), [personalization](), [reasoning](), [research](), [retrieval](), [scale]() ### AI overview Meta describes Hierarchical Interest Representation, an upstream system that learns unified embeddings for users, advertisers, products, and services. It combines graph learning, multimodal content processed through LLMs, engagement signals, and self-supervised distillation to improve personalization, retrieval, ranking, and deep-funnel advertising optimization. ### Source excerpt Hierarchical Interest Representation is a research area for Meta Ads. We're exploring an upstream representation layer over the universe of Ads entities - users, advertisers, products, services - learning unified embeddings that connect users' inferred interests with the breadth of what advertisers offer in their deep funnel ads. The innovations in Hierarchical Interest Representation are [...] Read More... The post Exploring Hierarchical Interest Representation For Meta Ads Deep Funnel Optimization appeared first on Engineering at Meta. ## Block Everything You Hate Online with AdGuard Home DevFeed: [Block Everything You Hate Online with AdGuard Home]() Original publisher: [Read original article]() Author: Jeremy Published: 2026-06-25T19:47:00Z Content type: article Language: en Sources: [Noted]() Topics: [Network](), [dashboards](), [hosting](), [browser](), [Streaming]() Tags: [ads](), [browser](), [browsers](), [devices](), [dns](), [extensions](), [gaming](), [hosting](), [internet](), [malware](), [real-time](), [self-hosted-web-tools](), [self-hosting](), [server](), [servers](), [streaming](), [youtube]() ### AI overview AdGuard Home is a self-hosted, network-wide blocker for ads, trackers, malware domains, and adult content. It applies custom filtering rules across phones, tablets, smart TVs, laptops, apps, games, and streaming services, with a web dashboard for management and real-time visibility. ### Source excerpt Self-host AdGuard Home or use their public DNS to block ads, trackers, and adult content across all your devices with ease. ## Introducing Ads CLI DevFeed: [Introducing Ads CLI]() Original publisher: [Read original article]() Published: 2026-04-29T21:55:46Z Content type: release Language: en Sources: [Facebook Developers]() Topics: [Command-line interface](), [Meta](), [API](), [Artificial Intelligence](), [Python]() Tags: [ads](), [agents](), [ai-agents](), [api](), [ci-cd](), [cli](), [command-line](), [json](), [meta](), [python]() ### AI overview Meta introduces an ads CLI that lets developers and AI agents manage campaigns, catalogs, products, and conversion tracking through the command line. It supports multiple output formats, unattended CI/CD use, standard exit codes, and environment variables for sensitive values. ### Source excerpt Today we're introducing the Meta ads CLI, a command-line tool for developers to manage Meta ad campaigns. Developers and AI agents working with the Meta Marketing API can now create, edit, and analyze campaigns directly from the command line, without writing custom code. ## Operation "Date Bait": AI-enabled scam targeting loveseekers DevFeed: [Operation "Date Bait": AI-enabled scam targeting loveseekers]() Original publisher: [Read original article]() Published: 2026-02-01T00:00:00Z Content type: news Language: en Sources: [OpenAI News]() Topics: [Artificial Intelligence](), [OpenAI](), [ChatGPT](), [Automation](), [API]() Tags: [ads](), [ai](), [api](), [automation](), [chatgpt](), [engagement](), [openai](), [safety](), [scam](), [social-media](), [structured](), [tasks](), [telegram](), [translation](), [trust]() ### AI overview OpenAI describes Operation "Date Bait," in which accounts likely originating in Cambodia used ChatGPT and API access for a semi-automated romance and task scam targeting Indonesian men. The operation used translated and emotionally manipulative outreach across advertisements, an AI chatbot, Telegram, and dating platforms. ### Source excerpt OpenAI banned accounts that very likely originated in Cambodia and used AI for scam outreach to Indonesian loveseekers, including translation and engagement. ## Our approach to advertising and expanding access to ChatGPT DevFeed: [Our approach to advertising and expanding access to ChatGPT]() Original publisher: [Read original article]() Published: 2026-01-16T00:00:00Z Content type: article Language: en Sources: [OpenAI News]() Topics: [ChatGPT](), [Artificial Intelligence](), [OpenAI](), [personalization](), [User Experience]() Tags: [ads](), [advertising](), [ai](), [chatgpt](), [company](), [openai](), [personalization](), [privacy](), [subscriptions](), [user-experience]() ### AI overview OpenAI announces the expansion of ChatGPT Go to the U.S. and all locations where ChatGPT is available, alongside plans to test ads for free and Go users. The article outlines commitments to answer independence, conversation privacy, user control, personalization choices, and an ad-free paid option. ### Source excerpt OpenAI plans to test advertising in the U.S. for ChatGPT's free and Go tiers to expand affordable access to AI worldwide, while protecting privacy, trust, and answer quality. ## How we're bringing AI image verification to the Gemini app DevFeed: [How we're bringing AI image verification to the Gemini app]() Original publisher: [Read original article]() Author: Pushmeet Kohli Published: 2025-11-20T15:13:19Z Content type: news Language: en Sources: [Google DeepMind News]() Topics: [Google AI](), [AI Chat]() Tags: [ads](), [ai](), [app](), [audio](), [content](), [ecosystem](), [embedded](), [feature](), [gemini](), [generative](), [google](), [google-ai](), [images](), [launch](), [media](), [none](), [partners](), [product](), [products](), [reasoning](), [research]() ### AI overview Google is adding Gemini app image verification that checks SynthID watermarks to indicate whether an image was created or edited with Google AI. The company also plans broader support for video, audio, C2PA metadata, and additional Google products. ### Source excerpt Our new Gemini app feature allows you to verify Google AI images and determine whether content was created or edited by AI. ## Three new features to help build brand momentum with Figma Buzz DevFeed: [Three new features to help build brand momentum with Figma Buzz]() Original publisher: [Read original article]() Author: Jasmine Stoy Published: 2025-10-23T00:00:00Z Content type: article Language: en Sources: [Figma Blog]() Topics: [Figma](), [Template](), [Code]() Tags: [ads](), [animation](), [asset-management](), [customization](), [design](), [design-systems](), [event](), [features](), [figma](), [linkedin](), [marketing](), [plugins](), [product-development](), [promotion](), [social-media](), [tools](), [video]() ### AI overview Figma Buzz introduces three features for creating branded marketing assets: configurable templates connected to design systems, plugins for tasks such as digital asset management and translation, and direct video trimming. ### Source excerpt With marketing templates that are now connected to your design system, plugins that pull in your favorite apps, and video trimming in Figma Buzz, we're giving designers and marketers new tools to create branded assets that speak volumes. ## How Changan Ford cut costs by 40% and powered precision marketing with ClickHouse Enterprise Edition DevFeed: [How Changan Ford cut costs by 40% and powered precision marketing with ClickHouse Enterprise Edition]() Original publisher: [Read original article]() Author: ClickHouse Published: 2025-09-22T00:00:00Z Content type: article Language: en Sources: [ClickHouse Blog]() Topics: [data](), [dashboards]() Tags: [ads](), [analytics](), [apache-flink](), [architecture](), [clickhouse](), [cloud](), [customer](), [dashboards](), [data](), [enterprise](), [errors](), [open-source](), [performance](), [platform](), [real-time](), [serverless](), [spark](), [storage]() ### AI overview Changan Ford migrated its customer data platform from ClickHouse Community Edition to ClickHouse Enterprise Edition on Alibaba Cloud. The company reports a 40% cost reduction, lower operational workload, and improved stability for high-demand marketing campaigns. ### Source excerpt Changan Ford migrated their Customer Data Platform to ClickHouse Enterprise Edition, cut costs by 40%, eased the operational workload, and gave the team stability and confidence even during their most demanding campaigns. ## Why Switch to Firefox: Open Source, Ad Blocking, and Android Extensions DevFeed: [Why Switch to Firefox: Open Source, Ad Blocking, and Android Extensions]() Original publisher: [Read original article]() Author: Kaushik Gopal Published: 2025-07-18T00:00:00Z Content type: opinion Language: en Sources: [Kaushik Gopal's Site]() Topics: [Firefox](), [uBlock Origin Filters](), [Chrome](), [firefox for android](), [Firefox extension](), [Open Source]() Tags: [ads](), [android](), [blocking](), [chrome](), [extensions](), [firefox](), [open-source]() ### AI overview An opinionated guide encouraging readers to switch to Firefox, citing its open-source code, support for uBlock Origin, synchronization on Android, and mobile browser extensions. ### Source excerpt Chrome finally pulled the trigger on the web's best ad-blocker, uBlock Origin. Now that Chrome has hobbled uBO, Firefox -- my beloved --1 is surging again. I want to do my part to convince you to switch to Firefox and show you how I use it. Why Firefox # Let's get through the important talking points, in case you need a quick copy paste to convince a friend. 100% open-source Un-enshittify the web Android users rejoice Customize to your heart's content 100% open-source ## This section can be quick. Here's a github link to the source code of the Firefox browser. You can clone the repo, pop open your favorite AI code assistant and start asking questions about your browser - the most important app you use. What libraries does their Android app use? libs.versions.toml boom! Also 8.11.1 on android gradle plugin? not bad Firefox. Their license allows you to fork and distribute alternative versions. Vibe code a whole new browser. Un-enshittify the web ## Most of the web today is enshittified with a cesspool of ads, popups, cookie notices, and tracking scripts. Our primary defense has been ad-blockers, with the most powerful being uBlock Origin. uBO relies on community-curated filter lists that play a cat-and-mouse game to zap known ads, trackers, and other digital sludge. But with Chrome controlling the web, Google followed through on its promise to kneecap uBO with Manifest V3, effectively blocking the full version from its extension store. Sure, there's uBlock Origin "Lite" now, which does the same thing, right? Nope: uBlock Origin Lite != uBlock Origin Filter lists update only when the extension updates no fetching up to date lists from servers (this is a big one!) No custom filters so no element picker which allows you to point and zap Many filters are dropped at conversion time due to MV3's limited filter syntax No strict-blocked pages No per-site switches No dynamic filtering No importing external lists Did you know, uBlock Origin works best on Firefox. Why not just use ## Integrating Xandr's Real-Time Data Provider On-Premises: Infrastructure Requirements and Engineering Challenges DevFeed: [Integrating Xandr's Real-Time Data Provider On-Premises: Infrastructure Requirements and Engineering Challenges]() Original publisher: [Read original article]() Author: Guy Watson Published: 2025-04-22T22:57:37Z Content type: article Language: en Sources: [GumGum]() Topics: [real-time](), [Requirements](), [on-prem](), [Latency](), [Low Latency](), [Hardware](), [data](), [digital]() Tags: [ads](), [advertising](), [challenges](), [clients](), [data-processing](), [decision-making](), [hardware](), [infrastructure](), [latency](), [low-latency](), [metric](), [on-prem](), [performance](), [platform](), [real-time]() ### AI overview The article describes GumGum's experience integrating Xandr's Real-Time Data Provider on-premises, focusing on infrastructure requirements, scaling challenges, latency, traffic volume, and the decision to own hardware. ### Source excerpt How We Slashed Our Infrastructure Costs by 80% While Successfully Integrating Xandr's Real-Time Ad Platform!Introduction In the fast-paced world of digital advertising, maximizing return on investment (ROI) for ad spend is paramount. Buyers need to make data-driven decisions in real time to ensure their ads reach the right audience at the right moment. For us, integrating Xandr's Real-Time Data Provider (RTDP) was essential to providing the real-time optimization signals that would help our clients maximize their ROI by boosting Attention Time -- the key metric driving the effectiveness of programmatic ad campaigns. Our story is one of navigating through technical hurdles, experimenting with new infrastructure, and finding creative solutions to challenging engineering problems. As we embarked on integrating Xandr Real Time Data Provider, the path was far from straightforward. From vendor selection to scaling issues, and even the decision to own our hardware, every step had its complications. Yet, each obstacle presented an opportunity for innovation and refinement. In this article, we'll take you through the key challenges we faced, how we overcame them, and the lessons we learned from integrating Xandr on-prem. Whether you're considering a similar project or are simply curious about the behind-the-scenes of large-scale advertising tech deployments, our experience might just offer the insights you need. Xandr Integration and Its Requirements Xandr, a leading programmatic advertising platform, provides powerful tools to streamline and optimize ad delivery, targeting, and performance tracking. For us, integrating with Xandr RTDP meant integrating with the real time optimisation Xandr platform. Xandr's system, built to handle vast amounts of data in real time, comes with certain infrastructure demands. These include: Volume: The platform must be capable of handling massive amounts of traffic at any given time. For example, billions of ad impressions are processed daily, ## My journey from Disqus to Remark42 DevFeed: [My journey from Disqus to Remark42]() Original publisher: [Read original article]() Author: andreacorbellini Published: 2023-09-05T08:30:00Z Content type: opinion Language: en Sources: [Andrea Corbellini]() Topics: [Website](), [data](), [WordPress]() Tags: [ads](), [articles](), [blog](), [blog-post](), [change](), [data](), [privacy](), [third-party](), [website](), [wordpress]() ### AI overview The author explains replacing Disqus with Remark42 on a static blog after discovering that Disqus displayed unwanted ads and raised concerns about tracking, data collection, and possible third-party data sharing. ### Source excerpt Readers of this blog might have noticed a few changes recently. For example, I've been working on improving the look of the blog (maybe with questionable results), as well as improving the experience on mobile. But one of the biggest changes that perhaps some have noticed is that all of the comments on all of my articles have suddenly disappeared since February 2023 ... ## Maximize Revenue with Remote Config Personalization DevFeed: [Maximize Revenue with Remote Config Personalization]() Original publisher: [Read original article]() Author: Dana Silver Published: 2023-04-11T00:00:00Z Content type: tutorial Language: en Sources: [Firebase Blog]() Topics: [personalization](), [Firebase](), [Google Analytics](), [App](), [Machine learning]() Tags: [admob](), [ads](), [analytics](), [app](), [firebase](), [google-analytics](), [how-to](), [personalization](), [remote-config](), [revenue](), [tutorials]() ### AI overview This tutorial explains how Firebase Remote Config personalization uses Google Analytics events and parameter values to tailor app experiences and optimize objectives such as purchases, ad impressions, revenue, and return ad spend. It also demonstrates configuring ad frequency through the Firebase Console. ### Source excerpt News, tutorials, and updates from the Firebase team. [Next page]()