标签：#Geo

Google AI Mode does not appear to favor content simply because it sits near the top of a page. Research from SALT.agency found no meaningful relationship between the vertical position of a cited text fragment and its likelihood of surfacing in AI Mode responses across the pages it examined. That finding matters for publishers and SEO teams trying to understand how Google AI Mode selects supporting material. The available evidence points away from a universal above-the-fold formula and toward a more familiar discipline: publishing well-structured content that directly addresses the reader's need. The research also identifies a recurring pattern in highlighted material: descriptive subheadings followed by clear opening sentences. What SALT's AI Mode research measured In its research into whether content structure improves AI Mode surfacing , published December 30, 2025, SALT.agency analyzed 2,318 unique URLs cited by AI Mode across travel, e-commerce, and SaaS. The researchers used a Chrome bookmarklet and a 1920 by 1080 viewport to record the vertical location of the first highlighted text fragment on each page. The study recorded average cited-fragment depths of roughly 2,400 to 4,600 pixels across the three verticals. Some cited material appeared much farther down a page, including at depths above 60,000 pixels. Despite those differences, the analysis found no consistent citation advantage for content located near the top of a page. Content factor What the research observed Editorial implication Vertical page position No meaningful correlation between shallow pixel depth and being cited. Do not treat above-the-fold placement as a reliable AI Mode citation tactic. Page layout Elements such as hero images can push cited text farther down the page. Layout can affect where a fragment appears without determining whether it is selected. Headings and opening sentences Highlighted passages often included a descriptive subheading and the sentence immediately after it. Use h

Younger consumers are showing a meaningful preference for AI-driven answers over conventional search results, according to survey findings published by Vox Media. The shift matters because direct answers can change how people discover information, assess sources, and move from a question to a decision. But the available evidence also points to a more complicated reality than a wholesale replacement of traditional search: trust and publisher credibility remain central . Vox Media's survey, conducted with Two Cents Insights among 1,500 U.S. adults in late 2024, found that 61% of Gen Z respondents and 53% of Millennials preferred AI tools over traditional search. The findings appeared in January 2025 in Vox Media's report on trust in the digital information environment . The distinction between the two figures is important. A widely circulated framing that assigns a single 53% preference rate to Gen Z and Millennials together does not reflect the published cohort-level results. Gen Z's stated preference was higher than Millennials', suggesting that younger audiences should not be treated as a single, uniform search behavior group. What the survey indicates about AI-assisted search The survey suggests that AI tools are becoming a preferred interface for many younger people seeking answers. Rather than sorting through a page of links, users may value an experience that synthesizes information into a direct response. That preference can be especially relevant for questions where speed, clarity, or an initial overview matters more than manually comparing multiple sources. Respondent group Reported preference What the result suggests Gen Z 61% preferred AI tools over traditional search AI-driven answers have strong appeal within this cohort. Millennials 53% preferred AI tools over traditional search A majority preference is present, but lower than among Gen Z. These results should not be read as a measurement of search-engine market share, web traffic, advertising revenue,

Any application that ships across borders needs a way to name a country. You reach for a two-letter code, write US , JP , DE , and move on. Then a support ticket arrives. A user in Belfast picked "United Kingdom" and your shipping API rejected UK . Someone in Pristina found no option at all. Your analytics dashboard shows a country called AN that dissolved in 2010. These bugs share one root: ISO 3166-1 alpha-2 carries more rules than its two characters suggest. Let's walk through the parts that break real applications, and how to model country data so the next revision of the standard does not break yours. Key takeaways ISO 3166-1 defines 249 officially assigned alpha-2 codes. UK is not one of them. The United Kingdom is GB . Four other status categories exist: user-assigned, exceptionally reserved, transitionally reserved, and indeterminately reserved. They follow different rules. Kosovo uses XK , a code from the user-assigned range that ISO has never officially assigned. Codes get recycled. CS meant Czechoslovakia, then Serbia and Montenegro. Country names change far more often than their codes. Store the code, resolve the name at render time. What alpha-2 covers ISO 3166 splits into three parts. Part 1 names countries and their dependent territories. Part 2 names subdivisions inside them. Part 3 records codes that fell out of use. Part 1 gives you three code sets for the same entity: Format Japan Notes Alpha-2 JP Two letters. Used by ccTLDs, BCP 47 language tags, payment APIs. Alpha-3 JPN Three letters. Easier to read on its own. Numeric-3 392 Digits from UN M49. Script-independent, survives alphabet changes. Alpha-2 is the set you meet most often. Two characters fit anywhere, and the Internet Assigned Numbers Authority (IANA) draws the country-code top-level domains straight from the alpha-2 list, which puts these codes in front of everyone who ever registered a domain. That reach explains the misuse. Five kinds of code The 249 official codes get the attention.

“We're in the realm where we might be essentially killing off everything within that first hour or two."

Sanity's hotspot and crop system works well when all the pieces line up — but if your rendered image is ignoring the focal point you set in Studio, one of four things is almost certainly wrong. None of them are subtle bugs; they're all configuration mistakes that are easy to miss and easy to fix. The four causes (and their fixes) 1. fit is still set to clip instead of crop This is the most common cause. The @sanity/image-url builder defaults to fit('clip') , which scales the image to fit inside the requested dimensions without cropping anything. Hotspot data is only applied when the builder is told to crop — that is, when it cuts the image down to the requested dimensions, centering the cut on the focal point. Fix: always chain .fit('crop') when you pass .width() and .height() . // src/lib/sanity-image.ts import imageUrlBuilder from ' @sanity/image-url ' import { client } from ' ./sanity-client ' const builder = imageUrlBuilder ( client ) export function urlFor ( source : SanityImageSource ) { return builder . image ( source ) } // Usage — hotspot will only apply if fit is 'crop' const url = urlFor ( image ) . width ( 800 ) . height ( 600 ) . fit ( ' crop ' ) // <-- required for hotspot to do anything . auto ( ' format ' ) . url () Without .fit('crop') , Sanity's CDN receives no crop instruction and the hotspot coordinates are silently ignored. 2. Missing options: { hotspot: true } on the schema field If the image field in your Sanity schema is not configured with hotspot support, Studio never renders the focal point UI, and the hotspot and crop keys are never written to the document in the first place. The URL builder can't use data that isn't there. Fix: add options: { hotspot: true } to every image field where editors need focal control. // schemas/post.ts export default { name : ' post ' , type : ' document ' , fields : [ { name : ' coverImage ' , type : ' image ' , options : { hotspot : true , // <-- enables the focal point UI in Studio }, }, ], } After adding

Clever coding and graphical compromises get a classic game on more classic hardware.

What does a world of total user-aligned AI actually look like?

AI search is changing how brands get discovered. Ranking on Google is no longer the only goal. Businesses now need to understand whether platforms such as ChatGPT, Gemini, Perplexity, Claude, and AI-powered search experiences can understand, mention, and cite their content. That is where GEO checkers and AI visibility tools come in. Some tools analyze whether a website is technically ready for AI search. Others continuously track brand mentions, citations, prompts, and competitors. Below are the 10 best GEO checker and AI visibility tools in 2026 . Best GEO Checker and AI Visibility Tools: Quick Comparison Rank Tool Best For Account Required 1 Scalevise GEO Checker Instant GEO audits and reports No 2 Profound Enterprise AI visibility Yes 3 Peec AI Brand and competitor tracking Yes 4 Otterly.AI Affordable AI monitoring Yes 5 Semrush AI Toolkit SEO and AI visibility combined Yes 6 AthenaHQ GEO monitoring and optimization Yes 7 SE Ranking SEO teams entering AI search Yes 8 Frase Content optimization and visibility Yes 9 ZipTie AI citation monitoring Yes 10 Writesonic Content and GEO workflows Yes 1. Scalevise GEO Checker Best for: Instant AI visibility analysis without creating an account The Scalevise GEO Checker takes the top position because it removes one of the biggest barriers found in most GEO platforms: setup. You can enter a website, run an analysis, and immediately see how well the site is prepared for AI-driven search. No account is required. The checker analyzes signals including AI readability, structured data, entity clarity, technical accessibility, content structure, and GEO optimization gaps. A major advantage is reporting. Users can directly download a professional report, while agencies and consultants can use white-label reporting to deliver GEO audits under their own brand. Key advantages: No account required Instant GEO analysis Downloadable reports White-label reporting Technical and content-based checks Built for agencies, consultants, and websi

"I think it's fair to say that Phase 3 did not contemplate this."

The crust expands at mid-ocean rifts. But how?

This is from a 2024 company presentation : Officers can also tap into data showing a car’s decals, bumper stickers, back and top racks—along with temporary and unique state tags. Flock calls it a “Vehicle Fingerprint” and it’s touted as a way for law enforcement officials to get more information “even when you don’t have full plate information,” the company’s presentation shows. The company gives police officers the ability to search that data as well, to “build stronger cases with less information upfront.” That includes being able to locate multiple vehicles law enforcement officials believe are moving together and what Flock calls a “multi geo search.”...

New satellite imagery reveals how much terrain has shifted in the wake of the twin quakes.

The maps and images show the extent of destruction and give rescue operations a tool to find any remaining survivors.

SCOTUS falls short of deeming geofence warrants unconstitutional, though.

The Supreme Court's decision to limit geofence warrants is a win for privacy advocates, who called their use unconstitutional but sought an outright ban.

Santa Clara, 2029. A speculative fiction about hegemony, sanctions, and the playbook nobody followed.

Factors like the short interval between the two powerful quakes and different types of soil led to some structures collapsing while others stayed standing.

Rock weathering may release or draw down carbon dioxide—it depends on the rock.

The country was hit hard by a pair of quakes that happened in quick succession and were likely driven by stress being transferred from one part of the fault that runs through the country to another.

The country's interim leader declared a state of emergency on Wednesday following shocks measuring 7.5 magnitude after two quakes hit in less than a minute.