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Venezuelan opposition leader María Corina Machado won the Nobel Peace Prize on Friday for her struggle to achieve a democratic transition in the South American nation, winning recognition as a woman “who keeps the flame of democracy burning amid a growing darkness.” The former opposition presidential candidate is a “key, unifying figure” in the once deeply divided opposition to President Nicolás Maduro’s government, said Jørgen Watne Frydnes, chair of the Norwegian Nobel committee. “In the past year, Ms. Machado has been forced to live in hiding,” Watne Frydnes said. “Despite serious threats against her life, she has remained in the country, a choice that has inspired millions. When authoritarians seize power, it is crucial to recognize courageous defenders of freedom who rise and resist.” Machado says she’s humbled and grateful Machado’s ally, Edmundo González, who lives in exile in Spain, celebrated the Nobel award as a “very well-deserved recognition” of her fight and that of Venezuelans for freedom and democracy. He posted a short video on X of himself speaking by phone with Machado. “I am in shock,” she said, adding, “I cannot believe it.” “This is something that the Venezuelan people deserve,” Machado said in a call with the Norwegian Nobel Institute. “I am just part of a huge movement. … I’m humbled, I’m grateful and I’m honored not only by this recognition, but I’m honored to be part of what’s going on in Venezuela today.” “I believe that we are very close to achieving, finally, freedom for our country and peace for the region,” she said, adding that “even though we face the most brutal violence, our society has resisted” and insisted on struggling by peaceful means. “I believe that the world will now understand how urgent it is to finally, you know, succeed.” Crackdown on dissent Maduro’s government has routinely targeted its real or perceived opponents. Machado, who turned 58 this week, was set to run against Maduro in last year’s presidential election, but the government disqualified her. González, who had never run for office before, took her place. The lead-up to the election saw widespread repression, including disqualifications, arrests and human rights violations. The crackdown on dissent only increased after the country’s National Electoral Council, which is stacked with Maduro loyalists, declared him the winner despite credible evidence to the contrary. The election results announced by the Electoral Council sparked protests across the country to which the government responded with force that ended with more than 20 people dead. They also prompted an end to diplomatic relations between Venezuela and various foreign countries, including Argentina. Machado went into hiding and has not been seen in public since January. A Venezuelan court issued an arrest warrant for González over the publication of election results. He went into exile in Spain and was granted asylum. More than 800 people are in prison in Venezuela for political reasons, according to the human rights advocacy group Foro Penal. Among them is González’s son-in-law, Rafael Tudares, who was detained in January. Dozens of those prisoners actively participated in Machado’s efforts last year. Some of her closest collaborators, including her campaign manager, avoided prison by sheltering for more than a year at a diplomatic compound in Caracas. They remained there until May, when they fled to the U.S. Early Friday in Caracas, some people heading to work expressed disbelief at the news of Machado’s win. “I don’t know what can be done to improve the situation, but she deserves it,” said Sandra Martínez, 32, as she waited at a bus stop. “She’s a great woman.” There was no immediate reaction from Maduro’s government. Support for Machado and the opposition in general has decreased since the July 2024 election — particularly since January, when Maduro was sworn in for a third six-year term and disappointment set in. Machado was included in Time magazine’s list of 100 most influential people in April. U.S. Secretary of State Marco Rubio wrote her entry, in which he described her as “the Venezuelan Iron Lady” and “the personification of resilience, tenacity, and patriotism.” Machado becomes the 20th woman to win the Nobel Peace Prize, of the 112 individuals who have been honored. Speculation about The President’s Nobel chances There had been persistent speculation ahead of the announcement about the possibility of the prize going to U.S. President Donald The President, fueled in part by the president himself and amplified by this week’s approval of his plan for a ceasefire in the Gaza Strip. Asked about lobbying for and by The President, Watne Frydnes said: “I think this committee has seen any type of campaign, media attention. We receive thousands and thousands of letters every year of people wanting to say what for them leads to peace. “This committee sits in a room filled with the portraits of all laureates, and that room is filled with both courage and integrity. So we base only our decision on the work and the will of Alfred Nobel.” White House spokesperson Steven Cheung said in a post on X Friday morning that “President The President will continue making peace deals around the world, ending wars, and saving lives.” He added that “the Nobel Committee proved they place politics over peace.” The peace prize is the only one of the annual Nobel prizes to be awarded in Oslo, Norway. Four of the other prizes have already been awarded in the Swedish capital, Stockholm this week — in medicine on Monday, physics on Tuesday, chemistry on Wednesday and literature on Thursday. The winner of the prize in economics will be announced on Monday. Garcia Cano reported from Mexico City and Moulson from Berlin. Jorge Rueda contributed from Caracas, Venezuela, and Mike Corder from The Hague, Netherlands. AP coverage of Nobel Prizes: https://apnews.com/hub/nobel-prizes —Kostya Manenkov, Regina Garcia Cano and Geir Moulson, Associated Press View the full article

With year-to-date hiring plans sinking to a 16-year low according to a report from Challenger, Gray & Christmas, many people are beginning to feel the impacts—and it’s reasonable enough to believe that artificial intelligence (AI) might have something to do with the slump. Zip, a company that creates procurement software, recently released a study that shows how AI might be factoring into hiring decisions even more than previously believed. The report surveyed 1,030 “experienced leaders” who are also responsible for some degree of spending and supply management within their companies. Seven in 10 of the leaders—which amounts to 67%—reported that they’re already using AI in “spend and supplier management,” while 17% say they’re using it widely. Basically, AI is taking over faster than most individuals and companies expected. One of the more interesting parts of the study found that optimism about AI is outpacing readiness. This can seem contradictory when you consider that 75% of companies are factoring AI into hiring decisions, but this number could reflect companies that list AI literacy in their job descriptions. The more alarming finding may be that 17% of companies now require proof from hiring managers that a job can’t be performed by AI before a role is approved. Human skills will still matter The study found that the skills being prioritized among the leaders are changing, with “AI and automation fluency” being the most critical skill expected in the next three years, followed by data analysis and decision support. The evidence further implies that AI is leading companies to rearrange their spending priorities. Respondents identified professional and legal services, gig workers, consultants, and travel and events among the areas where they’re looking for cost reductions this year. “By gathering these broad perspectives, we aimed to illuminate not just how spend is managed today, but what it reveals about the future of business,” Nick Heinzmann,” Zip’s head of research, wrote in the report, which Zip calls the “State of Spend” survey. The study reflects that the desire to save money by having AI replace workers may represent an overall contradiction of most companies’ overall goals—especially when establishing relationships with clients is more important than ever. View the full article

Key ChatGPT updates mapped for marketers, highlighting AI-driven trends that helped shape search behavior and visibility strategies. The post Timeline Of ChatGPT Updates & Key Events appeared first on Search Engine Journal. View the full article

We may earn a commission from links on this page. Did you know you can customize Google to filter out garbage? Take these steps for better search results, including adding Lifehacker as a preferred source for tech news. Doing things the old-fashioned way and hand-writing your notes is better for retaining what you’ve learned, but it definitely has drawbacks that can make typing notes more appealing. Hand-written notes aren’t searchable on your phone or laptop, for example, and unlike your phone, your notebook probably won’t always be with you for a quick study session on the bus or train. That’s why you should take advantage of both methods: once you’ve written them out, you should digitize your notes in some fashion to make studying easier, blending the old style with the new. Here are the best ways to do so. The easiest way to digitize your notes: A cameraThe most straightforward way to digitize your notes is by taking a picture of them and uploading it to your Google Drive or straight to your computer. You can name and file the images however you want, and though they won’t be easily searchable, they will be legible to you. Though this is super basic, it’s on the list because there’s one major advantage here: After uploading the image of your paper, you can stick it at the top of a document and use it as a guide to further revise your notes in the space for typing below. Manual revision (especially when done right after class) is extremely beneficial to understanding and retention, so if you’re trying to grasp the content at hand, it might be better to just type and revise it all yourself than to, say, let an app or gadget do the work for you. That said, phones are getting smarter, and the built-in photos app on iPhone allows you to search for specific words within photos. For example, if you know you have a page of notes about the respiratory system saved as a photo, you should be able to search "respiratory system" or "lungs" or "alveoli" and it will search all your photos for those phrases. Google Photos has something similar. On that note, let’s talk apps and gadgets. (No judgment.) Use an app to digitize your notesThe most popular app for digitizing notes is Evernote, which advertises itself as a “pocket scanner” on your phone. You use an in-app camera to scan the document and, if your notes are “clearly written,” they’ll become editable and searchable. I tested this one out and didn't love it, but it's still the most popular and worth your time to consider. (You can read my full review of Evernote here.) For what it's worth, in a head-to-head notes app battle, I tend to favor Notion over Evernote, but in this instance, that's not true because Notion doesn't allow for the scanning of handwritten notes. If you want to hand-write into an app, try Microsoft OneNote, which is free and easily converts what you write with your finger or stylus into searchable, editable text and makes it available across all your devices with Microsoft’s tools installed. Use a smart notebook to digitize your notesTo make the writing-to-digital process super easy, try a tool designed for the purpose: A smart notebook. You have a few options when it comes to devices that turn your writing into easily accessible notes. The most popular is the Rocketbook ($22–$40), which comes in a few different sizes and styles and is simple to use. You write on the pages with the pen that comes with it, scan the page with the associated app, and then wipe the page clean to start again, as whatever was already on it is syncing to your device. I picked one up for myself when I started grad school and got one for my boyfriend when he went back to school, too. We both found it easy to use, functional, and simple to transport. While those are more like traditional paper and pen, you also have the option of a smart notebook that is more like a tablet. There are a number of these on the market, but Lifehacker's Joel Cunningham spent a year testing eight of them and comprised this list of the best ones. With e-ink notebooks tablets aimed at those who need an AI assist, those who require a lot of writing space, or those who also want to read textbooks and other materials on it, you'll find one that aligns with your own needs. Just be warned that with prices between $285 and $690, they're quite a bit pricier than the Rocketbook. Still, a resource that can help you through school and beyond is always a good investment. For what it's worth, the best-performing one of the bunch is the Boox Note Air 4C 10.3-Inch Digital Notebook ($530) for a few reasons. Its 10.3" screen is big enough to write on, but not so big that it makes it hard to carry this thing around. The ease of writing with the stylus is notable, according to Joel's review, as is the varied functionality of its native note-taking app, which helps you not only write your notes, but organize them. Make a mind map insteadRevising your notes and turning them into readable, portable, and digital versions is smart no matter how you do it and you'll probably want to keep them, well, looking like notes. But there's value in making a mind map, too. Part of your revision process can be using an app like Xmind to create a visual mind map that shows the connections between the concepts, ideas, and facts in your notes. Studying with a mind map is helpful, especially for visual learners, because it helps you think critically about how everything you're going over works together, both while you're creating and reviewing the map. When you use an app to do it, your maps stay on your phone, so you still have the ease of studying whenever you can find time. View the full article

European shares were mixed in early trading while Asian shares mostly fell on Friday after a respite from Wall Street’s recent feverish rally. The price of gold also pulled back from record highs following recent torrid runs. The futures for the S&P 500 and the Dow Jones Industrial Average were both up less than 0.1%. Oil prices slipped. In early European trading, Germany’s DAX rose 0.2% to 24,652.73, while France’s CAC 40 added 0.4% to 8,076.96. Britain’s FTSE 100 slipped 0.1% to 9,498.95, weighed down by losses for mining and energy stocks. Most Asian indexes fell. But South Korea’s Kospi climbed 1.7% to 3,610.60 as trading reopened after a holiday. India’s BSE Sensex also gained, adding 0.5%. The Kospi’s surge was fueled by a rally of tech shares including SK Hynix, which rose 8.2%. Samsung Electronics added 6.1%, boosted by news that Nvidia-backed Reflection AI had raised $2 billion in funding, increasing its market value to $8 billion. Japan’s Nikkei 225 closed 1% lower to 48,088.80, pulling back from big gains the previous day after data showed producer prices rose more than expected in September. Political uncertainty also loomed after the ruling Liberal Democrats failed to persuade their junior coalition partner, the Buddhist-backed Komeito, to stay. The Komeito’s leader said the group was unhappy with the Liberal Democrats’ stance on cleaning up corruption. The Komeito’s move was a significant blow to hopes for LDP leader Sanae Takaichi, an ultra-conservative lawmaker, to become Japan’s first female prime minister. Hong Kong’s Hang Seng index shed 1.8% to 26,277.84, while the Shanghai Composite index slipped nearly 1% to 3,897.03. Australia’s S&P/ASX 200 slid more than 0.1% to 8,958.30. Taiwan’s stock market was closed for a holiday. On Thursday, the S&P 500 slipped 0.3% from its latest all-time high for just its second loss in the last 10 days. The Dow dropped 0.5% and the Nasdaq composite lost 0.1%. Gold also fell following its stellar rally this year, losing 2.4% to drop back below $4,000 per ounce, while Treasury yields held relatively steady in the bond market. They’re taking a moment following big runs driven in large part by expectations that the Federal Reserve will cut interest rates to support the economy. Financial markets have been climbing so relentlessly, including a 35% leap for the S&P 500 from a low in April, that worries are mounting that prices may have shot too high. Concerns are particularly strong about the frenzy lifting stocks related to artificial-intelligence technology. In other dealings early Friday, U.S. benchmark crude oil shed 6 cents to $61.45 per barrel. Brent crude, the international standard, edged down 14 cents to $65.08 per barrel. The U.S. dollar fell to 152.71 Japanese yen from 153.05 yen. The euro rose to $1.1585 from $1.1569. —Teresa Cerojano, Associated Press View the full article

Small business owners across the country are facing a familiar challenge: a significant number of job openings that remain unfilled. According to the latest NFIB September Jobs Report, 32% of small business owners reported having job openings they could not fill, a statistic that has remained consistent since August. This number has not dipped below 32% since July 2020, highlighting a persistent issue in the small business sector. Amidst this backdrop, the report’s findings present both challenges and opportunities for small business owners. Bill Dunkelberg, Chief Economist at NFIB, noted, “Main Street job openings remain above their historical average, with owners reporting few qualified applicants.” He emphasized the ongoing economic uncertainty, suggesting that while a recession seems unlikely, small business owners continue to navigate labor imbalances that could impact their growth. Key Findings from the Report Job Creation Plans: Encouragingly, a net 16% of small business owners plan to create new jobs in the next three months, marking the highest hiring intentions since January. This represents a 1-point increase from August. Hiring Activity: In September, 58% of small business owners either hired or attempted to hire, up by 5 points from the previous month. Among those hiring, 88% reported that they faced challenges finding qualified candidates, up 7 points from August. Skilled vs. Unskilled Labor: Of the reported openings, 28% were for skilled roles, while 13% were for unskilled labor. The evolving landscape means that small business owners must adapt their hiring strategies to not only attract candidates but also retain them. According to the report, the percentage of small business owners prioritizing labor quality as their most significant challenge decreased to 18%, down 3 points from August. However, labor costs have emerged as a growing concern, with 11% of owners citing it as their top issue—up 3 points from the previous month. Compensation Trends Compensation is a crucial factor in attracting talent. The report revealed that a net 31% of small business owners raised wages in September, an increase of 2 points from August. However, the percentage planning future raises decreased slightly to 19%, down 1 point from the previous month. This wage pressure indicates the competitive environment small business owners must navigate to retain and attract employees. Real-World Implications Given these insights, small business owners should prioritize innovative recruitment strategies. Here are a few practical steps to consider: Broaden Recruitment: Explore non-traditional hiring pools, including remote workers and underrepresented communities. Upskill Current Employees: Invest in training and development to enhance the skills of your current workforce. This can alleviate some pressure from the skills gap. Enhance Benefits: Flexible working hours, remote work options, and competitive benefits may attract candidates who are weighing choices between multiple opportunities. However, the challenges persist. The inability to find quality candidates could hinder planned business growth. Owners must remain vigilant about balancing compensation strategies while fostering a workplace culture that retains talent. As small business owners approach the busy end-of-year season, they should carefully evaluate their hiring strategies in light of these trends. Keeping a pulse on the economic environment and adapting quickly will be essential to navigating this continuously evolving landscape. For further details on the September Jobs Report and its implications, please visit the full report here. This document provides nuanced insights into the ongoing challenges and opportunities that await small business owners as they confront the complexities of the current job market. Image via NFIB This article, "Small Businesses Struggle with Job Openings as Hiring Plans Rise" was first published on Small Business Trends View the full article

Small business owners across the country are facing a familiar challenge: a significant number of job openings that remain unfilled. According to the latest NFIB September Jobs Report, 32% of small business owners reported having job openings they could not fill, a statistic that has remained consistent since August. This number has not dipped below 32% since July 2020, highlighting a persistent issue in the small business sector. Amidst this backdrop, the report’s findings present both challenges and opportunities for small business owners. Bill Dunkelberg, Chief Economist at NFIB, noted, “Main Street job openings remain above their historical average, with owners reporting few qualified applicants.” He emphasized the ongoing economic uncertainty, suggesting that while a recession seems unlikely, small business owners continue to navigate labor imbalances that could impact their growth. Key Findings from the Report Job Creation Plans: Encouragingly, a net 16% of small business owners plan to create new jobs in the next three months, marking the highest hiring intentions since January. This represents a 1-point increase from August. Hiring Activity: In September, 58% of small business owners either hired or attempted to hire, up by 5 points from the previous month. Among those hiring, 88% reported that they faced challenges finding qualified candidates, up 7 points from August. Skilled vs. Unskilled Labor: Of the reported openings, 28% were for skilled roles, while 13% were for unskilled labor. The evolving landscape means that small business owners must adapt their hiring strategies to not only attract candidates but also retain them. According to the report, the percentage of small business owners prioritizing labor quality as their most significant challenge decreased to 18%, down 3 points from August. However, labor costs have emerged as a growing concern, with 11% of owners citing it as their top issue—up 3 points from the previous month. Compensation Trends Compensation is a crucial factor in attracting talent. The report revealed that a net 31% of small business owners raised wages in September, an increase of 2 points from August. However, the percentage planning future raises decreased slightly to 19%, down 1 point from the previous month. This wage pressure indicates the competitive environment small business owners must navigate to retain and attract employees. Real-World Implications Given these insights, small business owners should prioritize innovative recruitment strategies. Here are a few practical steps to consider: Broaden Recruitment: Explore non-traditional hiring pools, including remote workers and underrepresented communities. Upskill Current Employees: Invest in training and development to enhance the skills of your current workforce. This can alleviate some pressure from the skills gap. Enhance Benefits: Flexible working hours, remote work options, and competitive benefits may attract candidates who are weighing choices between multiple opportunities. However, the challenges persist. The inability to find quality candidates could hinder planned business growth. Owners must remain vigilant about balancing compensation strategies while fostering a workplace culture that retains talent. As small business owners approach the busy end-of-year season, they should carefully evaluate their hiring strategies in light of these trends. Keeping a pulse on the economic environment and adapting quickly will be essential to navigating this continuously evolving landscape. For further details on the September Jobs Report and its implications, please visit the full report here. This document provides nuanced insights into the ongoing challenges and opportunities that await small business owners as they confront the complexities of the current job market. Image via NFIB This article, "Small Businesses Struggle with Job Openings as Hiring Plans Rise" was first published on Small Business Trends View the full article

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Yoast SEO is a free WordPress SEO plugin that helps your site perform better in search engines like Google. It also gives you the tools to bring your content to the highest SEO and overall readability standards. Here, we’ll explain how our plugin helps you build the best website possible! Table of contents What Yoast SEO does SEO for your posts and pages Technical SEO for your website Learn SEO by doing SEO with Yoast A quick recap What Yoast SEO does Yoast SEO offers many tools and features to boost your SEO. Some of these features influence the SEO of your whole site, while others help you optimize individual posts and pages for search engines. At Yoast, we believe in our mission, “SEO for everyone,” so you can access all the essential WordPress SEO tools in our free Yoast SEO plugin. But if you really want to boost your SEO, upgrade to Yoast SEO Premium. This upgrade gives you even more amazing SEO features, including great AI features like Yoast AI Optimize and AI Summarize! Keep reading to find out what Yoast SEO can do for your SEO! SEO for your posts and pages If you want your posts and pages to appear in the search results, you need to optimize them! So, when you use WordPress to create/edit posts, you’ll find a lot of Yoast SEO tools to help you draft and optimize great content. And if you think SEO optimization is all about keywords, think again. The tools and tips in our Yoast SEO plugins also focus on quality content and user experience. Trust us, because it will all help your rankings, directly or indirectly. Here’s how the plugins will help you optimize your posts and pages: Make sure you’re optimizing correctly (we’ll tell you if you aren’t) After you’ve done your keyword research, you’ll have to start optimizing the pages and posts on your sites for the keywords and keyphrases you want to rank for. To do that, you can set a focus keyphrase for an article in Yoast SEO. Then, the plugin uses our content SEO analyses to determine how your content scores on different factors. It checks how many times you use your keyphrase, the length of your text, or whether you used any internal links. The results of these analyses guide you in optimizing your post or page to rank with your chosen keyphrase. You’ll see red, orange, and green traffic lights to indicate how every factor scores. This gives you an overview of the overall score and what you can still tackle to increase your rankings! We also give you tools to find out which keywords you can target successfully, and track how successful your content really is. For the keyword research part, we integrate with the leading online marketing platform, Semrush. For tracking the performance of your content in search, we integrate with the rank tracking platform Wincher. Guidance for writing high-quality content — in many languages! Optimizing your content to rank with the right keyphrase is important, but don’t forget your reader! Even if you write amazing content for search engines, your audience won’t benefit from it if they don’t understand it. When a person doesn’t understand your content, the chance of them buying something from you is close to zero. The same is true for the odds of them sharing one of your articles with their friends. So, you must ensure your content is also easy to understand. And that’s where the readability features come in. Our readability checks let you adopt the feedback in a way that suits you, without losing your personal touch. If you’re interested in all the factors that increase readability, you can read more about the Yoast SEO readability features. What’s more, you can optionally enable the inclusive language analysis alongside readability and SEO checks The readability analysis tells you how to optimize your text to make it read easily using red, orange, and green traffic lights All or most features are available in the following languages: English, German, Dutch, French, Spanish, Italian, Portuguese, Czech, Russian, Polish, Swedish, Hungarian, Indonesian, Arabic, Hebrew, Turkish, Norwegian, Japanese, Slovak, and Greek.* We support more languages at various levels. Check the overview for other languages. * Unfortunately, it’s not possible to calculate the Flesch reading ease score for some of these languages. Check the overview below to see which languages. Based on years of research Yoast SEO’s readability features are well-researched analyses that give you feedback on how to optimize your writing. Now, this may sound strange, because the way you write can be very personal. Let us explain how it works. The plugin uses an algorithm to check your content for factors that are proven to increase readability. We look at the use of transition words, the use of passive voice, sentence and paragraph lengths, word complexity, and more. However, we carefully crafted this algorithm to be as accurate as possible without being too strict. Influence what Google shows in search results Of course, you don’t just want your pages to appear in Google’s search results. You want your search results to look amazing, too! That’s why Yoast SEO has tools to let you plan and preview how each page will (probably) look when it appears on Google. This is probably something we can’t avoid here, as Google will occasionally decide it knows better and show something else instead. But by optimizing certain outputs on your page, you can indicate how Google should present your content to users. And that’s still something worth doing. Titles and meta descriptions With our plugin, you can specify an SEO title (the ‘headline’ of your search result) and a meta description (a short piece of text underneath your search headline, describing what users can find on your page) for each new page you publish. We’ll let you know if these are too long or if your keyword is missing. If you want to, you can also set defaults for all your pages. You might have seen search results that contain extra parts beyond the usual headline-and-description format before. The example below contains recipes with extra information like reviews, cooking time, ingredients, and images, for instance. And that’s just one example. Extra information can be added for all kinds of results, including products! The way to get results like this is by using Schema structured data. We won’t lie: it’s complex, technical stuff. Luckily for you, you won’t need to know a thing about the tech wizardry behind it. Just having Yoast SEO installed means you’ll automatically have structured data output for your pages. All you need to do is select a few options to make sure it suits your needs. Manage social outputs Now, social media isn’t strictly a part of SEO. But when you make great content, you often want to share that content on your social feeds, too. That’s why Yoast SEO also comes with Facebook and X previews that you can adjust to make sure your content is always looking great, whoever is sharing it. You can set a specific title, description and OpenGraph image for each post. Again, if you prefer to set one standard structure for all posts, there’s an option to do that. Technical SEO for your website We’ve taken a look at what Yoast SEO can do for your posts and pages. But what can it do for your site overall? If technical SEO isn’t your strong suit, much of the following may not make sense to you. But don’t worry! Yoast SEO exists to make sure you don’t have to know all of these things. Set up your site for SEO The plugin settings are very sensible by default, and our first-time configuration also guides you through the steps to get your technical SEO settings right. Behind the scenes, our hidden features will also gear you up with an XML sitemap, a robots.txt file, site-level Schema structured data, and more. The free version of Yoast SEO automatically generates XML sitemaps for your website, making it easier for search engines like Google to find and index your content. These sitemaps update on their own whenever you add or remove pages, so you don’t have to do any manual work. In addition, Yoast SEO gives you easy access to your site’s robots.txt file. From the plugin, you can view or edit this file to control which parts of your site search engines are allowed to crawl. Both features help search engines discover your content while giving you more control over your site’s visibility. Thanks to Yoast SEO, you can now quickly and without additional cost add an llms.txt file to your site to guide AI systems toward your most valuable content. This simple text file helps AI tools identify and prioritize key pages efficiently, ensuring they focus on what matters most to your site. Manage your content As you write more and more content for your site, you’ll be looking for easy ways to manage it! The Yoast SEO plugin comes with a few features to help you manage your content well and avoid common SEO issues. For instance, when you make changes like deleting a page or changing a URL, if you don’t know what you’re doing, then things can get messy. And if you make a lot of similar pages, that can be a problem too, as Google doesn’t know which one it should direct users towards. To help you deal with SEO issues like these, Yoast SEO comes with two unmissable tools: canonical URL tags and the Redirects tool. Canonical URLs Canonical URLs are really helpful if you have a lot of similar content, such as a webshop with multiple variants of the same product, each having its own page. To make life easy for you, Yoast SEO automatically adds canonical tags to all content marked for indexing. All of the canonical tags will be taken care of in the background; in most cases, you won’t need to change a thing. If you do need to adjust your canonical URL tags, it’s easy to do so. Managing redirects Redirects are essential if you’re moving or removing content. The fact is, users will probably still find their way to the old URL, but the content they’re expecting won’t be there. That’s not only disappointing and frustrating for users, but it can also make it harder for Google to find and index your content, too. While advanced redirect management is part of Yoast SEO Premium, you can still handle basic changes using WordPress settings or other free plugins. Build your site structure and internal links If you want findable content that really ranks, you need to take care of your site structure and internal linking. The Yoast SEO plugin comes with a few tools to help you manage how your content links together: there’s a text link counter, which will tell you how many incoming and outgoing internal links there are on a page, as well as an internal linking suggestions tool in Yoast SEO Premium (in the editor view), which can help you add more if necessary. These features help you build a strong site structure and make sure your important content is easy for visitors and search engines to find. Even more technical features of Yoast SEO By simply installing the plugin and following the steps in our configuration workout, you’re already fixing a lot of important technical SEO things for your site! We do these steps for you, so you don’t have to know about every little technical detail. If you really want to know everything Yoast SEO can do for you, then take a look at the complete list of features. Additionally, if you are (a bit more) familiar with technical SEO, you might enjoy reading more about Yoast SEO’s hidden features that secretly level up your SEO! Read more: Things we don’t do in Yoast SEO and why » Learn SEO by doing SEO with Yoast Still need to learn about SEO? One of the biggest benefits of using the Yoast plugins is that they make it really easy to get started and learn as you go along! We’ll give you pointers to help you get everything right, as well as links to read more about how SEO works and how to do it. If you want to keep learning about SEO, we also offer free training courses and resources in our Yoast SEO Academy and on our SEO blog. You can start with these basics to understand how SEO works and get more out of your website as you go. A quick recap In this article, we’ve shown you what Yoast SEO can do for your site. Our plugin helps you improve your content SEO by helping you set a keyphrase and telling you exactly how you can optimize your content to rank with this keyphrase. The plugin also helps you improve the readability of your content by providing feedback that you can easily incorporate into your own writing style. And last but not least, the Yoast plugin improves your technical SEO by taking care of a lot of technical things in the background. Everything above is available in Yoast SEO’s free plugin, making it a great starting point for most WordPress users. If you ever want more advanced tools, you can always explore Yoast SEO Premium and its extra features. Okay, I'm convinced. Show me to that Yoast SEO plugin! The post What does Yoast SEO do? appeared first on Yoast. View the full article

Generative AI is no longer a single thing. Ask, “What is the best generative AI tool for writing PR content?” or “Is keyword targeting as impossible as spinning straw into gold?,” and each engine will take a different route from prompt to answer. For writers, editors, PR pros, and content strategists, those routes matter – every AI system has its own strengths, transparency, and expectations for how to check, edit, and cite what it produces. This article covers the top AI platforms – ChatGPT (OpenAI), Perplexity, Google’s Gemini, DeepSeek, and Claude (Anthropic) – and explains how they: Find and synthesize information. Source and train on data. Use or skip the live web. Handle citation and visibility for content creators. The mechanics behind every AI answer Generative AI engines are built on two core architectures – model-native synthesis and retrieval-augmented generation (RAG). Every platform relies on a different blend of these approaches, which explains why some engines cite sources while others generate text purely from memory. Model-native synthesis The engine generates answers from what’s “in” the model: patterns learned during training (text corpora, books, websites, licensed datasets). This is fast and coherent, but it can hallucinate facts because the model creates text from probabilistic knowledge rather than quoting live sources. Retrieval-augmented generation The engine: Performs a live retrieval step (searching a corpus or the web). Pulls back relevant documents or snippets. Then synthesizes a response grounded in those retrieved items. RAG trades a bit of speed for better traceability and easier citation. Different products sit at different points on this spectrum. The differences explain why some answers come with sources and links while others feel like confident – but unreferenced – explanations. ChatGPT (OpenAI): Model-first, live-web when enabled How it’s built ChatGPT’s family (GPT models) are trained on massive text datasets – public web text, books, licensed material, and human feedback – so the baseline model generates answers from stored patterns. OpenAI documents this model-native process as the core of ChatGPT’s behavior. Live web and plugins By default, ChatGPT answers from its training data and does not continuously crawl the web. However, OpenAI added explicit ways to access live data – plugins and browsing features – that let the model call out to live sources or tools (web search, databases, calculators). When those are enabled, ChatGPT can behave like a RAG system and return answers grounded in current web content. Citations and visibility Without plugins, ChatGPT typically does not supply source links. With retrieval or plugins enabled, it can include citations or source attributions depending on the integration. For writers: expect model-native answers to require fact-checking and sourcing before publication. Perplexity: Designed around live web retrieval and citations How it’s built Perplexity positions itself as an “answer engine” that searches the web in real time and synthesizes concise answers based on retrieved documents. It defaults to retrieval-first behavior: query → live search → synthesize → cite. Live web and citations Perplexity actively uses live web results and frequently displays inline citations to the sources it used. That makes Perplexity attractive for tasks where a traceable link to evidence matters – research briefs, competitive intel, or quick fact-checking. Because it’s retrieving from the web each time, its answers can be more current, and its citations give editors a direct place to verify claims. Caveat for creators Perplexity’s choice of sources follows its own retrieval heuristics. Being cited by Perplexity isn’t the same as ranking well in Google. Still, Perplexity’s visible citations make it easier for writers to copy a draft and then verify each claim against the cited pages before publishing. Dig deeper: How Perplexity ranks content: Research uncovers core ranking factors and systems Google Gemini: Multimodal models tied into Google’s search and knowledge graph How it’s built Gemini (the successor family to earlier Google models) is a multimodal LLM developed by Google/DeepMind. It’s optimized for language, reasoning, and multimodal inputs (text, images, audio). Google has explicitly folded generative capabilities into Search and its AI Overviews to answer complex queries. Live web and integration Because Google controls a live index and the Knowledge Graph, Gemini-powered experiences are commonly integrated directly with live search. In practice, this means Gemini can provide up-to-date answers and often surface links or snippets from indexed pages. The line between “search result” and “AI-generated overview” blurs in Google’s products. Citations and attribution Google’s generative answers typically show source links (or at least point to source pages in the UI). For publishers, this creates both an opportunity (your content can be quoted in an AI overview) and a risk (users may get a summarized answer without clicking through). That makes clear, succinct headings and easily machine-readable factual content valuable. Get the newsletter search marketers rely on. See terms. Anthropic’s Claude: Safety-first models, with selective web search How it’s built Anthropic’s Claude models are trained on large corpora and tuned with safety and helpfulness in mind. Recent Claude models (Claude 3 family) are designed for speed and high-context tasks. Live web Anthropic recently added web search capabilities to Claude, allowing it to access live information when needed. With web search rolling out in 2025, Claude can now operate in two modes – model-native or retrieval-augmented – depending on the query. Privacy and training data Anthropic’s policies around using customer conversations for training have evolved. Creators and enterprises should check current privacy settings for how conversation data is handled (opt-out options vary by account type). This affects whether the producer edits or proprietary facts you feed into Claude could be used to improve the underlying model. DeepSeek: Emerging player with region-specific stacks How it’s built DeepSeek (and similar newer companies) offers LLMs trained on large datasets, often with engineering choices that optimize them for particular hardware stacks or languages. DeepSeek in particular has focused on optimization for non-NVIDIA accelerators and rapid iteration of model families. Their models are primarily trained offline on large corpora, but can be deployed with retrieval layers. Live web and deployments Whether a DeepSeek-powered application uses live web retrieval depends on the integration. Some deployments are pure model-native inference, others add RAG layers that query internal or external corpora. Because DeepSeek is a smaller/younger player compared with Google or OpenAI, integrations vary considerably by customer and region. For content creators Watch for differences in language quality, citation behavior, and regional content priorities. Newer models sometimes emphasize certain languages, domain coverage, or hardware-optimized performance that affects responsiveness for long-context documents. Practical differences that matter to writers and editors Even with similar prompts, AI engines don’t produce the same kind of answers – or carry the same editorial implications. Four factors matter most for writers, editors, and content teams: Recency Engines that pull from the live web – such as Perplexity, Gemini, and Claude with search enabled – surface more current information. Model-native systems like ChatGPT without browsing rely on training data that may lag behind real-world events. If accuracy or freshness is critical, use retrieval-enabled tools or verify every claim against a primary source. Traceability and verification Retrieval-first engines display citations and make it easier to confirm facts. Model-native systems often provide fluent but unsourced text, requiring a manual fact-check. Editors should plan extra review time for any AI-generated draft that lacks visible attribution. Attribution and visibility Some interfaces show inline citations or source lists; others reveal nothing unless users enable plugins. That inconsistency affects how much verification and editing a team must do before publication – and how likely a site is to earn credit when cited by AI platforms. Privacy and training reuse Each provider handles user data differently. Some allow opt-outs from model training. Others retain conversation data by default. Writers should avoid feeding confidential or proprietary material into consumer versions of these tools and use enterprise deployments when available. Applying these differences in your workflow Understanding these differences helps teams design responsible workflows: Match the engine to the task – retrieval tools for research, model-native tools for drafting or style. Keep citation hygiene non-negotiable. Verify before publishing. Treat AI output as a starting point, not a finished product. Understanding AI engines matters for visibility Different AI engines take different routes from prompt to answer. Some rely on stored knowledge, others pull live data, and many now combine both. For writers and content teams, that distinction matters – it shapes how information is retrieved, cited, and ultimately surfaced to audiences. Matching the engine to the task, verifying outputs against primary sources, and layering in human expertise remain non-negotiable. The editorial fundamentals haven’t changed. They’ve simply become more visible in an AI-driven landscape. As Rand Fishkin recently noted, it’s no longer enough to create something people want to read – you have to create something people want to talk about. In a world where AI platforms summarize and synthesize at scale, attention becomes the new distribution engine. For search and marketing professionals, that means visibility depends on more than originality or E-E-A-T. It now includes how clearly your ideas can be retrieved, cited, and shared across human and machine audiences alike. View the full article

Did you know you can customize Google to filter out garbage? Take these steps for better search results, including adding Lifehacker as a preferred source for tech news. I'm going to say something that sounds contradictory at first, though I swear it does make sense eventually: You should always study in silence, but a little noise can be helpful for remembering things. Specifically, your noise can be helpful—that is, when you’re speaking out loud. If you practice the “production effect,” it can help you remember what you’re studying. Here’s how to use it the next time you’re trying to remember something challenging. What is the production effect?The production effect refers to what happens when you use vocalizing as a mnemonic to improve your memory of a new concept. Basically, your memory favors words you read aloud more than the ones you read silently. When you speak out loud, you’re producing something with your material, which is how this gets its name. Research has also shown that the more distinct things you produce, the better you’ll remember whatever you’re saying—so being loud or even singing the new information is more helpful than just reading it out loud. How to capitalize on the production effect when studyingYou have a few options when it comes to trying this out for yourself during a study session. At the most basic level, you can read your notes or textbook out loud to yourself, but in line with the research supporting the value of distinctiveness, I’d recommend taking it further. You can always rely on the Feynman technique, where you teach someone else the material you’re studying, and make sure you’re doing it out loud. I've recommended using ChatGPT to work through the Feyman method before, but if you're trying to tap into the production effect, that's not going to cut it this time. You can practice a few times with AI if you need to or if no one else is around to study with, but you should be going over it at least once out loud with someone else. Try incorporating the production effect into your flashcard use, too. When using the Leitner system, for instance, read your flashcards out loud to yourself. This approach is solid because it doesn't rely on anyone else participating. You don't need anyone else around to capitalize on the value of the production effect and, in fact, it's usually better to study on your own because you avoid distractions or being held back by someone else's schedule or lack of enthusiasm. I’ve already recommended making a “personal podcast” for your studies, too, and that’s helpful here not only because it gives you something to listen to over and over until you grasp it, but because you have to speak the material the first time around, lending the whole exercise to the production effect. This is your two-for-one option and, provided you have the patience to script and read your materials, record them, and listen back to them repeatedly, it's likely your best one. View the full article

Last year's WWC USA was a smash hit so we're returning to last year's great venue and central location at the iconic Computer History Museum. The post Wi-Fi World Congress USA will be back in Mountain View this April 13-15. Sign up now! appeared first on Wi-Fi NOW Global. View the full article

Industrial scion remade herself as a grassroots campaigner bent on unseating President Nicolás MaduroView the full article

Google has published a new help document on the topic of Google Business Profile negative review extortion scams. The document explains what they are, how to report the scam, what to expect and more importantly, what not to do.View the full article

Google is testing a new section within the Google Ads advertising console named "Missed Growth Opportunities." This section shows you the "performance you could've achieved in the last year if you'd adjusted your bids and budgets for campaigns with growth opportunities," according to Google.View the full article

Megan Rapinoe, Caitlin Clark, Serena Williams, Mia Hamm, Lindsey Vonn—the list of high-profile, recognizable women athletes is growing. And track and field athletes may be the next to become household names. That’s the bet that Alexis Ohanian is making with Athlos, an all-women’s track and field league, which is hosting its second event in New York this week. Ohanian is perhaps best known as the cofounder of Reddit, but he’s also an investor who’s made no secret of his interest in investing in sports. During a press event in New York City this week, he said the idea for Athlos came to him while watching the Olympics, during which millions of people tune in to watch track and field events. His logic: Why not try to tap into that audience outside of larger events? That’s how Athlos was born. The league is an attempt to capture the excitement around track and field events that has, traditionally, only existed around the Olympics and other big-time track and field events. Last year, during its inaugural event, Ohanian says it drew 3 million viewers, attracted big-name advertisers like Toyota and Tiffany & Co., and was more successful than anticipated. This year, he expects it to be even bigger, and hopes that some of the athletes taking part will start to become recognizable to casual sports fans—perhaps on a level that even matches what Clark has achieved in basketball. “Americans are going to be paying attention” When the Olympics or World Championship track and field events come around, “Americans are going to be paying attention,” Ohanian says. “[We] have a legacy of American excellence in the sport, especially among our women. No one doubted for a second that women’s soccer, women’s basketball, was a tier-one opportunity.” Ohanian was joined at the press conference by a lineup of Olympic Gold Medalists, world champions, and recordholders, including Masai Russell, Alexis Holmes, Grace Stark, Keely Hodgkinson, Faith Kipyegon, and Georgia Hunter Bell. Those athletes and others will compete this week for a top prize of $60,000. And Athlos is also giving some of them the chance to focus entirely on their chosen events, something that, until very recently, only the top sliver of athletes have been able to do. British mid-distance runner Georgia Hunter Bell, for instance, said that she only recently was able to quit her full-time job in tech sales to focus on track and field—and she’s an Olympic medalist who has set national records. “It was hard training around a full-time, corporate job and trying to train like a professional athlete,” she said. But leagues like Athlos are creating pathways to the pros for athletes like her. Globally, revenue from women’s sports doubled from 2023 to 2024 and was expected to exceed $2.3 billion this year, according to a March 2025 report from Deloitte. Basketball and soccer remain the sector’s biggest moneymakers. Athlos is only the most recent attempt at creating a professional-level league for female athletes. Several others are already gaining traction, including the WNBA, the National Women’s Soccer League (NWSL), and the Professional Women’s Hockey League (PWHL). The demand is there, Ohanian argues, and there’s a big business opportunity for brands, advertisers, athletes, and others to get in on it—though he thinks it’ll take some time. “I think this is just the start. We’re not at F1 (Formula 1) size yet,” he said. “But I want people to take for granted that this sport—which, again, is the most popular sport during the Olympics—can have the same-size platform outside of that, and bring together athletes, builders, CEOs, and investors who can keep driving it.” View the full article

There are a nice number of reports of GA4, Google Analytics, showing a huge surge in organic search traffic over the past couple of days, but Google Search Console is not showing any increase, it remains flat. Some are suspecting this is the result of fake bot traffic not being filtered by GA4, but others are not sure.View the full article

Greetings, salutations, and my thanks—as always—for reading Fast Company’s Plugged In. Me: “Are you here just to monitor for safety?” Guy sitting in the driver’s seat of the Tesla Model Y I’m riding in: “I can’t specify.” That was the extent of the conversation during a recent trip I took using Tesla’s Robotaxi service. I was curious why the car that picked me up had a human in it: After all, Tesla bills its service as “the future of autonomy,” and the car did, in fact, drive itself for the entirety of my 4.5-mile journey. But I didn’t get any answers from this guy—or Tesla the corporate entity, which prides itself on ignoring the media and didn’t reply to my emailed questions. This we do know. After years of anticipation, Tesla rolled out Robotaxis in Austin in June. A month later, they arrived here in the San Francisco Bay Area. For now, however, it falls far short of a full-blown deployment of a small-r robotaxi service. (The term is often used generically for self-driving car services as well as being a Tesla trademark.) For one thing, I spent time on a waitlist before being allowed to start hailing cars. For another, Tesla reportedly launched Robotaxi in the Bay Area without securing the necessary approval to operate a fleet of autonomous vehicles in California. Its Robotaxis are autonomous in the same sense that any Tesla car with the misleadingly named “full self driving” package is autonomous. Hence the need for the guy in the driver’s seat—a safety monitor who could take over in an emergency. It’s a little like getting a lift from a friend who owns a Tesla, who would also be required to stay behind the wheel. In Austin, where Tesla is further along in the regulatory process, the company initially put the safety monitors in the front passenger seat, but has reportedly moved them to the driver’s seat as well. All of this is fundamentally different from Waymo, which began as Google’s self-driving car project and—after an extraordinarily long, hard, expensive slog—is up and running in Austin, San Francisco, and three other U.S. metropolitan areas. Waymos have no safety monitors; it’s just you, any friends or relatives you’ve brought along, and the car. The service is a triumph not only of technology but also the patient labor required to convince relevant officials that permitting unsupervised cars to drive themselves around a city isn’t a deadly mistake, and might even be safer than letting humans behind the wheel. In its present incarnation, Tesla’s Robotaxi service also bears scant resemblance to the one Elon Musk talked up at an event in April 2019. Back then, the company was going to have a million such vehicles on the road—not Tesla-owned ones, primarily, but privately owned cars that could hit the road and ferry passengers when their owners didn’t need them. Oh, and Musk said that would happen by the end of 2020. During this presentation, Musk did cheerfully acknowledge his tendency to blow deadlines. But a half-decade later, his 2019 plan has barely inched toward reality. Even his comparatively modest recent prediction of Tesla autonomous ride-hailing being available to half the U.S. population (“subject to regulatory approvals”) by the end of 2025 is not going to happen. Meanwhile, I don’t intend to pay much attention to the Cybercab—a self-driving two-seater Tesla with no driver’s seat, allegedly due next year—until I’m riding in one. Judged on their own merits as a mode of transportation, I’ve found my first Tesla Robotaxi trips uneven at best. Unexpectedly, the best part has been their aggressively low pricing. Tesla has abandoned its original per-trip flat rate of $4.20 (ha ha, Elon!). But for my journeys, Robotaxi always beat Waymo and Uber pricing, sometimes by a lot. The first trip I took—returning home from a nearby mall—cost a mere $1.92. More pluses: Tesla’s Robotaxi fleet of Model Y cars is more reliably clean and cushy than Uber or Lyft. The service covers a far broader swath of the Bay Area than Waymo. And unlike Waymos in their present form, Robotaxis can take the highway—presumably because they’re not officially autonomous vehicles—making longer trips practical. Once one of the best-regarded car companies in the world, Tesla is now dogged with a reputation for safety problems, especially when it comes to self-driving: When I announced I’d been in a Robotaxi, one friend told me I shouldn’t put my life at risk like that. Grim humor aside, all the trips I’ve taken felt safe and involved efficient routes. (I should note that in one case, the safety monitor did have his hands on the wheel a fair amount of the time—whether out of necessity or force of habit, I can’t say.) Still, moving past the question of autonomy for a moment, I didn’t find Robotaxis ready to replace ride-hailing services even in their traditional, human-driven form. How many taxis Tesla has in the Bay Area is a mystery, but it’s clearly not enough: When I checked, pickup wait times usually were in the neighborhood of 13 to 15 minutes and got as high as 29 minutes. Worse, the Robotaxi app often said no cars were available at all, and told me to try again later. The Robotaxi software also lacks Waymo’s polish. When I leaned forward to play with the back-seat touchscreen, I kept getting a message telling me to put my (still buckled) seat belt back on or the car would pull over. That screen appeared to offer an array of entertainment options, but when I tapped on Netflix and Disney+, all I got were sign-up promos. Then there’s the service’s iPhone app, which has a rickroll-style gag involving tipping that I didn’t find funny the first time and don’t relish encountering on any future trips. Most of all, the need for the safety monitor eviscerates any possibility of Robotaxi rivaling the experience Waymo is already delivering. Once you get over the coolness factor, much of Waymo’s value proposition is the aura of comfy isolation. You can take calls, bang away at your laptop, or maybe even take a short nap without feeling like privacy is an issue or you’re being rude to the driver. It’s the closest thing to an office on wheels I’ve ever encountered. The Robotaxi safety monitors may be a vestigial concession to regulatory reality, but they eliminate the magic of autonomy. When—if?—Tesla is able to safely ditch them, it will make the service a true Waymo competitor. For now, the monitors I encountered were perfectly polite but also resistant to my efforts to chat them up. Here’s another dialogue I had with one: Me: “So the car is driving itself?” Safety monitor: “Yeah.” Surveys show that many people who haven’t been in a self-driving car remain deeply skeptical of the whole idea. I can’t help but think that Tesla is missing an opportunity by not turning the monitors into ambassadors. Rather than deflecting inquiries, maybe they should be volunteering information, as if they were welcoming tour guides to the autonomous future Musk has promised but not yet fully delivered. You’ve been reading Plugged In, Fast Company’s weekly tech newsletter from me, global technology editor Harry McCracken. If a friend or colleague forwarded this edition to you—or if you’re reading it on FastCompany.com—you can check out previous issues and sign up to get it yourself every Friday morning. I love hearing from you: Ping me at hmccracken@fastcompany.com with your feedback and ideas for future newsletters. I’m also on Bluesky, Mastodon, and Threads, and you can follow Plugged In on Flipboard. More top tech stories from Fast Company What’s it really like to use a folding phone? Life with the Google Pixel 10 Pro Fold A gimmicky category is growing up. And skepticism be damned, it does feel like a taste of the future. Read More → Meta’s next big bet for VR: Your living room The company’s Hyperscape VR app will have the ability to create digital replicas of your surroundings. Photorealistic avatars may soon follow. Read More → What can the rise and fall—and rebound—of NFTs teach us about the AI bubble? After the market for NFTs collapsed in 2022, the tech quickly fell out of the mainstream. It never went away, though. Experts now tell Fast Company what went wrong and what’s next. Read More → The flailing The President Media is part of the Russell 3000 index. These states want to know why The company’s poor performance raises questions about its inclusion. Read More → This massive new data center is powered by used EV batteries A new project from battery recycling startup Redwood Materials and data center builder Crusoe shows that it’s possible to build data centers cheaper and faster while also slashing emissions. Read More → ChatGPT wants to be the new operating system. Here’s why that should worry us Compute has become the new oil, and OpenAI just secured drilling rights. Read More → View the full article

Google has updated its Voice Search models to be powered by Speech-to-Retrieval (S2R). Google said this allows it to "gets answers straight from your spoken query without having to convert it to text first, resulting in a faster, more reliable search for everyone."View the full article

The Microsoft Advertising blog posted about how to optimize for AI Search Answers. I thought it was weird to see this on the Microsoft Advertising blog and not on the Bing Search blog, because (a) it is an ad blog and (b) it was written by Krishna Madhavan, who is part of the Bing team, not ad team.View the full article

This past June, Meta set off a bomb in the marketing world when it announced that it would fully automate the advertising on its platforms by 2026. People in advertising wondered: Is this the end of ad agencies as we know it? Has the AI “slopification” of social media finally been fully realized? The hyperbolic reaction is understandable—maybe even justified. With 3.43 billion unique active users across its platforms around the world, and an advertising machine that brought in $47.5 billion in Q2 sales alone (up 22% over last year), Meta is an accurate bellwether for where the ad business is heading. Meta has been working for years to build a machine that is already pretty damn close to automating its entire ad system, from creative concept generation to determining whose eyeballs see the final product. Its current capabilities are good enough to give most advertising creatives the flop sweats. But now is not the time for marketers to cower in fear. The opposite, actually. This is a great moment for marketers face head-on how Meta views its relationship with creatives, agencies, and brands, as it continues to roll out new technologies and features. To help, we asked Meta ad execs to break down their strategy. Below is a detailed explainer to help you understand how Meta is thinking about its role in the advertising space, and what brands, agencies, and even consumers can do to better prepare themselves for what’s to come. In this premium piece, you’ll learn: What Meta’s new AI advertising tools are and how they work, straight from the people creating them The reason why agencies will always be a part of Meta’s advertising equation Which tools are turbocharging growth for marketers, according to Helen Ma, Meta’s VP of product management (GenAI ad formats, video growth, creative diversification) Five key breakthroughs Earlier this month, Meta announced a slew of features to its AI-powered ad platform, including virtual try-on tech, AI-generated video for advertisers, and generative CTA (call to action) stickers to replace the common “Buy Now” button. But to understand the significance of the new tools, it’s important to step back for a moment and dig into the technology infrastructure that powers Meta’s advertising system. Over the past few years, Meta has systematically rebuilt its entire ad infrastructure around AI. Each innovation builds on previous advances, creating compounding improvements in the effectiveness of ads on its platforms. (Take haircare brand Living Proof, for example, which saw an 18% boost in purchases after using Meta’s generative AI feature for ad creative, compared to using its usual campaign strategy and creative.) This all-in-one-place approach to marketing tools reduces the operational burden for advertisers while increasing their dependence on Meta’s systems. The goal for Meta is to be as embedded as possible in a brand’s overall marketing operation. Matt Steiner, Meta’s VP of monetization infrastructure for ranking and AI foundations, says there are essentially five key technological breakthroughs that underpin Meta’s AI advertising platforms. The focus is on automating and optimizing every part of the advertising process, from creative generation to targeting and performance measurement. Here’s what you need to know: Advantage Plus Shopping Campaigns: The Automated Ad Manager Instead of advertisers needing large teams to constantly monitor their ads, analyze spreadsheets, and manually decide when to increase or decrease spending, Meta introduced Advantage Plus in 2022 to use machine learning models to do the heavy lifting. The AI constantly monitors which campaigns and audiences are performing well and automatically redirects the budget and changes the bid strategy 24 hours a day to maximize results. “I think the key innovation that drives it is that machine learning models don’t get tired,” Steiner says. He notes that this technology was key to Meta’s ad business when Apple introduced anti-tracking changes for iPhone users. Historically, Meta could track whether ads you saw on its platforms ultimately led to a purchase elsewhere, and this anti-tracking change cut off its lifeline to that information. Meta bypassed the blockage using transfer learning and combining its app data with advertisers’ own data on the people using its sites and making purchases. Meta Lattice: The “Shared Knowledge” System This is a deep machine learning technology that allows different AI models to learn from each other. Traditionally, Meta had separate AI models predicting different user behaviors. For example, one model would predict who will click on an ad, while another would predict who would actually buy the product. Announced in 2023, Lattice utilizes transfer learning, which allows these models to share knowledge. Transfer learning is a concept where a machine learning model trained to do one task can be trained to do a second task, and its performance on the first task improves by being trained to do the second task. Generative AI for Ads Creative: The Automatic Ad Designer This set of tools, originally introduced in May 2024, automatically creates variations of a brand’s ad content across text and image backgrounds as well as entirely new images from scratch. It then optimizes them to look good and perform well on Meta platforms. This saves advertisers time by allowing them to test and learn what consumers respond to much faster than a human team could. “Humans are best at coming up with novel ideas,” says Steiner. “They’re not really good at thinking of all variations of the word buy or sale, and that’s not something people are really excited to do. So with machine learning models to automate that, they can spend their time doing the things that are uniquely human-skilled, like coming up with new ideas and really understanding why a campaign will resonate with people—things that are not really automatable today.” Andromeda: The High-Speed Ad Finder The goal of all Meta advertising is to match the right brand’s ad to the right person at the time that person is most likely to click (and buy). Thanks to the new AI ad tools rolled out over the past year, the number of ads available in Meta’s system increased rapidly. Within a month of launching its first AI tools in 2024, more than a million advertisers used Meta’s generative AI tools to create more than 15 million ads. This essentially clogged the system and made it harder and slower for Meta to search through all those ads to find the few that might be relevant to any particular user. In December Meta introduced Andromeda, a massive technical and hardware upgrade to Meta’s backend infrastructure that lends it up to 10,000 times more computing power. Codesigned with Meta Training and Inference Accelerator (MTIA) and Nvidia’s Grace Hopper Superchip​​, Andromeda allows Meta’s system to handle the massive increase in demand for computing power from all the ads being created using its generative AI tools. Steiner says the result has been a dramatic improvement in the selection of relevant ads, increasing the likelihood of people finding a useful ad and ultimately driving up conversions for advertisers. According to the company, so far it has boosted conversions on Facebook mobile Feed and Reels by 4%. Generative Ads Recommendation Model (GEM): The Customer Map Introduced in April, GEM is new AI model architecture for deciding which ad to show you, based on predicting future behavior. Just as an LLM uses sequence learning to predict the next logical item in a sequence, this does the same thing for ads. Instead of just predicting whether you’ll click on the next single ad, GEM tracks your entire history of ad interactions and purchases. This allows the model to recognize that you might be on several different, parallel “purchase journeys” simultaneously and react accordingly. The company says these improvements increased ad conversions by approximately 5% on Instagram and 3% on Facebook Feed and Reels in Q2. Ad feeds of the future This new backbone technology is powering all the ads you see, but it’s all more or less invisible. Here’s what Meta is betting on to get you buying more across Instagram, Facebook, and WhatsApp: Virtual try-on: This is exactly what it sounds like. Meta is now testing with select advertisers the ability to see how clothing featured in an ad looks on them after they upload a photo of themselves. AI Sticker CTA (call to action): Most of the time you see an ad on Instagram, there’s a generic “Shop Now” button at the bottom. Now brands are going to be using custom AI-generated stickers that could be a product photo or a logo graphic to add a bit more flair. “We’re seeing something like 50% to 200% higher click-through rates on these AI-generated CTA stickers, because they’re fun and visually appealing and bring the product to life,” says Helen Ma, Meta’s VP of product management. Previously announced at Cannes, this visual enhancement is now available to more advertisers globally for Facebook Stories and testing for Facebook Reels, as well as Instagram Stories and Reels. Creative generation upgrades: Meta rolled out two notable updates to its generative AI tool kit. First is an AI-generated music feature that understands the content of an ad and produces unique, custom music that reflects the product, style, and sentiment a brand wants to convey. It will also feature AI dubbing for international or multilingual audiences. The other is what Meta calls “persona-based image generation,” to help advertisers further personalize ads to different customers. This is like an AI vibes tool, changing the vibe of an ad to fit specific audiences. If you’re selling headphones, it can create one image that focuses on style for a fashion angle, one to highlight sound quality for audiophiles, and another that emphasizes comfort for travelers, all from the same product image. Facebook creator discovery API: This makes it easier for brands to find creators on Facebook by allowing them and third-party partners (like agencies) to search for creators using keywords. It also helps agencies and brands explore creator insights like audience demographics and average engagement rate to find the best match. Meta AI assistant-informed ads: The Meta AI digital assistant has more than 1 billion active monthly users and is available as a stand-alone app, as well as across its apps like Facebook, Instagram, WhatsApp, and Messenger. Starting December 16, the company will utilize users’ interactions with the AI assistant to inform ads and other content it shows them. Krassimir Karamfilov, Meta Advertising’s VP of product, says that the number of Meta platforms, combined with billions of users, makes it impossible for individual marketers to get the most out of their ads without the help of tools like this. “It’s just impossible to manually test all the potential variants, so this is why AI is just making it easier to experiment efficiently and then home in on what works,” Karamfilov says. He knows that some advertisers have expressed concerns over a lack of control, but he counters that ads perform better when they’re not limited to the brand’s initial parameters. “We see a lot of suboptimal usage of our products,” he says. “What we’re doing is all about aligning our systems to the way the advertisers measure value.” Enter the AI Concierge Meta isn’t stopping at the ads in your feed. It sees a bigger business opportunity in helping brands—especially small and midsize businesses—utilize AI agents in their own business operations like customer service. Earlier this month, the company launched Business AI, which acts as a sales concierge to help take a consumer from an ad in a Meta feed all the way to purchasing a product. It acts as a personalized AI agent on Meta ads, messaging threads inside Meta platforms, and can even extend to the brand’s own websites. Clara Shih, VP of Business AI, says Meta’s clients were asking for help beyond the advertising side. “Our customers have said, ‘We want AI to not only help with product discovery and generating leads, help us all the way to closure, help us with our business operations, help us with customer support questions,” Shih says. A recent MIT study reported that 95% of enterprise generative AI pilots fail to deliver measurable business impact, despite a collective billions invested. Shih says Business AI takes the burden of infrastructure off of companies in order to feel that impact. “It’s just very hard, and a lot of companies don’t have big machine learning and AI teams where they can piece all these things together,” she says. “So something else that’s been really important to us is creating something that’s easy to set up and maintain.” The benefit to brands is that a Meta-powered AI chatbot doesn’t have to learn about a brand from scratch because so many businesses and brands have been active on Meta for years. Shih says all of their past ads and social posts are a gold mine of tacit knowledge about a businesses within the Meta universe, giving the Business AI chatbot a lot of information to work with from the start. “They don’t have to hire a consultant and pay millions of dollars to set up their chatbot. We could just look at what they’ve said and what they’ve done and what their brand is all about,” she says. “And just by using LLMs to mine that information, we’ve been able to create the world’s first turnkey business agent that just works because it’s them. It’s all based on what they’ve done.” It’s all very fun and convenient in the short term. And Meta’s recent earnings prove that it’s working. Second-quarter ad sales hit more than $47 billion, a 22% increase year over year. Every executive I spoke to emphasized that these are tools for humans to use, and that the company’s relationship with agencies and creatives are crucial to any of this working—at least for now. Just keep in mind that the end game here is still full automation. As Shih put it, “Mark [Zuckerberg] has talked about how in the future, the dream state for a business is to come to Meta, share their product catalog, share their business outcomes, and then we can automate the rest through a combination of Advantage Plus AI features, all as a business agent,” she says. “And we are getting closer and closer to that.” View the full article

While online discussion obsesses over whether ChatGPT spells the end of Google, websites are losing revenue from a far more real and immediate problem: some of their most valuable pages are invisible to the systems that matter. Because while the bots have changed, the game hasn’t. Your website content needs to be crawlable. Between May 2024 and May 2025, AI crawler traffic surged by 96%, with GPTBot’s share jumping from 5% to 30%. But this growth isn’t replacing traditional search traffic. Semrush’s analysis of 260 billion rows of clickstream data showed that people who start using ChatGPT maintain their Google search habits. They’re not switching; they’re expanding. This means enterprise sites need to satisfy both traditional crawlers and AI systems, while maintaining the same crawl budget they had before. The dilemma: Crawl volume vs. revenue impact Many companies get crawlability wrong due focusing on what we can easily measure (total pages crawled) rather than what actually drives revenue (which pages get crawled). When Cloudflare analyzed AI crawler behavior, they discovered a troubling inefficiency. For example, for every visitor Anthropic’s Claude refers back to websites, ClaudeBot crawls tens of thousands of pages. This unbalanced crawl-to-referral ratio reveals a fundamental asymmetry of modern search: massive consumption, minimal traffic return. That’s why it’s imperative for crawl budgets to be effectively directed towards your most valuable pages. In many cases, the problem isn’t about having too many pages. It’s about the wrong pages consuming your crawl budget. The PAVE framework: Prioritizing for revenue The PAVE framework helps manage crawlability across both search channels. It offers four dimensions that determine whether a page deserves crawl budget: P – Potential: Does this page have realistic ranking or referral potential? Not all pages should be crawled. If a page isn’t conversion-optimized, provides thin content, or has minimal ranking potential, you’re wasting crawl budget that could go to value-generating pages. A – Authority: The markers are familiar for Google, but as shown in Semrush Enterprise’s AI Visibility Index, if your content lacks sufficient authority signals – like clear E-E-A-T, domain credibility – AI bots will also skip it. V – Value: How much unique, synthesizable information exists per crawl request? Pages requiring JavaScript rendering take 9x longer to crawl than static HTML. And remember: JavaScript is also skipped by AI crawlers. E – Evolution: How often does this page change in meaningful ways? Crawl demand increases for pages that update frequently with valuable content. Static pages get deprioritized automatically. Server-side rendering is a revenue multiplier JavaScript-heavy sites are paying a 9x rendering tax on their crawl budget in Google. And most AI crawlers don’t execute JavaScript. They grab raw HTML and move on. If you’re relying on client-side rendering (CSR), where content assembles in the browser after JavaScript runs, you’re hurting your crawl budget. Server-side rendering (SSR) flips the equation entirely. With SSR, your web server pre-builds the full HTML before sending it to browsers or bots. No JavaScript execution needed to access main content. The bot gets needed in the first request. Product names, pricing, and descriptions are all immediately visible and indexable. But here’s where SSR becomes a true revenue multiplier: this added speed doesn’t just help bots, but also dramatically improves conversion rates. Deloitte’s analysis with Google found that a mere 0.1 second improvement in mobile load time drives: 8.4% increase in retail conversions 10.1% increase in travel conversions 9.2% increase in average order value for retail SSR makes pages load faster for users and bots because the server does the heavy lifting once, then serves the pre-rendered result to everyone. No redundant client-side processing. No JavaScript execution delays. Just fast, crawlable, convertible pages. For enterprise sites with millions of pages, SSR might be a key factor in whether bots and users actually see – and convert on – your highest-value content. The disconnected data gap Many businesses are flying blind due to disconnected data. Crawl logs live in one system. Your SEO rank tracking lives in another. Your AI search monitoring in a third. This makes it nearly impossible to definitively answer the question: “Which crawl issues are costing us revenue right now?” This fragmentation creates a compounding cost of making decisions without complete information. Every day you operate with siloed data, you risk optimizing for the wrong priorities. The businesses that solve crawlability and manage their site health at scale don’t just collect more data. They unify crawl intelligence with search performance data to create a complete picture. When teams can segment crawl data by business units, compare pre- and post-deployment performance side-by-side, and correlate crawl health with actual search visibility, you transform crawl budget from a technical mystery into a strategic lever. 3 immediate actions to protect revenue 1. Conduct a crawl audit using the PAVE framework Use Google Search Console’s Crawl Stats report alongside log file analysis to identify which URLs consume the most crawl budget. But here’s where most enterprises hit a wall: Google Search Console wasn’t built for complex, multi-regional sites with millions of pages. This is where scalable site health management becomes critical. Global teams need the ability to segment crawl data by regions, product lines, or languages to see exactly which parts of your website are burning budget instead of pushing conversions. Precision segmentation capabilities that Semrush Enterprise’s Site Intelligence enables. Once you have an overview, apply the PAVE framework: if a page scores low on all four dimensions, consider blocking it from crawls or consolidating it with other content. Focused optimization via improving internal linking, fixing page depth issues, and updating sitemaps to include only indexable URLs can also yield huge dividends. 2. Implement continuous monitoring, not periodic audits Most businesses conduct quarterly or annual audits, taking a snapshot in time and calling it a day. But crawl budget and wider site health problems don’t wait for your audit schedule. A deployment on Tuesday can silently leave key pages invisible on Wednesday, and you won’t discover it until your next review. After weeks of revenue loss. The solution is implementing monitoring that catches issues before they compound. When you can align audits with deployments, track your site historically, and compare releases or environments side-by-side, you move from reactive fire drills into a proactive revenue protection system. 3. Systematically build your AI authority AI search operates in stages. When users research general topics (“best waterproof hiking boots”), AI synthesizes from review sites and comparison content. But when users investigate specific brands or products (“are Salomon X Ultra waterproof, and how much do they cost?”) AI shifts its research approach entirely. Your official website becomes the primary source. This is the authority game, and most enterprises are losing it by neglecting their foundational information architecture. Here’s a quick checklist: Ensure your product descriptions are factual, comprehensive, and ungated (no JavaScript-heavy content) Clearly state vital information like pricing in static HTML Use structured data markup for technical specifications Add feature comparisons to your domain, don’t rely on third-party sites Visibility is profitability Your crawl budget problem is really a revenue recognition problem disguised as a technical issue. Every day that high-value pages are invisible is a day of lost competitive positioning, missed conversions, and compounding revenue loss. With search crawler traffic surging, and ChatGPT now reporting over 700 million daily users, the stakes have never been higher. The winners won’t be those with the most pages or the most sophisticated content, but those who optimize site health so bots reach their highest-value pages first.For enterprises managing millions of pages across multiple regions, consider how unified crawl intelligence—combining deep crawl data with search performance metrics—can transform your site health management from a technical headache into a revenue protection system. Learn more about Site Intelligence by Semrush Enterprise. View the full article

Cleveland, we have a problemView the full article

Maybe you’re meeting a coworker you’ve only known on Zoom in person for the first time. Maybe you’re greeting a group of coworkers at a conference, or saying goodbye after a team happy hour. Maybe a coworker has experienced a sudden loss. Or maybe you’re simply more of a hug person than a handshake person. Is embracing a colleague a faux pas—or worse? Cultural moments like the #MeToo movement, as well as the hands-off norms established during the pandemic, have shaped opinions about when it’s okay to touch someone else. Although most people don’t greet their office mates with literal open arms each day, colleagues who’ve developed close bonds may feel inclined to hug from time to time. That’s probably not surprising, given the important role friendships play in the workplace. And with the rise of flexible work in the knowledge economy, where people are encountering colleagues in real life less frequently, interacting with them face-to-face feels more like an event that warrants something more than a firm business handshake. But is it okay to hug your coworkers? Even if they’re friends? It’s a touchy subject, depending on whom you ask—perhaps the touchiest. To hug or not hug Cameron Herold is decidedly pro-hug. The founder of the COO Alliance (a coaching practice for chief operating officers) and former COO of 1-800-GOT-JUNK says he started his career in the straightlaced, suit-and-tie, handshakes-only late ’80s. A trip to Burning Man in 2007 changed his ways. “Everybody was hugging. It pulled me way out of my comfort zone,” he says. Since that trip, he greets just about everyone with an embrace, including former Sprint CEO Marcelo Claure upon meeting him roughly eight years ago. “I’m 6-foot-3 and he’s 6-foot-7. I went in for an over-the-shoulder hug. He laughed, said that was a first ever,” he recalls. That hug led to two lucrative coaching engagements with Claure and his then-chief operating officer, Herold recalls. Other workplace experts are more measured about coworkers and touch. Author and CEO coach Kim Scott, who’s coached at places like Dropbox and Twitter, says if you want to touch someone, it’s your job to find out first whether they’re comfortable being touched. “If they’re not comfortable, don’t touch,” she says, adding, “And if you’re not sure, don’t touch.” Ignoring that advice could land you in hot water, says Virginia-based employment attorney Leah Stiegler. She says that legally, there’s a “two-pronged element” to deem an action offensive: The action must be considered offensive by a reasonable third person, in addition to the person touched feeling offended. But if an employee files a lawsuit alleging a hostile workplace or sexual harassment, the company will still have a costly defense on its hands, even if the case is thrown out, Stiegler says. Plus, even if the hug isn’t something that would rise to the level of a hostile workplace lawsuit, an internal report to human resources about unwanted touching could cause its own problems for the hugger. When communications adviser Elizabeth Rosenberg worked at a previous employer, part of the company’s (pre-pandemic) annual holiday gathering was having all 300 employees walk the “line of leadership,” where company brass gave each a thank-you note and their bonus. Leaders also gave team members a hug, fist bump, or no touch, depending on the employee’s preference. Rosenberg says it was up to the team member to voice their preference. “I feel like we have got to be better about taking responsibility for our own feelings,” she says. “If somebody is uncomfortable being hugged, I think they need to step up and say, ‘I’m not comfortable with hugging.’” Before you reach, read the room What makes some people open to embracing coworkers while others would rather chew glass? (As one Reddit poster put it: Since when are people giving hugs at work?) Even outside the office, “hug or no hug” has been a long-standing cultural debate. Social media debates and news articles capture the tension: In general, is hugging creepy? Sweet? Invasive? Affirming? Inappropriate? Appropriate? We all have different backgrounds and preferences that can affect how we feel about being hugged or touched, says workplace mental health expert and licensed clinical social worker Christina Muller. “Some people call it a ‘love language,’” she says. An individual’s “language” of building connection may be physical touch, like hugging. Others may prefer time spent together, praise, or acts of service, for example. For those people, “getting a cup of coffee or just letting them vent could be a [preferred] source of comfort and connection,” she says. Even with the risks, Stiegler stops short of recommending a blanket “no hugging/no touching” policy, which she says would be difficult to enforce. Instead, establish strong anti-harassment policies and train employees about the behavior expected in the workplace, including consent. One solution is to provide an easy way to dodge an unwanted hug, says author Ben Swire, founder of team-building company Make Believe Works. “The offer of a hug should always come with a graceful way out. It shouldn’t feel like, Ooh, if I say no, it’s going to feel weird and icky,” he says. You can literally just ask something along the lines of, “Can I hug you?” Swire says quickly asking something like, “Are you a hug person, a fist-bump person, or a wave person?” gives people an easy way to choose their comfort level. Be aware of situational nuances as well, Scott says. In addition to preference and consent, consider whether there are gender or power dynamics in the relationship that could make touch inappropriate. If so, refrain from hugging, she advises. (And if alcohol is involved, it’s a very good idea to stay hands-off, she adds.) When in doubt, Steigler says, just read the room: “If they’re wearing a COVID mask in 2025, don’t hug them.” View the full article

Long John Silver’s is known for its seafood, but it’d like to be better known for its poultry. So much so, that it just swapped the fish in its logo for a chicken. In time for national seafood month, Kentucky-based chain announced that it’s dropping the golden yellow fish illustration for a similarly styled chicken illustration. It’s also adding the words “Chicken” and “Seafood” to its lock-up. “Guests have been telling us for years that our chicken is a best-kept secret,” Long John Silver’s senior vice president of marketing and innovation Christopher Caudill said in a statement. “It’s time we let that secret out.” For now, the new logo shows up on the Long John Silver’s website and social media, and it’s expected to be on the wrap of the chain’s car at the South Point 400, a NASCAR Cup Series stock car race this Sunday in Las Vegas. The company didn’t indicate in its announcement whether the rebrand is permanent, nor whether it will also appear in store and on signage nationwide (Long John Silver’s did not respond to a request for comment). At the very least, it’s the latest example of a promotional brand transformation. Like Maxwell House temporarily rebrading as Maxwell Apartment or Lacoste releasing a limited-edition goat logo, Long John Silver’s new chicken logo is meant to communicate a pointed message: this is a fast food restaurant that does more than crab cakes and surf clams. The rise of fast-food chicken sales Founded in 1969 and named after a pirate on Treasure Island, Long John Silver’s was designed to bring seafood to the landlocked parts of the U.S. But diners in places like Des Moines and Denver aren’t necessarily looking for fish and shrimp these days—they are looking for chicken. Fast-food chicken sales now account for more than $53 billion in annual revenue for U.S. restaurants, according to data from Technomic, a market research firm. You can see its popularity reflected in menu items like Taco Bell’s limited-run chicken nuggets and Wendy’s new chicken tenders. To protect its turf in a time of rising competition, KFC is leaning into its origin story and mascot. For Long John Silver’s, the new look helps promote new chicken menu items, like chicken wraps and Nashville hot chicken, which the seafood the company says it’s testing at a new flagship location in Louisville, Kentucky. Chicken is “part of our heritage,” Caudill said, “so it deserves its rightful place on our logo, our menu, and our guests’ tables,” but he added that chicken is also “a big part of our future.” Previously owned by Yum! Brands, the parent company behind the chains KFC, Taco Bell, and Pizza Hut, Long John Silver’s was acquired for an undisclosed sum in March 2021, according to PitchBook. Long John Silver’s has closed more than 150 restaurants in three years. With the dual focus on seafood and chicken, though, Long John Silver’s is hoping to reverse its decline by making its stores their own self-contained combination locations. For longtime customers still drawn in by its fish and shrimp, the brand will still deliver, but by casting a wider net, it’s hoping to catch some of the growing number of chicken fans too. View the full article