Author: Awais

An analysis from Discover tracking tool DiscoverSnoop adds to the post-update data available on Google’s Discover core update, confirming some patterns identified in earlier NewzDash analysis while contradicting others. The DiscoverSnoop report compared article counts and audience scores for publishers in the week before the update began (January 26 to February 1) against the week after it completed (March 2 to March 8). That post-completion window differs from NewzDash’s earlier scorecard, which measured a mid-rollout window. For transparency, DiscoverSnoop is a commercial Discover analytics platform. The report is based on its own tracking data. Who Lost Visibility Some publishers lost…

[Submitted on 12 Feb 2026 (v1), last revised 12 Mar 2026 (this version, v2)] View a PDF of the paper titled Evolving Beyond Snapshots: Harmonizing Structure and Sequence via Entity State Tuning for Temporal Knowledge Graph Forecasting, by Siyuan Li and Yunjia Wu and 7 other authors View PDF HTML (experimental) Abstract:Temporal knowledge graph (TKG) forecasting requires predicting future facts by jointly modeling structural dependencies within each snapshot and temporal evolution across snapshots. However, most existing methods are stateless: they recompute entity representations at each timestamp from a limited query window, leading to episodic amnesia and rapid decay of long-term…

You’re building a Zap. A lead comes in through a form and needs to go to your CRM. The email has extra spaces. The name is in all caps. A phone number is buried in a text block.The data needs to be cleaned before it hits your CRM. The question is: where should that transformation live?Until now, the answer was usually to add a Formatter step. Formatter is powerful—great for complex transformations and advanced logic. But for quick, in-field adjustments, adding a full step can be more than you need.Today, we’re introducing a complementary option.Inline Formulas let you handle lightweight…

Outside of the festive season, I’m not usually hand-washing much glassware, but I do clean my knives nearly every day. And let me tell you, this special sponge happens to fit perfectly around sharp blades too. It glides seamlessly along both sides of a knife (or kitchen shears) at once, neither tearing, snagging, nor slipping along the way. Once I realized it worked so well on my santoku (decidedly not a wine glass), nothing was safe. The Mitt left my little glass prep bowls, mini tongs, jiggers, measuring spoons, and thermometer probes sparkling clean. Honestly, the more I used it,…

, I’d like to share a practical variation of Uber’s Two-Tower Embedding (TTE) approach for cases where both user-related data and computing resources are limited. The problem came from a high-traffic discovery widget on the home screen of a food delivery app. This widget shows curated selections such as Italian, Burgers, Sushi, or Healthy. The selections are created from tags: each restaurant can have multiple tags, and each tile is essentially a tag-defined slice of the catalog (with the addition of some manual picking). In other words, the candidate set is already known, so the real problem is not retrieval…

A recent Harvard Business Review piece echoes the shift we’re sseeing in the SEO industry: at a macro level, LLMs and Google’s AI-powered SERP features, such as AI Overviews, aren’t just creating a zero-click environment, but also changing user journeys and behavior. They’re collapsing what used to be multi-touch customer journeys into a single synthesized answer. For a more visual and emphatic metaphor, the monolith of “Search” is crumbling. When that happens, brands lose many of the touchpoints they once owned, and your marketing strategy must change accordingly. HBR captures this moment well, arguing that marketing now has a new…

arXiv:2603.12249v1 Announce Type: cross Abstract: Constructing scientific multimodal document reasoning datasets for foundation model training involves an inherent trade-off among scale, faithfulness, and realism. To address this challenge, we introduce the synthesize-and-reground framework, a two-stage pipeline comprising: (1) Claim-Centric QA Synthesis, which generates faithful, isolated QA pairs and reasoning on focused segments, and (2) Document-Scale Regrounding, which programmatically re-embeds these pairs into full-document tasks to ensure realistic complexity. Using this framework, we construct SciMDR, a large-scale training dataset for cross-modal comprehension, comprising 300K QA pairs with explicit reasoning chains across 20K scientific papers. We further construct SciMDR-Eval, an expert-annotated benchmark…

We recently started a small project to clean up how parts of our systems communicate behind the scenes at Buffer.Some quick context: we use something called SQS (Amazon Simple Queue Service. These queues act like waiting rooms for tasks. One part of our system drops off a message, and another picks it up later. Think of it like leaving a note for a coworker: “Hey, when you get a chance, process this data.” The system that sends the note doesn’t have to wait around for a response.Our project was to perform routine maintenance: update the tools we use to test…

, also known as RAG, is a powerful method to find relevant documents in a corpus of information, which you then provide to an LLM to give answers to user questions. Traditionally, RAG first uses vector similarity to find relevant chunks of documents in the corpus and then feeds the most relevant chunks into the LLM to provide a response. This works really well in a lot of scenarios since semantic similarity is a powerful way to find the most relevant chunks. However, semantic similarity struggles in some scenarios, for example, when a user inputs specific keywords or IDs that…

Google redesigned the Asset Optimization section in Google Ads for Demand Gen campaigns, consolidating AI-powered creative controls into a single, cleaner interface. Why we care. Advertisers managing creative at scale now have a centralized panel to toggle automated features on or off — making the process less manual and time consuming. What’s new. The redesigned layout groups three key automation capabilities together: Auto-generated shorter videos — AI trims existing video assets into shorter cuts to qualify for additional placements. Automatic video resizing — Videos are adapted across multiple aspect ratios to maximize inventory coverage. Landing page image pulls — Images…