All Activity

It’s Valentine’s Day on Saturday so let’s talk about workplace romance. Did you spot coworkers having a secret affair without realizing how obvious they were being? Did your boss date your dad and try to get you to go to couples therapy with them? Did you spend a ton of time mediating between two employees who hated each other and then they ended up dating? Was your coworker always making out with his girlfriend at work? Did your colleague leave a rambling, drunken message for his secret office girlfriend — but accidentally leave it on the boss’s voicemail instead? Let’s discuss workplace romance gone both wrong and right. The post let’s discuss workplace romance gone wrong … and right appeared first on Ask a Manager. View the full article

January filled our inboxes with productivity advice. Set stretch goals! Think bigger! Dream audaciously! What was conspicuously absent from all that exhortation was any practical guidance on how to move from grand vision to daily action without becoming paralyzed by the enormity of what we’ve committed to. And now, it’s February. Here’s a counterintuitive truth I’ve learned from decades of navigating complex creative challenges: The secret to tackling big, hairy, audacious goals (BHAG) isn’t summoning more willpower or grinding harder. It’s learning to approach complexity the way babies learn to eat solid food: one tiny, digestible bite at a time. I call it the Baby Food Method. Why your brain rebels against big goals When you declare a massive objective- launch a company, write a book, transform your organization’s culture- your brain doesn’t throw a parade. It throws up barriers! Neuroscience tells us that ambiguity and uncertainty trigger the same stress responses as physical threat. Your amygdala can’t distinguish between “I need to escape this predator” and “I have no idea how to execute this strategic pivot.” This is why so many January resolutions collapse by February. The goal itself becomes a source of anxiety rather than motivation. The solution isn’t to dream smaller. It’s to digest smarter. The Baby Food Principle Think about how infants transition from liquid to solid food. No parent hands a six-month-old a steak and says, “Figure it out.” Instead, they puree single ingredients into smooth, manageable portions. Carrots become orange mush. Peas become green paste. One new taste at a time, until gradually the palate, and the digestive system, can handle increasing complexity. Your audacious goals deserve the same graduated approach. The Baby Food Method works in three stages: puree, introduce, and integrate. Stage one: puree the complexity Before you can act on a big goal, you need to break it down into its most fundamental components, the equivalent of pureeing that carrot. This isn’t the same as creating a project plan or building a Gantt chart. It’s more elemental than that. Ask yourself: What are the irreducible units of this ambition? If your goal is to write a book, the puree might be: capture one idea worth exploring. Not “write Chapter One.” Not even “outline the book.” Just: find one compelling thought and get it out of your head. When I left a 16-year academic career to become an entrepreneur, I didn’t start by building a business plan. I started by having one conversation with someone who’d made a similar leap. One conversation. That was my puree. Stage two: introduce new elements gradually Babies don’t eat pureed carrots forever. Once they’ve mastered one food, they’re introduced to another. Then you start combining- carrots with sweet potato, apple with banana. The complexity builds incrementally, and each successful integration expands capacity for the next. Apply this to your BHAG. Once you’ve captured that one idea, introduce the next element: share it with someone whose perspective you trust. Then another: test it against a real-world problem. Each small introduction builds your tolerance for the ambiguity that initially triggered resistance. This is where I see leaders stumble most often. They puree beautifully, break their goal into components, and then they try to swallow everything at once! They mistake “understanding the pieces” for “being ready to execute them simultaneously.” Your nervous system doesn’t work that way. Neither does sustainable progress. Stage three: integrate toward solid food Eventually, a child graduates to actual table food. They’ve developed the motor skills, the digestive capacity, and the palate sophistication to handle complexity. The same progression applies to creative execution. Integration means combining your mastered elements into increasingly ambitious iterations. That one conversation becomes five conversations, which reveal patterns, which suggest a framework, which informs a proposal, which shapes a pilot project. At no point do you face the full weight of “build a business.” You face only the next natural increment of what you’ve already proven you can handle. A practical application Here’s how the Baby Food Method might work for a common goal: transforming your team’s approach to innovation. Puree: Host one 15-minute “what if” session with your team. No agenda beyond exploring one assumption you’ve never questioned. Introduce: Add a second element, perhaps a “So what?” follow-up the next week, where you examine whether any of those “what ifs” have practical relevance. Integrate: Combine the pattern into a monthly rhythm. Then invite a cross-functional colleague to join. Then pilot one small experiment that emerged from the discussions. Twelve months from now, you may find you’ve built an innovation culture. And not because you announced “We’re becoming innovative!” but because you fed your organization one digestible bite at a time. The gift of graduated ambition The Baby Food Method isn’t about lowering your sights. It’s about respecting the neuroscience of how humans actually change. We don’t transform through declarations. We transform through accumulated micro-actions that gradually rewire what we believe we’re capable of. Those early bites build what I call your inventory of courage. Each small success deposits evidence that you can handle complexity. When you eventually face the full weight of your audacious goal, you’re not starting from scratch. You’re drawing on months of proven capability. So remember, don’t just set the big goal. Puree it. What’s the smallest, most digestible first bite you could take this week? Start there. The steak can wait. The puree is where transformation begins. View the full article

As the The President administration prepares to close the Kennedy Center for a two-year renovation, the head of Washington’s performing arts center has warned its staff about impending cuts that will leave “skeletal teams.” In a Tuesday memo obtained by the Associated Press, Kennedy Center President Richard Grenell told staff that “departments will obviously function on a much smaller scale with some units totally reduced or on hold until we begin preparations to reopen in 2028,” promising “permanent or temporary adjustments for most everyone.” Over the next few months, he wrote, department heads would be “evaluating the needs and making the decisions as to what these skeletal teams left in place during the facility and closure and construction phase will look like.” Grenell said leadership would “provide as much clarity and advance notice as possible.” The Kennedy Center is slated to close in early July. Few details about what the renovations will look like have been released since President Donald The President announced his plan at the beginning of February. Neither The President nor Grenell have provided evidence to support claims about the building being in disrepair, and last October, The President had pledged it would remain open during renovations. “Upon the completion of these upgrades, Americans and visitors from all over the world, for generations to come, will enjoy the Center and marvel at its spectacular features and design,” White House press secretary Karoline Leavitt said in a statement Wednesday. It’s unclear exactly how many employees the center currently has, but a 2025 tax filing said nearly 2,500 people were employed during the 2023 calendar year. A request for comment sent to Kennedy Center Arts Workers United, which represents artists and arts professionals affiliated with the center, wasn’t immediately returned. Leading performers and groups have left or canceled appearances since The President ousted the center’s leadership a year ago and added his own name to the building in December. The Washington Post, which first reported about Grenell’s memo, has also cited significant drops in ticket revenue, which—along with private philanthropy—comprises the center’s operating budget. Officials have yet to say whether such long-running traditions as the Mark Twain Award for comedy or the honors ceremony for lifetime contributions to the arts will continue while the center is closed. The Kennedy Center was first conceived as a national cultural facility during the Eisenhower administration in the 1950s. President John F. Kennedy led a fundraising initiative, and the yet-to-be-built center was named in his honor following his assassination. It opened in 1971 and has become a preeminent showcase for theater, music, and dramatic performances, enjoying bipartisan backing until The President’s return to office last year. “This renovation represents a generational investment in our future,” Grenell wrote. “When we reopen, we will do so as a stronger organization—one that honors our legacy while expanding our impact.” —Hillel Italie, AP National Writer View the full article

WhatsApp is taking its commitment to online security a step further with the introduction of a new feature aimed at enhancing user safety in the increasingly complex digital landscape. The messaging platform recently announced its upcoming rollout of “Strict Account Settings,” designed to protect users, particularly high-profile individuals such as journalists and public figures, from sophisticated cyber threats. For small businesses that increasingly rely on digital communication, this added layer of security could be a vital asset. The essence of the Strict Account Settings feature lies in its ability to strengthen user privacy immensely. With a few simple taps, business owners can enforce the most stringent privacy protocols available on WhatsApp. This includes automatic blocking of attachments and media from unknown senders, silencing incoming calls from unfamiliar numbers, and further refining how the app operates in terms of information sharing. Implementing these settings can mitigate the risk of cyber attacks, which can be disruptive and costly for small businesses. “Just like you would in person, we believe you should be able to have private conversations on your devices,” a WhatsApp spokesperson stated. The platform emphasizes that default end-to-end encryption is already in place, but this new feature adds another layer of protection, particularly for users who might be targeted more frequently. For small business owners, the ability to ensure safe communication is critical, allowing them to engage with clients and partners without the fear of falling victim to cyber threats. Accessing the Strict Account Settings is straightforward. Users simply navigate to WhatsApp Settings, click on Privacy, and then select Advanced. This user-friendly approach ensures that even those without extensive tech know-how can manage their account settings effectively. As small business owners can often be overwhelmed with multiple responsibilities, this ease of use facilitates better security without adding complexity to their daily routines. For practical application, small businesses that engage with clients via WhatsApp have much to gain. The function can significantly reduce unsolicited spam and potential phishing attempts, allowing owners to focus more on cultivating relationships rather than fending off threats. Particularly for freelancers and small companies that deal in sensitive information, this feature can prove invaluable in maintaining client confidentiality. However, while the Strict Account Settings present clear advantages, there are also potential challenges that small business owners should consider. The heightened security settings may inadvertently limit communication capabilities. For instance, automatically blocking unknown contacts could hinder outreach efforts or networking opportunities. It’s essential for small business owners to strike a balance between protecting their communications and remaining accessible to customers and industry contacts. Another consideration is the potential tech-savviness required to manage these settings effectively. While the feature is designed for ease of use, some users may find the array of customization options overwhelming. Small business owners might consider training for employees, ensuring everyone is equipped to handle the advanced settings properly. WhatsApp’s latest feature will begin rolling out in the coming weeks, and it promises to further fortify the service’s already robust security framework. Furthermore, small businesses looking to embrace the feature should stay abreast of updates directly from the platform. For details on how to utilize Strict Account Settings effectively, users can refer to WhatsApp’s official guide here. By integrating a proactive security approach into their communication practices, small business owners not only protect themselves but also foster trust with their clientele. As cyber threats continue to evolve, robust measures like WhatsApp’s Strict Account Settings serve as essential tools in a business’s security toolkit, reinforcing the message that customer safety is a priority. Image via Google Gemini This article, "WhatsApp Introduces ‘Strict Account Settings’ for Enhanced User Security" was first published on Small Business Trends View the full article

Interrupt harsh self-talk and replace it with supportive, useful guidance. Accounting ARC With Byron Patrick and Donny Shimamoto Center for Accounting Transformation Go PRO for members-only access to more Center for Accounting Transformation. View the full article

Interrupt harsh self-talk and replace it with supportive, useful guidance. Accounting ARC With Byron Patrick and Donny Shimamoto Center for Accounting Transformation Go PRO for members-only access to more Center for Accounting Transformation. View the full article

Here is a recap of what happened in the search forums today, through the eyes of the Search Engine Roundtable and other search forums on the web. Google Ads launched new AI Mode retailer ads...View the full article

It’s tempting to think that an LLM chatbot can answer any question you pose it, including those about your health. After all, chatbots have been trained on plenty of medical information, and can regurgitate it if given the right prompts. But that doesn’t mean they will give you accurate medical advice, and a new study shows how easily AI’s supposed expertise breaks down. In short, they are even worse at it than I thought. In the study, researchers first quizzed several chatbots about medical information. In these carefully conducted tests, ChatGPT-4o, Llama 3, and Command R+ correctly diagnosed medical scenarios an impressive 94% of the time—though they were able to recommend the right treatment a much less impressive 56% of the time. But that wasn’t a real-world test for the chatbots medical utility. The researchers then gave medical scenarios to 1,298 people, and asked them to use an LLM to figure out what might be going on in that scenario, plus what they should do about it (for example, whether they should call an ambulance, follow up with their doctor when convenient, or take care of the issue on their own). The participants were recruited through an online platform that reported it verifies that research subjects are real humans and not bots themselves. Some participants were in a control group that was told to research the scenario on their own, and not using any AI tools. In the end, the no-AI control group did far better than the LLM-using group in correctly identifying medical conditions, including most serious “red flag” scenarios. How a chatbot with “correct” information can lead people astrayAs the researchers write, “Strong performance from the LLMs operating alone is not sufficient for strong performance with users.” Plenty of previous research has shown that chatbot output is sensitive to the exact phrasing people use when asking questions, and that chatbots seem to prioritize pleasing a user over giving correct information. Even if an LLM bot can correctly answer an objectively phrased question, that doesn’t mean it will give you good advice when you need it. That’s why it doesn’t really matter that ChatGPT can “pass” a modified medical licensing exam—success at answering formulaic multiple choice questions is not the same thing as telling you when you need to go to the hospital. The researchers analyzed chat logs to figure out where things broke down. Here are some of the issues they identified: The users didn’t always give the bot all of the relevant information. As non-experts, the users certainly didn’t know what was most important to include. If you’ve been to a doctor about anything potentially serious, you know they’ll pepper you with questions to be sure you aren’t leaving out something important. The bots don’t necessarily do that. The bots “generated several types of misleading and incorrect information.” Sometimes they ignored important details to narrow in on something else; sometimes they recommended calling an emergency number but gave the wrong one (such as an Australian emergency number for U.K. users). Responses could be drastically different for similar prompts. In one example, two users gave nearly identical messages about a subarachnoid hemorrhage. One response told the user to seek emergency care; the other said to lie down in a dark room. People varied in how they conversed with the chatbot. For example, some asked specific questions to constrain the bot’s answers, but some let the bot take the lead. Either method could introduce unreliability into the LLM's output. Correct answers were often grouped with incorrect answers. On average, each LLM gave 2.21 answers for the user to choose from. People understandably did not always choose correctly from those options. Overall, people who didn't use LLMs were 1.76 times more likely to get the right diagnosis. (Both groups were similarly likely to figure out the right course of action, but that's not saying much—on average, they only got it right about 43% of the time.) The researchers described the control group as doing "significantly better" at the task. And this may represent a best-case scenario: the researchers point out that they provided clear examples of common conditions, and LLMs would likely do worse with rare conditions or more complicated medical scenarios. They conclude: “Despite strong performance from the LLMs alone, both on existing benchmarks and on our scenarios, medical expertise was insufficient for effective patient care.” Chatbots are a risk for doctors, tooPatients may not know how to talk to an LLM, or how to vet its output, but surely doctors would fare better, right? Unfortunately, people in the medical field are also using AI chatbots for medical information in ways that create risks to patient care. ECRI, a medical safety nonprofit, put the misuse of AI chatbots in the number one spot on its list of health technology hazards of 2026. While the AI hype machine is trying to convince you to give ChatGPT your medical information, ECRI correctly points out that it’s wrong to think of these chatbots as having human personalities or cognition: “While these models produce humanlike responses, they do so by predicting the next word based on large datasets, not through genuine comprehension of the information.” ECRI reports that physicians are, in fact, using generative AI tools for patient care, and that research has already shown the serious risks involved. Using LLMs does not improve doctors’ clinical reasoning. LLMs will elaborate confidently on incorrect details included in prompts. Google’s Med-Gemini model, created for medical use, made up a nonexistent body part whose name was a mashup of two unrelated real body parts; Google told a Verge reporter that the mistake was a “typo.” ECRI argues that “because LLM responses often sound authoritative, the risk exists that clinicians may subconsciously factor AI-generated suggestions into their judgments without critical review.” Even in situations that don’t seem like life-and-death cases, consulting a chatbot can cause harm. ECRI asked four LLMs to recommend brands of gel that could be used with a certain ultrasound device on a patient with an indwelling catheter near the area being scanned. It’s important to use a sterile gel in this situation, because of the risk of infection. Only one of the four chatbots identified this issue and made appropriate suggestions; the others just recommended regular ultrasound gels. In other cases, ECRI’s tests resulted in chatbots giving unsafe advice on electrode placement and isolation gowns. Clearly, LLM chatbots are not ready to be trusted to keep people safe when seeking medical care, whether you’re the person who needs care, the doctor treating them, or even the staffer ordering supplies. But the services are already out there, being widely used and aggressively promoted. (Their makers are even fighting in the Super Bowl ads.) There’s no good way to be sure these chatbots aren’t involved in your care, but at the very least we can stick with good old Dr. Google—just make sure to disable AI-powered search results. View the full article

In Google AI Overviews and LLM-driven retrieval, credibility isn’t enough. Content must be structured, reinforced, and clear enough for machines to evaluate and reuse confidently. Many SEO strategies still optimize for recognition. But AI systems prioritize utility. If your authority can’t be located, verified, and extracted within a semantic system, it won’t shape retrieval. This article explains how authority works in AI search, why familiar SEO practices fall short, and what it takes to build entity strength that drives visibility. Why traditional authority signals worked – until they didn’t For years, SEOs liked to believe that “doing E-E-A-T” would make sites authoritative. Author bios were optimized, credentials showcased, outbound links added, and About pages polished, all in hopes that those signals would translate into authority. In practice, we all knew what actually moved the needle: links. E-E-A-T never really replaced external validation. Authority was still conferred primarily through links and third-party references. E-E-A-T helped sites appear coherent as entities, while links supplied the real gravitas behind the scenes. That arrangement worked as long as authority could be vague and still rewarded. It stops working when systems need to use authority, not just acknowledge it. In AI-driven retrieval, being recognized as authoritative isn’t enough. Authority still has to be specific, independently reinforced, and machine-verifiable, or it doesn’t get used. Being authoritative but not used is like being “paid” with experience. It doesn’t pay the bills. Your customers search everywhere. Make sure your brand shows up. The SEO toolkit you know, plus the AI visibility data you need. Start Free Trial Get started with How AI systems calculate authority Search no longer operates on a flat plane of keywords and pages. AI-driven systems rely on a multi-dimensional semantic space that models entities, relationships, and topical proximity. In that semantic space, entities function much like celestial bodies in physical space, discrete objects whose influence is defined by mass, distance, and interaction with others. E-E-A-T still matters, but the framework version is no longer a differentiator. Authority is now evaluated in a broader context that can’t be optimized with a handful of on-page tasks. In AI Overviews, ChatGPT, Claude, and similar systems, visibility doesn’t hinge on prestige or brand recognition. Those are symptoms of entity strength, not its source. What matters is whether a model can locate your entity within its semantic environment and whether that entity has accumulated enough mass to exert influence. That mass isn’t decorative. It’s built through third-party citations, mentions, and corroboration, then made machine-legible through consistent authorship, structure, and explicit entity relationships. Models don’t trust authority. They calculate it by measuring how densely and consistently an entity is reinforced across the broader corpus. Smaller brands don’t need to shine like legacy publishers. In a semantic system, apparent size and visibility don’t determine influence. Density does. In astrophysics, some planets appear enormous yet exert surprisingly weak gravity because their mass is spread thinly. Others are much smaller, but dense enough to exert stronger pull. AI visibility works the same way. What matters isn’t how large your brand appears to humans, but how concentrated and reinforced your authority is in machine-readable form. Dig deeper: From SEO to algorithmic education: The roadmap for long-term brand authority The E-E-A-T misinterpretation problem The problem with E-E-A-T was never the concept itself. It was the assumption that trustworthiness could be meaningfully demonstrated in isolation, primarily through signals a site applied to itself. Over time, E-E-A-T became operationalized as visible, on-page indicators: author bios, credentials, About pages, and lightweight citations. These signals were easy to implement and easy to audit, which made them attractive. They created the appearance of rigor, even when they did little to change how authority was actually conferred. That compromise held when search systems were willing to infer authority from proxies. It breaks down in AI-driven retrieval, where authority must be explicitly reinforced, independently corroborated, and machine-verifiable to carry weight. Surface-level trust markers don’t fail because models ignore them. They fail because they don’t supply the external reinforcement required to give an entity real mass. In a semantic system, entities gain influence through repeated confirmation across the broader corpus. On-site signals can help make an entity legible, but they don’t generate density on their own. Compliance isn’t comprehension, and E-E-A-T as a checklist doesn’t create gravitational pull. In human-centered search, these visible trust cues acted as reasonable stand-ins. In LLM retrieval, they don’t translate. Models aren’t evaluating presentation or intent. They’re evaluating semantic consistency, entity alignment, and whether claims can be cross-verified elsewhere. E-E-A-T isn’t outdated. It’s incomplete. It explains why humans might trust you. Applying E-E-A-T principles only within your own site won’t create the mass that machines need to recognize, align with, and prioritize your entity in a retrieval system. AI doesn’t trust, it calculates Human trust is emotional. Machine trust is statistical. In practice: LLMs prioritize clarity. Ambiguous writing reduces confidence. They reward clean extraction. Lists, tables, and focused paragraphs are easiest to reuse. They cross-verify facts. Redundant, consistent statements across multiple sources appear more reliable than a single sprawling narrative. Retrieval models evaluate confidence, not charisma. Structural decisions such as headings, paragraph boundaries, markup, and lists directly affect how accurately a model can map content to a query. This is why ChatGPT and AI Overview citations often come from unfamiliar brands. It’s also why brand-specific queries behave differently. When a query explicitly names a brand or entity, the model isn’t navigating the galaxy broadly. It’s plotting a short, precise trajectory to a known body. With intent tightly constrained and only one plausible source of truth, there’s far less risk of drifting toward adjacent entities. In those cases, the system can rely directly on the entity’s own content because the destination is already fixed. The models aren’t “discovering” hidden experts. They’re rewarding content whose structure reduces uncertainty. The semantic galaxy: How entities behave like bodies LLMs don’t experience topics, entities, or websites. They model relationships between representations in a high-dimensional semantic space. That’s why AI retrieval is better understood as plotting a course through a system of interacting gravitational bodies rather than “finding” an answer. Influence comes from mass, not intention. In embedding-based retrieval, entities behave like bodies in space, as demonstrated by Karpukhin et al. in their 2020 EMNLP paper on dense passage retrieval. Over time, citations, mentions, and third-party reinforcement increase an entity’s semantic mass. Each independent reference adds weight, making that entity increasingly difficult for the system to ignore. Queries move through this space as vectors shaped by intent. As they pass near sufficiently massive entities, they bend. The strongest entities exert the greatest gravitational pull, not because they are trusted in a human sense, but because they are repeatedly reinforced across the broader corpus. Extractability doesn’t create that gravity. It determines what happens after attraction occurs. An entity can be massive enough to warp trajectories and still be unusable if its signals aren’t machine-legible, like a planet with enough gravity to draw a spacecraft in but no viable way to land. Authority, in this context, isn’t belief. It’s gravity, the cumulative pull created by repeated, independent reinforcement across the wider semantic system. Entity strength vs. extractability Classic SEO emphasized backlinks and brand reputation. AI search desires entity strength for discovery, but demands clarity and semantic extractability to be included. Entity strength – your connections across the Knowledge Graph, Wikidata, and trusted domains – still matters and arguably matters more now. Unfortunately, no amount of entity strength helps if your content isn’t machine-parsable. Consider two sites featuring recognized experts: One uses clean headings, explicit definitions, and consistent links to verified profiles. The other buries its expertise inside dense, unstructured paragraphs. Only one will earn citations. LLMs need: One entity per paragraph or section. Explicit, unambiguous mentions. Repetition that reinforces relationships (“Dr. Jane Smith, cardiologist at XYZ Clinic”). Precision makes authority extractable. Extractability determines whether existing gravitational pull can be acted on once attraction has occurred, not whether that pull exists in the first place. Get the newsletter search marketers rely on. See terms. Structure like you mean it: Abstract first, then detail LLM retrieval is constrained by context windows and truncation limits, as outlined by Lewis et al. in their 2020 NeurIPS paper on retrieval-augmented generation. Models rarely process or reuse long-form content in its entirety. If you want to be cited, you can’t bury the lede. LLMs read the beginning, but then they skim. After a certain number of tokens, they truncate. Basically, if your core insight is buried in paragraph 12, it’s invisible. To optimize for retrieval: Open with a paragraph that functions as its own TL;DR. State your stance, the core insight, and what follows. Expand below the fold with depth and nuance. Don’t save your best material for the finale. Neither users nor models will reach it. Dig deeper: Organizing content for AI search: A 3-level framework Stop ‘linking out,’ start citing like a researcher The difference between a citation and a link isn’t subtle, but it’s routinely misunderstood. Part of that confusion comes from how E-E-A-T was operationalized in practice. In many traditional E-E-A-T playbooks, adding outbound links became a checkbox, a visible, easy-to-execute task that stood in for the harder work of substantiating claims. Over time, “cite sources” quietly degraded into “link out a few times.” A bad citation looks like this: A generic outbound link to a blog post or company homepage offered as vague “support,” often with language like “according to industry experts” or “SEO best practices say.” The source may be tangentially related, self-promotional, or simply restating opinion, but it does nothing to reinforce your entity’s factual position in the broader semantic system. A good citation behaves more like academic referencing. It points to: Primary research. Original reporting. Standards bodies. Widely recognized authorities in that domain. It’s also tied directly to a specific claim in your content. The model can independently verify the statement, cross-reference it elsewhere, and reinforce the association. The point was never to just “link out.” The point was to cite sources. Engineering retrieval authority without falling back into a checklist The patterns below aren’t tasks to complete or boxes to tick. They describe the recurring structural signals that, over time, allow an entity to accumulate mass and express gravity across systems. This is where many SEOs slip back into old habits. Once you say “E-E-A-T isn’t a checklist,” the instinct is to immediately ask, “Okay, so what’s the checklist?” But engineering retrieval authority isn’t a list of tasks. It’s a way of structuring your entire semantic footprint so your entity gains mass in the galaxy the models navigate. Authority isn’t something you sprinkle into content. It’s something you construct systematically across everything tied to your entity. Make authorship machine-legible: Use consistent naming. Link to canonical profiles. Add author and sameAs schema. Inconsistent bylines fragment your entity mass. Strengthen your internal entity web: Use descriptive anchor text. Connect related topics the way a knowledge graph would. Strong internal linking increases gravitational coherence. Write with semantic clarity: One idea per paragraph. Minimize rhetorical detours. LLMs reward explicitness, not flourish. Use schema and LLMS.txt as amplifiers: They don’t create authority. They expose it. Audit your “invisible” content: If critical information is hidden in pop-ups, accordions, or rendered outside the DOM, the model can’t see it. Invisible authority is no authority. See the complete picture of your search visibility. Track, optimize, and win in Google and AI search from one platform. Start Free Trial Get started with From rocket science to astrophysics E-E-A-T taught us to signal trust to humans. AI search demands more: understanding the forces that determine how information is pulled into view. Rocket science gets something into orbit. Astrophysics navigates and understands the systems it moves through once there. Traditional SEO focused on launching pages—optimizing, publishing, promoting. AI SEO is about mass, gravity, and interaction: how often your entity is cited, corroborated, and reinforced across the broader semantic system, and how strongly that accumulated mass influences retrieval. The brands that win won’t shine brightest or claim authority loudest, nor will they be no-name sites simulating credibility with artificial corroboration and junk links. They’ll be entities that are dense, coherent, and repeatedly confirmed by independent sources—entities with enough gravity to bend queries toward them. In an AI-driven search landscape, authority isn’t declared. It’s built, reinforced, and made impossible for machines to ignore. Dig deeper: User-first E-E-A-T: What actually drives SEO and GEO View the full article

Ukrainian skeleton athlete Vladyslav Heraskevych, a likely medal contender at the Milan Cortina Games, was barred from racing Thursday after refusing a last-minute plea from the International Olympic Committee (IOC) to not use a helmet that honors more than 20 athletes and coaches killed in his country’s war with Russia. The decision came roughly 45 minutes before the start of the competition and ended a three-day saga where Heraskevych knew he was risking being pulled from the Games by wearing the helmet, one that the IOC says breaks rules against making statements on the field of play. The International Bobsleigh and Skeleton Federation (IBSF) said his decision to wear the helmet was “inconsistent with the Olympic Charter and Guidelines on Athlete Expression.” He wore the helmet in training, but the IOC asked for him to wear a different helmet in races. It offered concessions, such as wearing a black armband or letting him display the helmet once he was off the ice. “I believe, deeply, the IBSF and IOC understand that I’m not violating any rules,” Heraskevych said. “Also, I would say (it’s) painful that it really looks like discrimination because many athletes already were expressing themselves. . . . They didn’t face the same things. So, suddenly, just the Ukrainian athlete in this Olympic Games will be disqualified for the helmet.” IOC President Kirsty Coventry, who was slated to be in Cortina d’Ampezzo to see Alpine skiing, went to the sliding center instead to meet Heraskevych. She was waiting at the top of the track when he arrived around 8:15 a.m., and they met privately. After about 10 minutes, Coventry was unable to change Heraskevych’s mind. “We didn’t find common ground in this regard,” Heraskevych said. Tears rolled down Coventry’s face after the meeting. The Olympic champion swimmer made clear that she wanted a different outcome, and the IOC said the decision was made with regret. “As you’ve all seen over the last few days, we’ve allowed for Vladyslav to use his helmet in training,” Coventry said. “No one, no one—especially me—is disagreeing with the messaging. The messaging is a powerful message. It’s a message of remembrance. It’s a message of memory and no one is disagreeing with that. The challenge that we are facing is that we wanted to ask or come up with a solution for just the field of play.” Coventry and Heraskevych agreed that the helmet isn’t clearly visible during races anyway, given that sliders are zipping down the icy chute at around 120 kilometers per hour (75 miles per hour). That, the IOC hoped, was the window to a compromise. Heraskevych would not budge. “Sadly, we’ve not been able to come to that solution,” Coventry said. “I really wanted to see him race today. It’s been an emotional morning.” Heraskevych said he would appeal to the Court of Arbitration for Sport, but the race went on without him. The first two runs were Thursday, the last two are Friday. Regardless of what CAS says, if anything, his chance to race in these Games is gone. The IOC is letting him keep his credential, meaning he can remain at the Olympics as an athlete—just not a competing one. About a dozen Russian athletes are being allowed to compete at the Olympics as neutral individuals along with seven Belarusians. They are not allowed to compete under their national flag or anthem. Heraskevych has spoken out several times about why he believes they shouldn’t be at the Olympics and said the IOC’s decision “plays along with Russian propaganda.” The decision drew immediate condemnation from officials in Ukraine and some athletes. “Sport shouldn’t mean amnesia, and the Olympic movement should help stop wars, not play into the hands of aggressors,” Ukraine President Volodymyr Zelenskyy wrote on social media. “Unfortunately, the decision of the International Olympic Committee to disqualify Ukrainian skeleton racer Vladyslav Heraskevych says otherwise.” “Disqualified. I think that’s enough to understand what the modern IOC really is and how it disgraces the idea of the Olympic movement,” added Ukrainian skier Kateryna Kotsar on Instagram. “Vladyslav Heraskevych, for us and for the whole world, you’re a champion. Even without starting.” The IOC had sided with Ukraine’s top slider before. When he displayed a “No war in Ukraine” sign after his fourth and final run at the 2022 Beijing Olympics, the IOC said he was simply calling for peace and did not find him in violation of the Olympic charter. This time, Heraskevych said he believes there are inconsistencies in how the IOC decides what statements are allowed. Among those he cited: U.S. figure skater Maxim Naumov bringing a photo of his late parents—former pairs world champions Evgenia Shishkova and Vadim Naumov, who were among the 67 people killed in a plane crash on January 29, 2025—to the kiss-and-cry area after his skate in Milan this week, and Israeli skeleton athlete Jared Firestone’s decision to appear at the opening ceremony wearing a kippah that bore the names of 11 Israeli athletes and coaches killed in the 1972 attack during the Munich Games. “A competitor literally placed the memory of the dead on his head to honor them,” Heraskevych wrote on Instagram. “I frankly do not understand how these two cases are fundamentally different.” Firestone said he admired Heraskevych. “I think he’s a man with strong values,” he said. In Milan, IOC spokesman Mark Adams said if athletes were allowed to display messaging without restrictions on the field of play “that would lead to a chaotic situation.” “Sport without rules cannot function. . . . If we have no rules, we have no sport,” Adams said. Heraskevych was fourth at the world championships last year and was among the fastest in training leading into the Olympic races. A medal was certainly within reach, but to Heraskevych, the helmet mattered more. “The International Olympic Committee destroyed our dreams,” said Mykhailo Heraskevych, the slider’s coach and father. “It’s not fair.” AP journalists Julia Frankel, Vasilisa Stepanenko and Graham Dunbar contributed. AP Olympics: https://apnews.com/hub/milan-cortina-2026-winter-olympics —Tim Reynolds, AP Sports Writer View the full article

US intelligence agency seeks to tap into frustration over extensive purges at People’s Liberation ArmyView the full article

Vladyslav Heraskevych wanted to wear helmet honouring compatriots killed in war during skeleton eventView the full article

Visibility in AI answers is gated long before ranking, and this article explains how Spam, Safety, Intent, and Trust decide who gets through. The post The Classifier Layer: Spam, Safety, Intent, Trust Stand Between You And The Answer appeared first on Search Engine Journal. View the full article

We may earn a commission from links on this page. I'd never owned a really good pair of headphones; it's just not something I've really cared about. But the JBL Tour One M3s I recently acquired changed my mind forever. (Our resident audio expert Daniel Oropeza went in depth about these headphones in his review, which you should read.) JBL Tour One M3 Smart Tx Wireless Noise Cancelling Headphones With Audio Transmitter $449.95 at Amazon Shop Now Shop Now $449.95 at Amazon Music is better when it sounds betterI've always taken a punk-rock approach to sound gear—cheap and loud has been good enough for me—but using these headphones non-stop for the past couple of weeks proves I've been very wrong. Music is better when played through decent equipment. There's so much more there, even in songs I've listened to a million times: I can finally make out what's actually being said in the "party chatter" that provides atmosphere in Marvin Gaye's "What's Going On," and who knew there was so much going on in The Dead Boys "Sonic Reducer?" And the spatial audio? Forget it: Hearing different instruments from different parts of 3D space is amazing. These headphones have me thinking seriously about stereo separation, constantly messing with the EQ, and turning my nose up to every format that isn't lossless. I'm listening to damn jazz. What's even happening? Silence is better when it's truly silent Okay, I know active noise-cancelling has been around for 20 years, but I never cared about it—most of the music I like is mostly noise, so why would I want to cancel it?—but it's for cancelling all that other noise that surrounds us. These are perfect for an airplane or car trip but also for just wearing around. I had no idea how much ambient sound I'm swimming in all day at my home office—the fridge running, the cars on the road, the wind—all gone in an instant. Nothing to hear but silence and tinnitus (from too much punk rock). What the audio transmitter does Credit: Stephen Johnson When I first opened the box and saw the smart transmitter/controller thing that comes with these phones, I was like, "What's this dumb thing?" But it turns out it's not dumb. It's a Smart Tx Audio Transmitter. You can plug it into almost anything audio and it will wirelessly stream 24-bit audio. Plug the AUX-to-USB-C cable into the beat-up jack at the gym, or an airplane’s headphone jack ,and you can listen with full noise-canceling and high-quality audio. (Now that I'm an audiophile, this is important to me.) It's also a touch screen controller so you can mess around with the EQ to hear Art Pepper's dulcet saxophone tone without taking your phone out, and trust me, you haven't heard Art Pepper if it's not lossless and tuned with JBL's "personal sound amplification." I mean, you might as well be listening to The Dead Boys or something. It comes with a traveling caseIn my old life, I would have left the Smart Tx Audio Transmitter on a bus, but these phones come with a little carrying case where all my little cords have places to live, and I put my audio transmitter right where it goes, because I never want to be burdened with inferior audio again. I could go on about these headphones, but I've realized that air is an imperfect medium for sound vibrations, so I'm going to sit and stare at the sheet music of Coltrane's A Love Supreme and listen to pure theory. View the full article

Central bank’s research undercuts Donald The President’s claims that foreign companies will pay for levies View the full article

A little known security feature on iPhones is in the spotlight after it stymied efforts by U.S. federal authorities to search devices seized from a reporter. Apple’s Lockdown Mode recently prevented FBI agents from getting into Washington Post reporter Hannah Natanson’s iPhone. Agents seized the phone, as well as two MacBooks and other electronic devices, when they searched Natanson’s home last month as part of an investigation into a Pentagon contractor accused of illegally handling classified information. But the FBI reported that its Computer Analysis Response Team “could not extract” data from the iPhone because it was in Lockdown Mode, according to a court filing. So what is Lockdown Mode? Here’s a rundown of how it works and how to use it: Highest security Apple says Lockdown Mode is an “optional, extreme” protection tool designed to guard against “extremely rare and highly sophisticated cyberattacks.” It’s not for everyone, but instead for “very few individuals” who could be targeted by digital threats because of who they are or what they do. “Most people will never be targeted by attacks of this nature,” Apple’s support page says. It’s available in Apple’s newer operating systems, including iOS 16 and macOS Ventura. It works by putting strict security limits on some apps and features, or even making some unavailable, to reduce the areas that advanced spyware can attack. It also restricts the kinds of browser technologies that websites can use and limits photo sharing. Can Apple turn it off? Apple has previously rejected U.S. government requests to build so-called backdoor access for its devices. In 2016, Apple refused a request by authorities to help bypass lockscreen security for an encrypted iPhone belonging to a shooter who carried out a terrorist attack in San Bernardino, California. The company also declined to add an ability to input passcodes electronically, which would make it possible to carry out “brute force” attempts to guess the combination using computers. “It would be wrong to intentionally weaken our products with a government-ordered backdoor,” Apple said in explaining its decision. How to turn on Lockdown Mode Make sure your iPhone, iPad, or MacBook has been updated. You’ll have to turn the feature on separately for each of your Apple devices. On your iPhone, go to Settings, then to the Privacy and Security section, scroll down to the bottom and tap on Lockdown Mode. Enter your passcode—not a facial or fingerprint scan—to activate it. The device will restart and then you’ll again have to use your passcode to unlock it. On MacBooks, follow a similar procedure from the System Settings menu. Apple recommends that you switch it on for all of the company’s devices that you own. Better than biometrics You might assume that requiring facial or fingerprint recognition to unlock your phone is good enough to protect it from snooping. But experts say passcodes are better than biometrics at protecting your devices from law enforcement, because they could compel you to unlock your device by holding your phone up to your face or forcing you to put your finger on the scanner. FBI agents told Natanson that they “could not compel her to provide her passcodes,” but the warrant they used to execute the search did give them the authority “to use Natanson’s biometrics, such as facial recognition or fingerprints, to open her devices.” According to a court filing, Natanson said she didn’t use biometrics to lock her devices but agents were ultimately able to unlock her MacBook with her finger. This is how it affects your phone Apple says some apps and features will work differently when Lockdown Mode is on. Some websites might load slowly or not work properly, and some images and web fonts could be missing because they block “certain complex web technologies.” In Messages, most types of attachments are blocked, and links and link previews won’t be available. Incoming FaceTime calls are blocked unless it’s from a number you’ve called in the past month. In Photos, location information is stripped from shared photos and shared albums are removed from the app. Focus mode won’t work normally. There are also tighter restrictions on connecting your phone or computer to unsecure Wi-Fi networks or to other computers and accessories. When I tried it out on my own iPhone, some apps warned me that certain functions might not work. I noticed that one of my news apps started using a different font and photos on some websites didn’t appear, replaced by a question mark. The biggest disruption happened when I went to the gym, which involved using a web-based check-in system to scan a QR code. But my phone camera wouldn’t work so I had to turn off Lockdown Mode in order to get in. To be sure, my iPhone’s standalone Code Scanner app still worked, so the problem seemed to center on using a website to activate the camera. Turn it off Follow the same procedure outlined above that you used to turn on Lockdown Mode. You’ll need to enter your passcode and the phone will perform a restart. Is there a tech topic that you think needs explaining? Write to us at onetechtip@ap.org with your suggestions for future editions of One Tech Tip. —Kelvin Chan, AP Business Writer View the full article

Airport lounges used to be a perk. In 2026, they are a battleground. American Express is refreshing Centurion Lounges and adding faster Sidecar formats. Chase is experimenting with champagne parlors and hyperlocal chef partnerships in its Sapphire Lounges. Citi is back in the ultra-premium card game. And Capital One, the relative newcomer, is making a different bet. Instead of building another lounge at LaGuardia Airport, it built a restaurant. The new Capital One Landing at Terminal B is a 12,500-square-foot, chef-driven dining space created with José Andrés. It has a 2,250-square-foot working kitchen, the largest in the terminal, and a menu built around Spanish tapas cooked from scratch. It looks more like a stand-alone dining destination than a cardholder waiting room. That is the point. From lounges to ‘landings’ Capital One’s airport strategy started with lounges at Dallas Fort Worth International Airport, Washington Dulles International Airport, Denver International Airport, and Ronald Reagan Washington National Airport. Those spaces became known for local partnerships, individually plated food made on site, and drinks from neighborhood breweries and distilleries. The idea was that even if you never left the airport, you would still get a sense of the city. The Landing concept is an evolution of that thinking. Instead of adapting lounge food to feel more local, Capital One asked what would happen if the airport space felt like a real restaurant first and a lounge second. “When we went to the lounge space, we similarly felt that lounges were becoming totally cookie-cutter . . . They were all kind of buffets. The drinks were the same, lounge to lounge,” Matt Knise, SVP of premium products and travel at Capital One, tells Fast Company. The Landing is Capital One’s answer to that sameness. “We felt that there was room for a restaurant type experience, so you could still sit somewhere a little bit more comfortable and put your stuff down and get a really quality restaurant, quality bite of food and still make it to your gate on time,” he says. Why a chef matters in a card war To make that work, Capital One sought out someone who could actually run a restaurant inside an airport. “We needed a partner on the other side of the equation, the hospitality and food side of the equation, who had the same passion about solving what we saw, and we found that with José and team,” Knise says. For Andrés, the project feels personal. “For me, in a way, it’s kind of a dream,” he says. “Capital One helped me build my own kitchen away from home.” That kitchen is not decorative. It is central to the pitch. “What makes this different—this Landing and this place—is that we’re making the food from scratch,” he says. “It’s not sitting there three, four hours in a place waiting for you to arrive.” In fact, Capital One built Andrés a kitchen with top-of-the-line equipment akin to what you would find in a high-end restaurant outside the terminal. Tapas for travelers on a clock The menu leans into Spanish tapas for a reason. “I believe in smaller portions and I believe in in the rainbow of possibilities,” says Andrés. “I don’t know a lot of concepts that are quicker than tapas.” Guests can grab plates from the tapas bar, order via QR code, or take items to go. Dishes like croquetas, the bikini sandwich, cheeses, and flauta bread are designed to be eaten quickly or slowly. Knise says the design balances both. “We felt deeply that a great dining experience and a relatively quick dining experience, those two things did not have to be mutually exclusive,” he says. “It’s a bit of a choose your own adventure.” Capital One is also leaning into what it calls Daily Rituals. At LGA, that includes tableside martinis, vermouth carts with garnishes and pintxos, oysters during select windows, and dessert carts. The airport as the new loyalty showroom In the fight for affluent travelers, the airport has become the most visible showroom for what a premium card actually promises. For Capital One. the space itself is part of the strategy. Skylights, a terrace filled with greenery, floor to ceiling windows overlooking the Manhattan skyline, and a 30 foot mural by Queens artist Amrita Marino all reinforce that this is meant to feel like a place, not a waiting area. The thinking is straightforward. If the first memorable part of your trip happens before you even board the plane, and it happens inside a space tied directly to your credit card, the card stops feeling like a payment tool and starts feeling like part of the journey. For years, perks lived on paper. Points multipliers, statement credits, travel portals, concierge access. Useful, but abstract. You only felt the value when you booked a flight or scanned a benefits page. Lounges changed that. They turned benefits into something physical you could walk into, sit inside, and experience before your trip even began. Now that every major card issuer is investing in lounges, the competition has moved past who has a lounge and into what that lounge feels like. Is it a place to grab a snack, or is it somewhere you plan to arrive early for? Does it feel interchangeable with every other airport space, or does it feel like a destination tied to the city you are in? Knise puts it this way: “We want a manifestation of what we stand for as a brand . . . we want them to leave and go, Oh, wow. Capital One is a company that totally has my back and is innovating to make my life easier.” For Andrés, the payoff shows up in a different way. Not in brand metrics or cardholder retention, but in what travelers say as they walk out. “I’ve had people say ‘I cannot wait to travel again so I can come back to eat the croqueta. [That] something like this happens in an airport. It’s very special.” View the full article

Want to use Discord from next month? You’ll have to hand over a photo of your ID or a scan of your face to verify you’re of age. It’s part of a new process introduced by the chat app aimed at ensuring no one underage is using the platform. All new and existing users, the company says, will be given a “teen-appropriate experience” by default, including content filtering and limited access to spaces that host adult content. To regain the experience they previously had, users will need to prove their age through one of several options, including video selfies or sharing a photo of an identity document. (Discord did not immediately respond to Fast Company’s request for comment.) Users have reacted pretty unfavorably toward the proposal, with many saying they’re unhappy about sharing personal data with Discord, which faced a massive data breach reported just months ago. In that instance, ID photos of 70,000 users were potentially leaked after a cyberattack. (Discord said the incident involved a third-party customer support provider, not its own systems.) What worries privacy groups most is not just Discord’s plan, but the precedent it sets for other platforms. “It’s a reflection of growing concerns over the erosion of privacy online, and the slippery slope of mandating identity and age verification across the internet, making these systems a prime tool for surveillance and tracking,” says Rin Alajaji, associate director of state affairs at the Electronic Frontier Foundation (EFF). “Mandating age verification on a platform like Discord directly undermines the platform and the internet’s long-standing culture of anonymity.” There are also broader concerns about the growing requirements for users to prove who they are and how old they are to do things they previously did without scrutiny. U.K. polling suggests that while people may support age checks in principle, they are far more reluctant to hand over ID or facial footage in practice. Willingness to comply drops significantly when specifics are involved, and the public is split on the use of face video and photographic ID. Only 23% of Brits say they’d hand over ID to access discussion forums like Discord. That same tension appears in the U.S.: people want children protected online, but are less comfortable when those protections infringe on their own rights. Elinor Carmi, a senior lecturer in data politics and data justice at City St George’s, University of London, argues the backlash isn’t just about biometrics or ID checks in the abstract, but about whether people believe this kind of gatekeeping will actually work. “People just don’t think that age verification actually works,” she says, adding that users see policymakers and platforms reaching for a patch rather than a fix. “The social media platforms and the regulators are basically saying, ‘We have an issue, but let’s not deal with it. And let’s try to solve it in the most technical and easy solution, which is obviously also not working, because you can obviously fake it.’” There’s also fatigue with the concept, with users feeling the burden is being shifted onto them, including teenagers as well as adults, rather than platforms. And beyond that, there are worries about the consequences of a “papers, please” era of the web. “For many users—especially vulnerable groups like LGBTQ+ youth—having a space to connect without revealing their real identities is essential for safety and free expression,” says EFF’s Alajaji. “Age verification puts that at risk, forcing users to choose between privacy and participation.” She calls the decision to ask people to hand over more personal data after some users already lost theirs in last year’s Discord-linked data breach “reckless.” People are wary because they’ve been burned before and know they’re being asked to trade their likeness and other sensitive information simply to participate online. “Many users are understandably alarmed about their data being exposed or misused,” Alajaji says. View the full article

Valentine’s Day may seem romantic, but to candy companies, it’s serious business. Our annual ode to St. Valentine is one of the most important and competitive days on candy company calendars, and every year, confectioners roll out special-edition heart-shaped chocolate bars and other product innovations to capture consumers’ dollars (nevermind hearts). When it comes to speaking to modern courtship, though, one candy brand has a unique leg up on the competition—and it’s built into the candy itself. Sweethearts were designed to be updated. The pastel-colored conversation hearts stay relevant year over year because their embossed messages can be easily and quickly updated, transforming a generic shape into a crunchy candy canvas that’s adaptable to the moment. That makes the face of these tiny hearts some of the most valuable real estate in the Valentine’s Day candy landscape, because the right quip could convert a passerby into a sale. And this year, their newest messages are all about the struggles of dating in today’s economy. Sweethearts’s latest sayings have been dubbed “Love in This Economy” after an online survey that the brand’s owner, the family-owned, Ohio-based Spangler Candy Company, conducted last December of 2,000 Gen Z and millennials who are single, casually dating, or in a serious relationship, making an edible sort of consumer sentiment index. The candy company’s survey found 80% of respondents said the economy was impacting their Valentine’s Day plans. Their new two-line messages, then—”Split Rent,” “Share Logn,” “Car Poll,” “Buy N Bulk,” and “Cook For 2″—reflect the realities of dating and courtship during a time of high prices, persistent inflation, and low consumer confidence. But just because the company has introduced new messages doesn’t mean it’s abandoned more evergreen ones. “We’re careful about evolving the sayings because Sweethearts must be both nostalgic and new,” Spangler Candy Company vice president of marketing Evan Brock tells Fast Company. Classic messages like “Marry Me,” “Cutie Pie,” and “Ooo La La” are included every year, while new sayings reflect how people express affection and connection today, she says. “Our role is to strike a balance between enduring tradition and modern expression.” Wiki Commons Some of the original messages stamped into the first Sweethearts from 1902 were “Be Mine,” “Be True,” and “Kiss Me,” according to Smithsonian Magazine. But over the years, the candy has been updated with the times. “Fax Me” turned into “Text Me,” and in 2024, the candies were purposefully misprinted to symbolize the confusion and mixed messages of situationships. Unlike M&Ms or Skittles, which use the surface of their candy shells to display their visual brands, Sweethearts has more flexibility to adapt to culture. But even so, it’s thoughtful about adding new sayings. Embossing the hearts is a highly coordinated process that involves engraving new phrases onto custom-made printing plates that will stamp the words onto each individual candy. There’s no understating how important Valentine’s Day is for candy sales. Along with Easter, Halloween, and the winter holiday season, the four holidays generate a whopping 62% of annual sales for the $54 billion confectionery industry, according to the National Confectioners Association. For Sweethearts, it’s practically the whole ballgame, since no one’s buying conversation hearts for Christmas. By tapping into current events and changing trends in courtship, the more-than-a-century-old brand is resonating with Valentine’s Day now. View the full article

We may earn a commission from links on this page. Deal pricing and availability subject to change after time of publication. The Apple Watch Series 9 [GPS + Cellular, 41mm] is currently going for $299.99 on Woot, which is a solid deal considering the same model starts at $399 new and about $226 refurbished on Amazon. This one’s brand-new and comes with a full one-year Apple warranty. With Prime, you also get free standard shipping (while non-Prime members are levied a $6 shipping fee), and the offer is live for four more days or until it sells out. Apple Watch Series 9 [GPS + Cellular, 41mm] $299.99 at Woot $399.00 Save $99.01 Get Deal Get Deal $299.99 at Woot $399.00 Save $99.01 It’s the model with cellular connectivity, so with an active carrier plan, you can call, message, or stream music even when your iPhone’s not nearby—something the cheaper GPS-only versions can’t do. That’s a big plus if you run without your phone or want to stay reachable while leaving it behind. The Series 9 runs on Apple’s S9 processor, which makes everything feel faster, and the screen gets much brighter. At 2,000 nits, it’s easy to read even when the sun’s beating down on your wrist. It also adds a double-tap gesture, so you can control things like answering a call or scrolling through widgets with just a pinch of your fingers. The onboard Siri lets you start a workout or set a timer with your voice, and it’s the first Apple Watch that’s carbon-neutral (at least in this aluminum and sport band combo). It also has access to the App Store, so apps like Spotify, Strava, and Calm run directly on the watch, notes this PCMag review. Battery life is around 32.5 hours, even with the always-on display enabled, which holds up fine for a full day and night of use, though heavy cellular use will shorten that. Health tracking is comprehensive. You get heart rate monitoring, ECG, blood oxygen readings, temperature sensing, sleep tracking, GPS, and fall detection. The watch is also IP6X dust resistant and WR50 water resistant, making it suitable for swimming and gym sessions. At $299.99, this is a strong price for a new cellular Apple Watch, making it one of the better deals for lifestyle smartwatches right now. Our Best Editor-Vetted Presidents' Day Deals Right Now Apple AirPods 4 Active Noise Cancelling Wireless Earbuds — $139.99 (List Price $179.00) Apple Watch Series 11 [GPS 46mm] Smartwatch with Jet Black Aluminum Case with Black Sport Band - M/L. Sleep Score, Fitness Tracker, Health Monitoring, Always-On Display, Water Resistant — $329.00 (List Price $429.00) Apple iPad 11" 128GB A16 WiFi Tablet (Blue, 2025) — $299.00 (List Price $349.00) Bose QuietComfort Noise Cancelling Wireless Headphones — $229.00 (List Price $349.00) Dell 16 DC16255 (AMD Ryzen 7 250, 512GB SSD, 16GB RAM, 2K Display) — $649.99 (List Price $869.99) HP Omen 35L (Intel Core Ultra 9 285K, RTX 5080, 2TB SSD, 64GB RAM) — (List Price $3,099.99 With Code "PRESDAYPC100") HP OmniBook X Flip Ngai 16-Inch (AMD Ryzen AI 7 350, Radeon 860M, 512GB SSD, 16GB RAM, 2K Display) — (List Price $649.99 With Code "PRESDAYPC50") Deals are selected by our commerce team View the full article

When the same information needs to exist in multiple systems, someone has to keep it consistent. Either a person manually updates each system when something changes, or software handles the synchronization automatically. Data synchronization is the process that makes the second option work. Organizations adopt specialized tools for different functions: a CRM for sales, a project management platform for operations, a support system for customer service, a marketing automation tool for campaigns. Each system stores data about customers, projects, or tasks in its own format. Without synchronization, these become isolated databases that require manual effort to keep aligned. The cost of that manual effort compounds quickly. Research shows knowledge workers spend 62% of their time on repetitive work rather than skilled tasks. A significant portion of that time involves moving data between systems that could synchronize automatically. What data synchronization means Data synchronization is the process of establishing consistency between data in different systems and maintaining that consistency over time. When data changes in one system, synchronization ensures the corresponding data updates in connected systems. The core components of data synchronization: ComponentWhat it doesSource identificationDetermines where data originates and which system holds authoritative recordsField mappingDefines how data fields in one system correspond to fields in anotherConflict resolutionEstablishes rules for handling cases where data differs between systemsChange detectionIdentifies when data has been modified and needs synchronizationTransformationConverts data formats, values, or structures between systems Simple synchronization might copy all records from one database to another on a schedule. Complex synchronization maintains bidirectional relationships between records across multiple systems, handling conflicts and transformations in real-time. The goal is data consistency without manual intervention. When a customer’s contact information updates in your CRM, that change should reflect in your marketing platform, support system, and billing software without anyone copying and pasting. Consider what happens without synchronization. A customer calls support to update their phone number. The support agent updates the support system. But the CRM still has the old number. So does the marketing platform. Next week, sales calls the old number wondering why the customer isn’t answering. Marketing sends SMS to a number that no longer works. The billing team has payment issues because the contact information is wrong. One data change should have propagated everywhere, but instead it created inconsistency that causes problems for weeks. Synchronization prevents this by ensuring that a change in one system automatically reflects in connected systems. The support agent updates the phone number once, and every system that needs that information receives the update. Types of data synchronization Different synchronization approaches fit different requirements. Understanding the options helps you choose the right method for each integration. One-way vs two-way synchronization One-way synchronization copies data from a source system to a destination system. Changes in the source update the destination, but changes in the destination don’t flow back. This works when one system is the clear authority and others just need to receive updates. Two-way synchronization maintains consistency in both directions. Changes in either system update the other. This works when different teams work in different systems and both need to modify the same data. Sync DirectionHow it worksBest forOne-waySource → Destination onlyReporting databases, read-only mirrors, data warehousesTwo-waySource DestinationCross-team collaboration, tools where both sides edit The choice matters because many business workflows require two-way sync even when it seems like one-way would suffice. A product manager updating the roadmap in their tool while engineering updates status in Jira needs changes flowing both directions. One-way sync from either system leaves the other outdated. Two-way sync is harder to implement than one-way. It requires conflict resolution logic, careful handling of which system is authoritative for which fields, and more sophisticated change detection. But for collaborative workflows where multiple teams modify the same data, two-way sync is often the only approach that actually works. One-way sync creates a second-class system where changes get overwritten, which defeats the purpose of letting teams work in their preferred tools. For a practical example, see how Airtable sync works with different methods. Real-time vs batch synchronization Real-time synchronization propagates changes immediately or within seconds of detection. When a record updates, connected systems reflect the change almost instantly. Batch synchronization collects changes and processes them on a schedule, whether every few minutes, hourly, or daily. Changes accumulate between sync cycles. Sync TimingHow it worksBest forReal-timeChanges propagate immediatelyCollaborative work, time-sensitive dataBatchChanges processed on scheduleHigh-volume data, systems that don’t need instant updates Real-time sync matters more than many organizations initially expect. When teams collaborate across tools, even a few minutes of delay creates confusion. Someone checks a status that changed two minutes ago and makes decisions based on stale information. For operational data where teams actively work, real-time synchronization eliminates that gap. The practical difference shows up in daily work. An engineer marks a Jira ticket as complete. If sync runs hourly, the product manager checking the roadmap tool won’t see that update for up to an hour. They might ping the engineer for status on something that’s already done. Multiply this by dozens of updates daily across a team, and the overhead from stale data becomes significant. Real-time sync makes this friction disappear. Full vs incremental synchronization Full synchronization compares and updates all records during each sync cycle. This ensures complete consistency but can be slow and resource-intensive with large datasets. Incremental synchronization only processes records that changed since the last sync. This is faster and more efficient for ongoing operations. Most modern synchronization platforms use incremental sync for regular operations with occasional full syncs to catch anything that might have been missed. Common data synchronization challenges Synchronization sounds straightforward until you encounter the edge cases that make implementation complex. Conflict resolution. What happens when the same record changes in both systems between sync cycles? Someone updated the customer phone number in the CRM while someone else updated it differently in the support system. Synchronization needs rules: last write wins, source system wins, or flag for manual review. Data format differences. Systems store data differently. One system might use “Active/Inactive” while another uses “1/0” for the same concept. Date formats vary. Required fields differ. Synchronization must transform data to match each system’s expectations. Relationship preservation. Business data includes relationships: projects have tasks, customers have contacts, tickets have comments. Synchronizing records without preserving these relationships creates orphaned data that loses its context. Historical data. New synchronization setups need to handle existing records, not just future changes. Migrating historical data while establishing ongoing sync adds complexity that many tools handle poorly. Scale and performance. Synchronizing thousands or millions of records requires infrastructure that can handle the volume without degrading system performance or creating bottlenecks. These challenges explain why organizations often settle for manual processes despite the inefficiency. Solving synchronization properly requires tooling designed for the complexity. The build vs buy decision matters here. Custom synchronization code is notoriously difficult to maintain. APIs change, edge cases multiply, and the developer who built the original integration moves to another role. Many organizations have a graveyard of broken sync scripts that nobody wants to touch. Purpose-built synchronization platforms handle these complexities so your team doesn’t have to rebuild solutions that already exist. When data synchronization matters most Not every data relationship requires synchronization. Identifying where sync delivers genuine value helps prioritize integration efforts. Cross-functional handoffs. When work passes between teams using different tools, synchronization ensures context travels with the work. Sales closes a deal in the CRM, and the customer information appears in the project management tool for implementation. No one copies and pastes. No information gets lost in translation. Collaborative work across tools. Different teams legitimately prefer different tools. Product managers live in roadmap software. Engineers live in Jira. Synchronization lets both teams work in their preferred environments while seeing the same priorities and progress. Customer data consistency. Customer information scattered across CRM, support, billing, and marketing systems without synchronization means every team works with potentially stale or conflicting data. Synchronization maintains a consistent customer record everywhere. Reporting and analytics. Accurate reporting requires current data. If the reporting database only updates weekly, decisions rely on week-old information. Synchronization keeps reporting data current. Tool transitions and migrations. When organizations adopt new tools, synchronization enables gradual transitions rather than disruptive switchovers. Teams can work in both old and new systems during the transition period while data stays consistent. This reduces the risk and stress of tool changes. Choosing the right synchronization approach The right approach depends on what you’re synchronizing, who needs access, and how current the data needs to be. Questions to clarify requirements: Does data need to flow one direction or both? If both teams modify records, you need two-way sync. How quickly do changes need to reflect across systems? Real-time for collaborative work, batch for reporting or archival. What happens when data conflicts? Define rules before you need them. How much historical data needs to migrate? Initial sync complexity varies significantly based on data volume. Who will maintain the synchronization? Custom solutions require ongoing development resources. Managed platforms shift that burden to the vendor. What’s the cost of sync failures? If synchronization breaks, how quickly do you need to know, and how severe are the consequences? Important data flows need monitoring and alerting. For work management tools where teams collaborate across Jira, Asana, Salesforce, HubSpot, and similar applications, platforms built for two-way sync handle the complexity of bidirectional updates, conflict resolution, and field mapping without requiring custom development. The goal isn’t synchronizing everything everywhere. It’s ensuring that the data people need stays current in the systems where they work. When your tools stay in sync, your teams can focus on the work itself rather than the overhead of keeping information aligned. The organizations that get synchronization right share a common trait: they invested in proper tooling rather than heroic manual effort or fragile custom scripts. The technology exists to keep your data consistent across systems automatically. The question is whether you’re using it. Two-way sync: The future of data synchronization For teams whose primary need is keeping project management, CRM, and development tools synchronized, two-way sync between work management platforms delivers data consistency without the complexity of building and maintaining custom integrations. View the full article

AI search visibility in beauty is increasingly shaped before a prompt is ever entered. Brands that appear in generative answers are often those already discussed, validated, and reinforced across social platforms. By the time a user turns to AI search, much of the groundwork has been laid. Using the beauty category as a lens, this article examines how social discovery influences brand visibility – and why AI search ultimately reflects those signals. Discovery didn’t move to AI – it fragmented Brand discovery has fragmented across platforms. AI tools influence mid-funnel consideration, but much discovery happens before a user enters a prompt. The signals that determine AI visibility are formed upstream. By the time a user reaches generative search, preferences and perceptions may already be set. If brands wait until AI search to influence demand, the window to shape consideration has narrowed. That upstream influence is increasingly social. Roughly two-thirds of U.S. consumers now use social platforms as search engines, per eMarketer research. This shift extends beyond Gen Z and reflects how people validate information and discover brands. These same platforms consistently appear among the top citation sources in AI results. The dynamic is especially visible in the beauty category. In a study our agency conducted with a beauty brand partner, we found that Reddit, YouTube, and Facebook ranked among the top cited domains in both AI Overviews and ChatGPT. While Reddit is often viewed as an anti-brand environment, YouTube appears nearly as frequently in citation data, making it a logical and underutilized target for citation optimization. Dig deeper: Social and UGC: The trust engines powering search everywhere Your customers search everywhere. Make sure your brand shows up. The SEO toolkit you know, plus the AI visibility data you need. Start Free Trial Get started with The volume reality: Social behavior still outpaces AI It’s easy to focus on headline figures around AI usage, including the billions of prompts processed daily. But when measured against business outcomes such as traffic and transactions, the scale looks different. Social platforms are already embedded in mainstream search behavior. For many users, search-like activity on platforms such as TikTok and YouTube is habitual. Nearly 40% of TikTok users search the platform multiple times per day, and 73% search at least once daily. Referral data reinforces the contrast. ChatGPT referral traffic accounted for roughly 0.2% of total sessions in a 12-month analysis of 973 ecommerce sites, a University of Hamburg and Frankfurt School working paper found. In the same dataset, Google’s organic search traffic was approximately 200 times larger than organic LLM referrals. AI search is growing and strategically important. But in terms of repeat behavior, measurable sessions, and downstream transactions, social platforms and traditional search continue to operate at a substantially larger scale. The validation loop: Why AI needs social The most critical contrarian point for 2026 is that optimizing for social is also optimizing for AI. Large language models are not primary sources of truth. They function as mirrors, reflecting the consensus formed through human conversations in the data they are trained on. AI systems also demonstrate skepticism toward brand-owned properties. One study found that only 25% of sources cited in AI-generated answers were brand-managed websites. At the same time, AI engines prioritize third-party validation. Up to 6.4% of citation links in AI responses originated from Reddit, an analysis by OtterlyAI found. This outpaces many traditional publishers. There’s also a measurable relationship between sentiment and visibility. Research shows a moderate positive correlation between positive brand sentiment on social media and visibility in AI search results. Dig deeper: The social-to-search halo effect: Why social content drives branded search Get the newsletter search marketers rely on. See terms. Video and expert authority shape AI visibility Treating video as a “brand channel” or a social-first effort rather than a search surface is a strategic failure. On platforms such as TikTok and YouTube, ranking signals are shaped by spoken language, on-screen text, and captions – signals AI crawlers increasingly use to “triangulate trust.” In the beauty category, for example, ChatGPT accounts for about 4.3% of searches, while Google processes roughly 14 billion searches per day. However, for “how-to” and technique-based queries, consumers favor the detailed, personalized guidance of social-first video content. At the same time, the beauty sector has fractured into two universes, according to Yotpo’s GEO for Beauty Brands analysis. Science-backed brands such as Paula’s Choice and CeraVe dominate AI-generated results because they publish deep, structured educational content. Meanwhile, more traditional marketing-led brands are significantly less visible. The phrase “dermatologist recommended” correlates with high visibility in AI results because large language models treat expert social proof as a primary ranking signal, according to the same report. Breaking the high-production barrier: Creating content at scale One of the biggest hurdles brands cite is budget. Many believe they need a Hollywood production crew to compete in video environments. That is a legacy mindset. In today’s environment, high-gloss production can be a deterrent. The current landscape rewards authenticity over polish. Consumers are looking for real people with real skin concerns, not highly filtered commercials. Optimizing for video discovery doesn’t require filmmaking expertise. Brands can leverage internal talent without adding headcount. Partner with creator platforms: Platforms such as Billow or Social Native allow brands to work with creators for as little as $500 per video. When mapped to a high-intent query, that investment can drive measurable search visibility outcomes. Leverage social natives on staff: Often, the strongest asset is internal. Identify team members who are active on platforms such as TikTok and understand platform dynamics. Creating internal incentives or challenges to produce content can generate a steady stream of authentic assets while contributing to culture. Make strategy the differentiator: A large following is not a prerequisite for visibility. In one case, a TikTok profile built from scratch with one part-time creator at $2,500 per month generated hundreds of thousands of views within 90 days. The focus was not on viral trends, but on meaningful transactional terms that drive revenue. If a new profile can reach more than 100,000 views per video within three months on a limited budget, the barrier isn’t equipment. It’s clarity on the business case and disciplined execution. Dig deeper: How to optimize video for AI-powered search See the complete picture of your search visibility. Track, optimize, and win in Google and AI search from one platform. Start Free Trial Get started with The new beauty SEO playbook for 2026 The data is clear. Brands can’t win the generative engine if they’re losing the social conversation. AI models function as mirrors, reflecting web consensus. If real users on Reddit, YouTube, and TikTok aren’t discussing a brand, AI systems have little to surface. If marketers wait until a user reaches a ChatGPT prompt to shape perception, the opportunity has already narrowed. Discovery happens upstream. Validation occurs in the loop between social proof and algorithmic citation. Translating this into action requires rethinking team structure and priorities: Stop the silos: Your SEO and social teams shouldn’t speak different languages. Both must focus on search surfaces. Prioritize the “why” before the “what”: Don’t just fix a technical tag. Build the business case for how social sentiment and expert validation drive market share. Embrace scrappy execution: Whether through $500 creator partnerships or internal social-native talent, start building authentic assets now. We’re witnessing a shift from algorithm-driven discovery to community-driven discovery. It’s agile and multidisciplinary, and when executed well, it can meaningfully impact the bottom line. View the full article

In India, domestic tech entrepreneurs are outperforming those who return home after a stint in Silicon Valley View the full article

This morning, shares of two of the largest computer memory companies that trade on U.S. markets are up yet again. The stock prices of Micron Technology, Inc. (Nasdaq: MU) and Sandisk Corporation (Nasdaq: SNDK) rose after a Japanese memory firm issued a surprising outlook. Here’s what you need to know. Stock prices jump as demand continues Shares in several memory chip makers traded on U.S. markets are currently up in premarket trading this morning. The companies include Micron and Sandisk, as well as Western Digital Corporation (Nasdaq: WDC) and Seagate Technology Holdings (Nasdaq: STX). As of this writing, Micron shares are currently up 2.9%, Sandisk shares are up 6.2%, Western Digital shares are up 3%, and Seagate shares are up 2.5%. While all four companies make memory chips, Western Digital and Seagate primarily focus on computer storage, leaving Micron and Sandisk as the two primary memory chip makers traded on U.S. exchanges. And those two companies are getting a lot of attention, not just today, but as of late, due to the memory chip shortage that global supply chains are currently dealing with. As Fast Company previously reported, there is a global memory chip shortage in 2026. Computer memory, also known as RAM, is the component inside a computer that saves and processes short-term memory (as opposed to long-term memory, which is what hard drives and SSDs store). Demand from artificial intelligence (AI) companies is fueling the shortage as they race to get as much RAM as they can get their hands on. These AI companies are currently building many AI data centers, which need powerful servers to run the AI, and those servers require memory to handle instructions. As a result, demand for memory chips is off the charts. And while that is bad for consumers, who are likely to see higher costs for smartphones and laptops this year due to rising memory prices, it’s very good for the companies that make memory, like Micron and SanDisk. Why are memory chip companies seeing their prices rise today? Today’s rise in memory company stock prices isn’t something totally out of the blue. The stock prices of memory companies have been rising for months as news of a memory chip shortage in 2026 spread. However, the stock price jumps in MU and SNDK today seem to be primarily due to a Japanese company called Kioxia. Kioxia is a Japanese flash memory supplier, and today, it reported fiscal third-quarter results. Those results, as noted by Investing.com, slightly exceeded expectations. Q4 guidance, on the other hand, blew past expectations. Most analysts had expected Kioxia to issue Q4 revenue guidance of ¥648.2 billion (about $4.2 billion). Instead, the company said its Q4 guidance is ¥890 billion at the midpoint (about $5.8 billion). That is a massive difference and one that many investors see as evidence that demand for memory chips isn’t going to slow anytime soon. And when demand is high, prices rise, and memory chip companies make more money. And investors seem to believe that if Kioxia is guiding much higher on revenue than analysts expected, that signals good news for memory chip companies on this side of the Pacific, too. Memory chip stocks have had a great 2026 so far Even before today’s Kioxia boost, U.S. memory chip stocks have had a pretty stellar run since the year began. As of yesterday’s market close, Micron was up more than 43% year to date, Sandisk was up 152%, Western Digital was up 58%, and Seagate was up 47%. To put those figures into greater context, the stock market they all trade on, the Nasdaq, has actually declined during the same period. As of yesterday’s close, the Nasdaq Composite was down about 0.7% for the year so far, according to data from Yahoo Finance. Looking back even further—over the past 12 months—the returns on these same four memory chip companies have been even more eye-popping. In the last year, Seagate has risen 316%, Micron has jumped 336%, Western Digital is up 425%, and Sandisk has risen a staggering 1,609%. During the same period, the NASDAQ Composite has risen 17.4% View the full article

History might be repeating itself after the sale of investment banks to bigger US rivalsView the full article