The regulator ended its civil enforcement case accusing the DeSo creator of wire fraud and selling unregistered crypto securities.
BUSINESS
The IRS has changed the tax rules for 2026 — here’s how to keep more money and not overpay
From the new SALT cap to 401(k) ‘super catch-ups,’ this guide can keep Uncle Sam out of your pocket.
How do companies get added to (& dropped from) the Dow?
Created in 1896 by Wall Street Journal cofounder Charles Dow, the Dow Jones Industrial Average is America’s oldest stock market index, but that’s not the only thing that makes it stand out among its peers. It’s also smaller than most other indexes, comprising just 30 blue-chip companies, and the way it’s constructed (and deconstructed and reconstructed) is also unique. The composition of most other bellwether indexes — i.e., the stocks they include — is standardized, with fairly simple criteria determining which companies end up in the index and which don’t. The S&P 500, for instance, includes the 500 largest American companies by market capitalization, assuming they meet the index’s other inclusion criteria (profitability requirements, float requirements, etc.). It is managed by an oversight committee that meets quarterly to rebalance it and ensure its composition aligns with its inclusion criteria.The Dow also has inclusion criteria, but they are significantly less specific, and when it comes to which companies make the cut, the decision ultimately rests with just five people, known collectively as the “averages committee.” And because of the Dow’s small size and relatively loose inclusion criteria, the averages committee has far more decision-making power than the committees that oversee more standardized indexes like the S&P 500. Here’s everything you need to know about the averages committee and how they decide which stocks to add to and drop from the Dow. What is the Dow’s averages committee? The Dow Jones Industrial Average is designed to serve as a benchmark for the U.S. stock market and economy at large by tracking the collective prices of 30 mature, blue-chip companies that together represent the best of the industries that make up the American economy.The Dow’s averages committee is responsible for ensuring that the index’s composition remains true to this purpose by dropping companies that no longer fit these criteria and replacing them with companies that do. Related: What happens when a stock splits in the Dow Jones Industrial Average?The averages committee includes only five people — three representatives from S&P Dow Jones Indices (the LLC behind both the Dow and the S&P 500) and two representatives from the Wall Street Journal (the financial news outlet founded by Charles Dow). These five individuals work together to monitor the health and viability of the companies in the Dow and make adjustments when necessary to maintain the index’s continuity and viability as a benchmark. What criteria must a stock meet to be included in the Dow? When choosing a stock to include in the Dow, the averages committee has quite a bit of leeway, though certain criteria are strongly considered, which narrows the pool of candidates to a more manageable size.To be considered for the Dow, a company must …Be headquartered and incorporated in the U.S.Be a non-transportation, non-utility stock included in the S&P 500 Have a good reputation and a history of sustained growth Have a large number of investorsRelated: Dow Jones’ revolving door: What happens to a stock after it’s dropped from the DJIA?What other factors does the averages committee consider when adding or dropping a stock from the Dow? In addition to the above criteria, the averages committee also considers the following questions when considering adding a stock to the DJIA: Is this company a leader in its industry? Does it have a history of increasing dividend payments to shareholders? Will its inclusion help the index accurately represent the sector balance of the U.S. economy? Is its stock price appropriate for its weighting in the index? (The DJIA is price-weighted, which is unusual, so stock prices — which can be arbitrary — must be considered to avoid weighting problems.)Related: The Dow’s best dividend stocks: A shortlist for income investorsWhy is the Dow’s averages committee different from other stock index oversight committees? Because the Dow’s inclusion criteria are far looser and less standardized than those of, say, the S&P 500, the averages committee holds quite a bit of decision-making power, especially since the DJIA is such a frequently cited benchmark in financial and economic news. In a way, the Dow has become something of an “all-star team” of American stocks, and its small size makes a company’s inclusion a sought-after accolade.While most other indexes are “constructed” according to a relatively strict set of criteria, the Dow is “curated,” with factors such as reputation, investor popularity, and industry leadership influencing the committee’s decisions. With so many healthy, mature companies to choose from, the averages committee’s choices aren’t always easy, and when they drop a stock from the Dow’s ranks and replace it with a new one, both companies tend to receive heightened interest and scrutiny from investors — retail and institutional alike. When a stock is dropped from the Dow, it can signal to investors that the company’s growth has slowed or stalled, or that it is losing cultural or economic relevance. When a company is added to the Dow, it can signal that it has transformed from a rising star to an established sector leader and a mainstay in the American economy.
Practical guidance on talking to someone who is living with dementia
Broadcast Retirement Network’s Jeffrey Snyder discusses how family members and caregivers can connect with loved one’s with dementia with University of Alabama Birmingham’s Andrew Duxbury, MD.Jeffrey Snyder, Broadcast Retirement NetworkJoining me now is Dr. Andrew Duxbury at the University of Alabama, Birmingham. Doctor, so great to see you. Thanks for joining us this morning.It’s a pleasure to be here. I am so excited because dementia is prominent in our society. And I want to take a step back and ask, in terms of relating to people with dementia, I would imagine it’s pretty difficult for caregivers, for family members to have that interaction with a loved one that’s kind of going in and out of their memories.Andrew Duxbury, MD, University of Alabama BirminghamWell, the thing that I always try to teach families in regards to communicating with someone with dementia is that their reality is different than ours because their brain works differently than ours and reality is strictly what our brain tells us it is. Therefore, our worlds intersect, but they do not overlap. And therefore, the important thing is to try to figure out how to stay as much as possible at the intersect together as you can, but that when they’re in their part of their world that you cannot visit or you’re in our reality that they cannot visit, that it’s okay.And it’s just a matter of trying to come around to where the intersect is present again.Jeffrey Snyder, Broadcast Retirement NetworkSo it’s really important to have those expectations going in. I would imagine, doctor, this is really hard for families because they’re so used to seeing their loved ones as they were, not as they are.Andrew Duxbury, MD, University of Alabama BirminghamThat is absolutely correct, that people develop long-term relationships with someone over many decades and they construct who that person is and how they will react. And when that person no longer fits that construct, it can cause a lot of friction and a lot of trying to push people back into the construct with which they are comfortable and familiar, even though that individual no longer fits and is not capable of inhabiting it.Jeffrey Snyder, Broadcast Retirement NetworkSo we’re essentially meeting the patient where they are. How do we do that? I mean, how do we reframe it for ourselves?But what kind of strategies should we undertake? There are probably numerous Americans out there, numerous family members who are dealing with this. What’s the first step?Andrew Duxbury, MD, University of Alabama BirminghamWell, the first step is to understand that life has always changed and that the biggest problems happen when we try to remain static, that we try to hold people in one place or we try to hold life in one pattern or we try to force people into a life pattern that they constructed for themselves in the past that they no longer fit. We’re really good at understanding these changes in younger people. A five-year-old, a 10-year-old, a 15-year-old and a 20-year-old are all very different beings, even though they’re only five years apart from each other.But we’re really terrible about understanding that these same kinds of changes and these same different or these very large differences can happen in the same kind of speed later in life. And so you have to always understand, you have to look forward, you have to understand that you have to move toward whatever way things are changing and not try to hold back in what is no longer appropriate.Jeffrey Snyder, Broadcast Retirement NetworkAnd so, you know, in terms of tactics, I’ve been reading a lot up, reading up a lot on dementia, reading a lot on music to stimulate some of those memories. Does that help kind of get the ball rolling? If a loved one loved a certain theater production to go into one of your hobbies or they liked a certain sound of music, would that help kind of stimulate?Andrew Duxbury, MD, University of Alabama BirminghamIt absolutely can. We lay down our understanding of culture, particularly kind of pop culture, in a very specific band of our lives between roughly the ages of 12 and 25. Everything that we come to understand as being right about music, television, movies, is all created for us when we’re going through that particular maturation process.I read somewhere that the key year in regards to music is the year we are 14. Whatever we are listening to that year is what we define as being good music for the rest of our lives. So for people with dementia, because music is processed in a very different way in the brain than language.And this is why, for instance, like all of the great epics are written in poetry, because we can not transfer orally prose language in large chunks, person to person very well. But we can transfer lyric and song and poetry person to person in large chunks much more easily. We lay down those poems and those songs and that and we always remember them and we all know this phenomenon because we’ve all been in the car listening to the radio and some song comes on that we haven’t heard in decades and we’re singing along.Jeffrey Snyder, Broadcast Retirement NetworkDoctor, in terms of the environment, thank you for that, in terms of the environment that we’re in when we’re communicating with our loved ones, should it be less stimulative, meaning quieter environment where you can look at the person one-on-one, there’s not these distractions, for example, you’re not in the mall, you’re not in…Andrew Duxbury, MD, University of Alabama BirminghamAbsolutely. Our brains have a finite capacity for processing information. And in a young healthy brain, that capacity is pretty large and a young person can be in a party and yelling and shrieking and music is blaring and you can hear someone say your name across the room and you can all of a sudden focus in on that conversation and drop out all of the other noise.But older brains just can’t do that. Older brains also have to deal with the fact that hearing decreases some as we age, it happens in everybody, and because we don’t hear as well, we start making up with that with other cues and we all start reading lips as we age in terms of understanding spoken language. So in order to really clearly understand someone, we have to see the face and we have to have not too much extraneous noise that the brain could pull into sound processing as somehow being part of the spoken information.At my age, in my mid-60s now, I realized that if the lawnmower or something’s going outside the window, all of a sudden the person talking to me from the other room is like they’re speaking Swahili because other noises are just getting into that stream of information and I don’t understand it as well.Jeffrey Snyder, Broadcast Retirement NetworkWell, doctor, I’ve got about a minute left and I want to ask you, I want you to touch on the latest, the future of research, but also could you talk about integrating technology? There’s a lot of new technology out there. People that go to the Consumer Electronics Show know there’s a lot of technology that’s being demoed for people in our age demographic.Andrew Duxbury, MD, University of Alabama BirminghamWell, it’s because there’s so many people in our age demographic. We have roughly somewhere between 8 and 10,000 people a day having their 80th birthday for the next 20 years and that’s just the baby boom and what has happened with our society. I don’t know exactly how AI is going to build into all of this and how we age and how we process information.My guess is there will be devices that will come online that will allow us to better understand the streams of information we need to and that AI will be able to help us eliminate those which are distracting. How that’s going to work, I have no idea. That’s way over my head in terms of understanding technology.Jeffrey Snyder, Broadcast Retirement NetworkYeah, well certainly, it’s iterative. We’re sure there are people in the field that you’re in or trying to take the data sets, trying to analyze them and try to get that research done more expeditiously. Dr. Duxbury, we’re going to have to leave it there. Thanks so much for joining us and look, we look forward to having you back on the program again very soon, sir.Andrew Duxbury, MD, University of Alabama BirminghamIt will be my pleasure.
Dividend-paying restaurant stock stumbles as gas prices surge
Restaurant stocks have been a rough ride lately. Since tensions in the Middle East flared, the sector has quietly been losing ground, and Wall Street is starting to pay close attention.The reason is simple. When gas prices rise, people have less money left over for eating out. It’s one of the most direct and predictable patterns in consumer behavior.That’s the warning Deutsche Bank analyst Lauren Silberman issued recently, according to CNBC. The analyst also pointed out that when gas prices spiked in response to the Russia-Ukraine war, several restaurant chains saw a “near-immediate” drop in customer traffic. She thinks it could happen again.Darden Restaurants is one of the most notable casualties. The Orlando, Fla.-based company behind Olive Garden, LongHorn Steakhouse, and more than a dozen other dining brands across the U.S. and Canada has seen its share price decline by 7.5% over the past month.However, the ongoing drawdown has raised the forward yield for Darden (DRI) to 3%, making the dividend stock attractive to income seekers. Darden Restaurants stock is a top buy for income investorsDarden is one of the few casual-dining names to which income investors pay attention. The stock pays shareholders a quarterly dividend of $1.50 per share, up from $0.40 per share in 2006.In the past two decades, DRI stock has returned 452% to shareholders. However, if adjusted for dividend reinvestments, the cumulative returns exceed 900%, according to Y-charts.com. Analysts tracking the dividend stock forecast that the restaurant giant will end fiscal 2026 with free cash flow of less than $1 billion. Comparatively, the annual dividend expense for Darden is around $700 million, indicating a high payout ratio of 70%. However, given consensus estimates, FCF is forecast to improve to $1.6 billion in fiscal 2029 (ending in May). Over the next three years, the annual dividend will be around $7.16 per share. Key dividend metrics for Darden stock:Dividend yield: Approx. 3%Quarterly dividend per share: $1.50Annual dividend per share: $6Dividend payout ratio: Roughly 70% of FCFDividend frequency: QuarterlyDarden has steadily increased its dividend each year following its post-pandemic recovery. For income investors, a payout ratio around 70% means the company earns more than it pays out, leaving room to sustain the dividend even if profits dip slightly.Macro headwinds could impact DardenDespite the stock’s recent slide, Darden delivered a solid second quarter for fiscal year 2026. Total sales came in at $3.1 billion, up 7% from the same period last year.Same-restaurant sales grew 4.3% across the portfolio. That beat the broader casual dining industry benchmark by 300 basis points year over year (YoY).
Olive Garden is the key driver of sales for Darden Restaurants.Morris/Bloomberg via Getty Images
Olive Garden was a standout. It posted same-restaurant sales growth of 4.7%, helped by its popular Never Ending Pasta Bowl promotion and the launch of first-party delivery through Uber Direct. Delivery made up 4% of total Olive Garden sales during the quarter, and roughly half of that was brand-new, incremental revenue.LongHorn Steakhouse wasn’t far behind, posting same-restaurant sales growth of 5.9%.The bad news? Beef prices. They’ve been running near historically high levels, pushing commodity inflation to around 5.5% for the quarter. Related: Olive Garden makes big menu move as restaurant prices surgeThat squeezed margins across almost every segment. Darden chose to price its menu 1.3% below inflation, meaning it absorbed some of the cost rather than passing it all on to guests. That’s a deliberate strategy to protect long-term loyalty, but it did weigh on near-term earnings.Adjusted diluted earnings per share came in at $2.08, up just 2.5% from a year ago.What’s ahead for Darden stock Management updated its guidance for the full fiscal year. It now expects total sales growth of 8.5% to 9.3%, with same-restaurant sales growth of 3.5% to 4.3%. Full-year adjusted earnings per share guidance remains between $10.50 and $10.70.CFO Raj Vennam said the gap between pricing and inflation should narrow in the second half of the year, helping margins improve. More Dividend Stocks:156-year-old energy giant to pay $17 billion in dividends as oil spikes to $110114-year-old defense stock offers a $3 billion dividend payout in 2026This megacap AI stock pays over $12 billion in annual dividendsBeef costs are expected to ease as the year progresses, providing some relief.Still, with gas prices a wild card and consumers already showing signs of caution, particularly households earning less than $50,000, the near-term outlook for restaurant stocks like Darden carries real risk.Out of the 19 analysts covering Darden stock, 13 recommend “buy” and six recommend “hold.” The average DRI stock price target is $226, 11.6% above the current price. If we include dividends, cumulative returns could be closer to 14.5%.The silver lining for income investors: Darden’s 30-year track record as a public company includes an annualized total shareholder return of 10% or more in every 10 years. That kind of consistency doesn’t disappear overnight.But if gas prices stay elevated heading into summer, Silberman’s warning could prove timely. Investors holding DRI stock for the dividend may want to watch traffic trends closely in the next quarter.Related: Down 63 percent, Warren Buffett dividend stock signals opportunity
Rethinking AEO when software agents navigate the web on behalf of users
For more than two decades, digital businesses have relied on a simple assumption: When someone interacts with a website, that activity reflects a human making a conscious choice. Clicks are treated as signals of interest. Time on page is assumed to indicate engagement. Movement through a funnel is interpreted as intent. Entire growth strategies, marketing budgets, and product decisions have been built on this premise.Today, that assumption is quietly beginning to erode.As AI-powered tools increasingly interact with the web on behalf of users, many of the signals organizations depend on are becoming harder to interpret. The data itself is still accurate — pages are viewed, buttons are clicked, actions are recorded — but the meaning behind those actions is changing. This shift isn’t theoretical or limited to edge cases. It’s already influencing how leaders read dashboards, forecast demand, and evaluate performance.The challenge ahead isn’t stopping AI-driven interactions. It’s learning how to interpret digital behavior in a world where human and automated activity increasingly overlap.A changing assumption about web trafficFor decades, the foundation of the internet rested on a quiet, human-centric model. Behind every scroll, form submission, or purchase flow was a person acting out of curiosity, need, or intent. Analytics platforms evolved to capture these behaviors. Security systems focused on separating “legitimate users” from clearly scripted automation. Even digital advertising economics assumed that engagement equaled human attention.Over the last few years, that model has begun to shift. Advances in large language models (LLMs), browser automation, and AI-driven agents have made it possible for software systems to navigate the web in ways that feel fluid and context-aware. Pages are explored, options are compared, workflows are completed — often without obvious signs of automation.This doesn’t mean the web is becoming less human. Instead, it’s becoming more hybrid. AI systems are increasingly embedded in everyday workflows, acting as research assistants, comparison tools, or task completers on behalf of people. As a result, the line between a human interacting directly with a site and software acting for them is becoming less distinct.The challenge isn’t automation itself. It’s the ambiguity this overlap introduces into the signals businesses rely on.What do we mean by AI-generated traffic?When people hear “automated traffic,” they often think of the bots of the past — rigid scripts that followed predefined paths and broke the moment an interface changed. Those systems were repetitive, predictable, and relatively easy to identify.AI-generated traffic is different.Modern AI agents combine machine learning (ML) with automated browsing capabilities. They can interpret page layouts, adapt to interface changes, and complete multi-step tasks. In many cases, language models guide decision-making, allowing these systems to adjust behavior based on context rather than fixed rules. The result is interaction that appears far more natural than earlier automation.Importantly, this kind of traffic is not inherently problematic. Automation has long played a productive role on the web, from search indexing and accessibility tools to testing frameworks and integrations. Newer AI agents simply extend this evolution — helping users summarize content, compare products, or gather information across multiple sites.The issue is not intent, but interpretation. When AI agents interact with a site successfully on behalf of users, traditional engagement metrics may no longer reflect the same meaning they once did.Why AI-generated traffic is becoming harder to distinguishHistorically, detecting automated activity relied on spotting technical irregularities. Systems flagged behavior that moved too fast, followed perfectly consistent paths, or lacked standard browser features. Automation exposed “tells” that made classification straightforward.AI-driven systems change this dynamic. They operate through standard browsers. They pause, scroll, and navigate non-linearly. They vary timing and interaction sequences. Because these agents are designed to interact with the web as it was built — for humans — their behavior increasingly blends into normal usage patterns.As a result, the challenge shifts from identifying errors to interpreting behavior. The question becomes less about whether an interaction is automated and more about how it unfolds over time. Many of the signals that once separated humans from software are converging, making binary classification less effective.When engagement stops meaning what we thinkConsider a common e-commerce scenario.A retail team notices a sustained increase in product views and “add to cart” actions. Historically, this would be a clear signal of growing demand, prompting increased ad spend or inventory expansion.Now imagine that a portion of this activity is generated by AI agents performing price monitoring or product comparison on behalf of users. The interactions occurred. The metrics are accurate. But the underlying intent is different. The funnel no longer represents a straightforward path toward purchase.Nothing is “wrong” with the data — but the meaning has shifted.Similar patterns are appearing across industries:Digital publishers see spikes in article engagement without corresponding ad revenue.SaaS companies observe heavy feature exploration with limited conversion.Travel platforms record increased search activity that doesn’t translate into bookings.In each case, organizations risk optimizing for activity rather than value.Why this is a data and analytics problemAt its core, AI-generated traffic introduces ambiguity into the assumptions underlying analytics and modeling. Many systems assume that observed behavior maps cleanly to human intent. When automated interactions are mixed into datasets, that assumption weakens.Behavioral data may now include:Exploration without purchase intentResearch-driven navigationTask completion without conversionRepeated patterns driven by automation goalsFor analytics teams, this introduces noise into labels, weakens proxy metrics, and increases the risk of feedback loops. Models trained on mixed signals may learn to optimize for volume rather than outcomes that matter to the business.This doesn’t invalidate analytics. It raises the bar for interpretation.Data integrity in a machine-to-machine worldAs behavioral data increasingly feeds ML systems that shape user experience, the composition of that data matters. If a growing share of interactions comes from automated agents, platforms may begin to optimize for machine navigation rather than human experience.Over time, this can subtly reshape the web. Interfaces may become efficient for extraction and summarization while losing the irregularities that make them intuitive or engaging for people. Preserving a meaningful human signal requires moving beyond raw volume and focusing on interaction context.From exclusion to interpretationFor years, the default response to automation was exclusion. CAPTCHAs, rate limits, and static thresholds worked well when automated behavior was clearly distinct.That approach is becoming less effective. AI-driven agents often provide real value to users, and blanket blocking can degrade user experience without improving outcomes. As a result, many organizations are shifting from exclusion toward interpretation.Rather than asking how to keep automation out, teams are asking how to understand different types of traffic and respond appropriately — serving purpose-aligned experiences without assuming a single definition of legitimacy.Behavioral context as a complementary signalOne promising approach is focusing on behavioral context. Instead of centering analysis on identity, systems examine how interactions unfold over time.Human behavior is inconsistent and inefficient. People hesitate, backtrack, and explore unpredictably. Automated agents, even when adaptive, tend to exhibit a more structured internal logic. By observing navigation flow, timing variability, and interaction sequencing, teams can infer intent probabilistically rather than categorically.This allows organizations to remain open while gaining a more nuanced understanding of activity.Ethics, privacy, and responsible interpretationAs analysis becomes more sophisticated, ethical boundaries become more important. Understanding interaction patterns is not the same as tracking individuals.The most resilient approaches rely on aggregated, anonymized signals and transparent practices. The goal is to protect platform integrity while respecting user expectations. Trust remains a foundational requirement, not an afterthought.The future: A spectrum of agencyLooking ahead, web interactions increasingly fall along a spectrum. On one end humans are browsing directly, in the middle users are assisted by AI tools, on the other end agents are acting independently on a user’s behalf.This evolution reflects a maturing digital ecosystem. It also demands a shift in how success is measured. Simple counts of clicks or visits are no longer sufficient. Value must be assessed in context.What business leaders should focus on nowAI-generated traffic is not a problem to eliminate — it’s a reality to understand.Leaders who adapt successfully will:Reevaluate how engagement metrics are interpretedSeparate activity from intent in analytics reviewsInvest in contextual and probabilistic measurement approachesPreserve data quality as AI participation growsTreat trust and privacy as design principlesThe web has evolved before, and it will evolve again. The question is whether organizations are prepared to evolve how they read the signals it produces.Shashwat Jain is a senior software engineer at Amazon.
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America’s Electric Grid Has A Reliability Problem
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