SUCCESS

Coby Mayo started spring training the subject of trade rumors. Now, he’s the Baltimore Orioles’ hottest hitter and closing in on a starting job at third base.

TheStreet aims to feature only the best products and services. If you buy something via one of our links, we may earn a commission.Why we love this dealIf only we all had the convenience of a walk-in closet. Unfortunately, many of us have to make do with what we have, which requires a little creativity when you have a small closet. There are entire systems to get your closet organized, but they can be a bit pricey. The alternative is to choose your storage options wisely. You want something that’s versatile, sturdy, and spacious, and we found a stackable mini dresser on sale at Amazon that fits the bill. The Boluo 2-Drawer Stackable Mini Dresser is a versatile little dresser that’s great for organizing small spaces, like closets. It’s on sale now for just $43. That’s a $17 price drop (AKA 29% off) from its regular price of $60. With the potential to majorly upgrade your closet storage, it’s one deal you don’t want to miss.Boluo 2-Drawer Stackable Mini Dresser, $43 (was $60) at Amazon

Courtesy of Amazon

Why do shoppers love it?When you want to add more storage to your closet, it’s tempting to want to buy a large dresser with more drawers. However, that gives you very little to no room to customize your space. A mini dresser gives you more options, especially when you buy more than one.Measuring 21.1 inches long by 15.7 inches wide by 16.1 inches high, the two-drawer mini dresser is on the smaller side, but reviewers say the drawers are “very spacious.” It has an engineered wood top, a metal frame, and drawers made of fabric, giving the dresser a lightweight but sturdy build that you can easily move around. Since the dresser is light, it’s ideal for more lightweight clothing and items rather than bulky and heavy pieces.Thanks to its stackable design, the mini dresser is a great place to start your closet organization system. If you have a slim closet, you can use one or two side by side and stack more on top if there’s room. With a slightly bigger closet, you can get more creative with the design, perhaps lining a few of the mini dressers side by side, and stacking two or three mini dressers vertically to create a taller chest of drawers. This mini dresser isn’t just great for closets. If you have a tall bed frame, it would work well as under-bed storage. You can also use it as a nightstand.Related: Walmart is selling a storage cabinet with drawers and a cupboard for just $65Details to knowOverall dimensions: It measures 21.1 inches long by 15.7 inches wide by 16.1 inches high.Weight capacity: The tabletop holds up to 35 pounds, and the drawers hold up to 15 pounds each.Material: The dresser is made of engineered wood, fabric, and metal.”I love that they stack securely, save space, and keep everything looking neat. They’re lightweight, true to size, and easy to assemble,” a shopper said. “Great for closets, pantry, or under the sink — very sturdy and practical!”Another reviewer said it’s a great alternative to more expensive solid wood dressers or nightstands. According to shoppers, it has a similar look, but without the hefty price tag, and it’s still sturdy and efficient at organizing your space.Shop more dealsPinkMuse 2-Drawer Stackable Dresser, $115 (was $130) at AmazonWoodtalks Stackable 1-Drawer Dresser, $68 at AmazonDaelifker 2-Drawer Mini Dresser, $58 (was $65) at AmazonThe Boluo 2-Drawer Stackable Mini Dresser is not just a great storage upgrade, but it’s also a great deal while it’s on sale for only $43.

You probably already feel it: the grocery bill climbs, the electric bill climbs. Then the explanation-of-benefits letter shows up, and the number at the bottom doesn’t make sense.But for tens of millions of Americans, the math has gotten so bad that they’re now choosing between eating dinner and filling a prescription. A major new survey just put hard numbers on how deep those tradeoffs run, and the scale of the problem should concern anyone who pays for health care in this country.82 million Americans cut daily expenses to cover health care billsRoughly one-third of U.S. adults reported cutting back on food, utilities, or other daily expenses to afford health care in 2025, according to a West Health-Gallup Center on Healthcare in America survey conducted in Mid March 2026. More than 82 million Americans said they made at least one tradeoff in daily spending to pay for medical care.The survey polled nearly 20,000 adults across all 50 states and the District of Columbia between June and August 2025. The sacrifices people described ranged from skipping meals and cutting utility use to driving less and borrowing money to pay medical bills, CNN reported.Uninsured Americans face the steepest sacrificesIf you don’t have health insurance, the pain is far worse. Among uninsured respondents, 62% said they made at least one sacrifice to pay for health care, GV Wire reported. That includes 32% who had to borrow money and 24% who stretched out their current medication to make it last longer.Among uninsured Americans surveyed:62% made at least one daily expense tradeoff to pay for health care32% borrowed money to cover medical costs24% prolonged their current medication rather than refilling on timeBut the problem does not stop with the uninsured. Among those with insurance, close to three in 10 reported making at least one sacrifice. Higher premiums and steeper out-of-pocket costs are squeezing even those who technically have coverage.Most Americans with private health insurance are paying higher premiums and steeper out-of-pocket costs in 2026, including millions on government-subsidized ACA plans where the extra pandemic-era subsidies have now expired.Even insured Americans are strugglingEllyn Maese, research director for the West Health-Gallup Center on Healthcare, put it bluntly in an interview with CNN. The cost pressure is no longer limited to lower-income or uninsured households. It has spread across income levels.Health care costs are forcing Americans to delay surgeries, homes, and retirementA second West Health-Gallup survey, conducted between October and December 2025 with 5,660 U.S. adults, found that health care costs have pushed tens of millions of Americans to postpone major life decisions in recent years.Life events delayed due to health care costs:Just over 25% delayed surgical or medical treatment.14% held off buying a new home.Nearly 9% postponed retirement.Roughly 18% delayed a job change.If you’ve been putting off a surgery or a needed procedure because you can’t absorb the out-of-pocket bill, you’re far from alone. And these delays carry their own costs. Conditions left untreated generally become more expensive, more complicated, and more dangerous over time.Postponing retirement or holding off on a job change can also compound financial stress. You may stay in a role that no longer fits because the health benefits feel irreplaceable, or you may push back retirement into a period when your health needs are higher, and your earning power is lower.U.S. health care spending hit $5.3 trillion in 2024, and it keeps climbingThis survey arrives against a backdrop of record health care spending. U.S. health care expenditures reached $5.3 trillion in 2024, or $15,474 per person, growing 7.2% from the prior year, according to the Centers for Medicare & Medicaid Services. Health spending now accounts for 18% of GDP.CMS projects health spending will grow an average of 5.8% annually through 2033, outpacing GDP growth of 4.3%, according to a Health Affairs analysis of CMS projections. By 2033, health care’s share of the economy is projected to reach 20.3%.Americans are getting sicker and spending moreTim Lash, president of West Health, told CNN that the country’s overall health is declining, with rising rates of metabolic disease, depression, and anxiety driving higher utilization.Americans are not just paying more for health care; they are in need of more access to it. Per capita health expenditures are projected to grow from $16,570 in 2024 to $24,200 by 2033, according to the Peterson-KFF Health System Tracker analysis of CMS data.Expired ACA subsidies are pushing millions toward unaffordable premiumsCongress allowed enhanced Affordable Care Act premium subsidies to expire at the end of 2025. Those subsidies had been keeping premiums manageable for an estimated 20 million people.Without them, ACA marketplace premiums jumped an average of 26% for 2026, according to KFF.More Health Care:If your Medicare plan was canceled, do this nowHealth care costs are the wild card in year-end tax planning22 million Americans hit by ACA health insurance cliff after vote failsFor subsidized enrollees, the expiration of enhanced tax credits drove out-of-pocket premium payments up by more than 75% on average; and subsequent KFF modeling put the increase even higher, at approximately 114%, or more than double what enrollees had been paying, according to the Peterson-KFF Health System Tracker. CMS projects that 4.7 million people will lose direct-purchase insurance coverage in 2026 as a result of the subsidy expiration, representing a 12.3% decline in direct-purchase enrollment, according to the agency’s National Health Expenditure Projections.If you’re on an ACA plan, you may already be feeling this. TheStreet has reported on how households above 150% of the federal poverty level face the steepest hikes. Some families are now choosing between paying their health insurance premiums and putting food on the table.Medicare costs are climbing for seniors on fixed incomesIf you’re on Medicare, 2026 brought its own round of increases. CMS announced that the standard Part B premium rose to $202.90 per month, up $17.90 from 2025. That’s a 9.6% jump, more than three times the 2.8% Social Security cost-of-living adjustment for 2026.Key Medicare cost increases for 2026:Part B monthly premium: $202.90 (up from $185)Part B annual deductible: $283 (up from $257)Part A inpatient hospital deductible: $1,736 (up from $1,676)Daily coinsurance for days 61-90 of hospitalization: $434 (up from $419)For retirees on fixed incomes, a bigger share of every Social Security check is going straight to Medicare. And that’s before you account for out-of-pocket spending on prescriptions, specialist visits, or services Medicare does not cover, such as dental, vision, or long-term care.TheStreet has reported on how this Part B increase is eroding the purchasing power of Social Security checks for millions of retirees.One retired librarian’s story shows how quickly the math falls apartSheila Nesbit, 65, recently retired after a long career as a librarian. She lives in Park Forest, a suburb south of Chicago, and she didn’t realize that Medicare would cover less than her former employer-sponsored insurance plan did, CNN explained.When her doctor recommended new orthopedic shoe inserts costing roughly $250, she decided not to buy them. She’s hunting for discount cards to afford a $90 medication that Medicare does not cover.She sometimes skips lunch, and she doesn’t always take her medications for cholesterol, asthma, and high blood pressure. She’s lowered her thermostat and wraps herself in a sweater and two blankets to ward off the cold. Her story is not unusual; it’s the kind of tradeoff that 82 million Americans are now making in some form.Steps you can take to reduce the damage to your budgetYou can’t control what health care costs. But you can take specific steps to limit how much of your household budget it consumes.Review your coverage every yearWhether you’re on an ACA plan, employer coverage, or Medicare, do not assume last year’s plan is still the best fit. Networks change, formulas change, and premiums shift. Compare options during every open enrollment period.Use every assistance program availableIf you’re on Medicare, check whether you qualify for the Medicare Savings Program or Extra Help for Part D prescription costs.If you’re on an ACA plan, verify your income estimate with your state marketplace. Even a small adjustment can change your subsidy amount.Look into drug manufacturer discount programs, GoodRx, or state pharmaceutical assistance programs.Ask your doctor about generic alternatives or therapeutic substitutions before accepting a brand-name prescription.Do not skip medication or delay treatmentStretching prescriptions or postponing procedures might seem like a way to save money, but it typically leads to higher costs later. Talk to your doctor about lower-cost alternatives or patient assistance programs before cutting corners on your care.Build a health care line item into your monthly budgetToo many households treat medical bills as surprises. If you’re on Original Medicare, plan for roughly $3,500 to $7,000 per year in out-of-pocket costs, depending on your health needs. If you’re on an ACA plan, know your deductible and out-of-pocket maximum and set money aside each month.The financial squeeze on American households is tighteningWith millions more expected to lose insurance coverage, health spending projected to consume a fifth of the economy within a decade, and household health deteriorating across the board, the pressure on family budgets is only increasing.Maese, the West Health-Gallup researcher, warned CNN that if more people lose their insurance, the tradeoffs already affecting 82 million Americans will spread even further.If you’re already stretching your budget to cover medical costs, the most important thing you can do is plan now. Review your coverage and seek out every assistance program you qualify for. Treat health care spending like the fixed cost it has become, not an expense you deal with after the bill arrives.​Related: Paying cash for U.S. medical care could save you a fortune

Do investors need bonds in their portfolios?The answer depends on the person. Investors with goals in the three- to 10-year range—say, buying a new home, starting a business, or retiring within the next decade—likely do need them. So do those who are already retired. Bonds are also favored by investors who may not be comfortable with being 100% invested in stocks, no matter their time horizons. Exchange-traded funds that focus on fixed-income securities can be an excellent way for investors to get exposure to bonds. Here are a few reasons:Many ETFs are transparent—most track indexes with very specific duration and credit-quality traits—and offer few surprises.The best ETFs are low-cost, which is even more important when investing in bonds than in stocks: Every extra point paid in expenses is one less point in return, and returns are typically tougher to come by with bonds than with stocks.ETFs are easy to buy and sell.A good place to start your search for the best bond ETFs is with the Morningstar Medalist Rating. ETFs that earn our highest rating of Gold are those that we think are most likely to outperform over a full market cycle.Read more: Bond ETFs Are Having a Moment. Here’s How They Can Benefit Your Portfolio in 2026Here’s the list of the best bond ETFs in three main groups: core bond funds, short-term bond funds, and specialized bond funds.8 Best Core Bond ETFs to Buy NowThese ETFs all land in one of the intermediate-term bond Morningstar Categories and earn our top Medalist Rating of Gold with 100% analyst coverage as of March 2026.Fidelity Investment Grade Bd ETF FIGBFidelity Total Bond ETF FBNDiShares Core US Aggregate Bond ETF AGG iShares Total Return Active ETF BRTR JPMorgan Core Plus Bond ETF JCPBSchwab US Aggregate Bond ETF SCHZSPDR Portfolio Aggregate Bond ETF SPABVanguard Total Bond Market ETF BNDThe highly rated ETFs on this list would be fine choices to anchor the bond portion of an investor’s portfolio, assuming the goals for the money are more than five years away.Read More: Morningstar’s Guide to Fixed-Income InvestingIShares Core US Aggregate Bond ETF, Vanguard Total Bond Market ETF, Schwab US Aggregate Bond ETF, and SPDR Portfolio Aggregate Bond ETF are classified as intermediate-term core bond ETFs by Morningstar, which means they invest in a blend of US investment-grade bonds, including government, corporate, and securitized debt. Fidelity Total Bond ETF, iShares Total Return Active ETF, and JPMorgan Core Plus Bond ETF qualify as intermediate-term core-plus bond ETFs; in addition to investing in investment-grade US bonds, these funds have more flexibility to buy corporate high-yield bonds, bank loans, and emerging-markets debt. If none of these ETFs fits the bill for you, you can find additional top-rated ETFs in The Best ETFs and How They Fit in Your Portfolio.8 Best Short-Term Bond ETFsThese ETFs all land in the ultrashort bond or short-term bond categories and earn our top Medalist Rating of Gold with 100% analyst coverage as of March 2026.JPMorgan Limited Duration Bond ETF JPLDPGIM Short Duration Multi-Sector Bond ETF PSDMPimco Enhanced Short Maturity Active ETF MINTPimco Enhanced Short Maturity Active ESG ETF EMNTSchwab Short-Term US Treasury ETF SCHOSPDR Portfolio Short Term Treasury ETF SPTSVanguard Short-Term Corporate Bond ETF VCSHVanguard Short-Term Treasury ETF VGSHThe top-rated ETFs on this list are good choices for those who are looking to invest in bonds but expect to tap into these investments in the next few years.Both Pimco Enhanced Short Maturity Active ETF and Pimco Enhanced Short Maturity Active ESG ETF qualify as ultrashort bond ETFs. The ETFs in this category favor high-quality bonds with durations of less than 1.0 year.Vanguard Short-Term Corporate Bond ETF falls into our short-term bond category, while both Schwab Short-Term US Treasury ETF and Vanguard Short-Term Treasury ETF land in our short government category. As the category’s name suggests, short-term government ETFs focus exclusively on short-term bonds issued by the US government, while short-term bond ETFs can invest in high-quality corporate bonds as well as government bonds. In both cases, the ETFs favor bonds with durations in the 1.0- to 3.0-year range.8 Best Specialized Bond ETFsThese ETFs all land in one of Morningstar’s specialized bond categories and earn our top Medalist Rating of Gold with 100% analyst coverage as of March 2026.Hartford Strategic Income ETF HFSIJPMorgan Income ETF JPIE Neuberger Berman EM Debt Hard Ccy ETF NEMDSchwab US TIPS ETF SCHP T. Rowe Price Floating Rate ETF TFLR Vanguard Intermediate-Term Corporate Bond ETF VCITVanguard Short-Term Inflation-Protected Securities ETF VTIP Vanguard Tax-Exempt Bond ETF VTEBThe top-rated ETFs on this list are what we’d call “satellite” holdings in a bond portfolio. They aren’t core holdings, but an investor might hold these ETFs to round out a bond portfolio, make a tactical move, or serve some other specialized interest.The list includes the two best bond ETFs for inflation protection: Schwab US TIPS ETF and Vanguard Short-Term Inflation-Protected Securities ETF. Both land in our inflation-protected bond category and invest in securities that adjust their principal values in line with the rate of inflation, which may hold appeal for some investors (particularly retirees).The remaining funds on the list favor different types of bonds (corporate bonds, floating-rate securities). Those funds with long durations, such as the Vanguard Intermediate-Term Corporate Bond ETF, are very sensitive to interest rate changes and very volatile by bond-fund standards. They can be used as a way to benefit from falling interest rates or as a tool for matching long-term liabilities.How to Find More Top ETFs for the Long TermETFs are often equated with low-cost indexing. However, the ETF marketplace has grown increasingly complicated. Some ETFs track a very narrow part of the market or pursue specific themes. Some ETFs invest based on a particular factor or a combination of factors. And now there are actively managed ETFs.Use these Morningstar resources to help find the best ETFs for the long term:Learn about the types of ETFs, their costs, and how to invest in them by reading Morningstar’s Guide to ETF Investing.Find the highest-rated ETFs across all investment categories in The Best ETFs and How They Fit in Your Portfolio.Review Morningstar director of personal finance Christine Benz’s suggested ETF portfolios for those saving for or already in retirement, including Tax-Efficient Retirement-Saver Portfolios for ETF Investors, Tax-Sheltered Retirement-Saver Portfolios for ETF Investors, Tax-Sheltered ESG Retirement-Saver Portfolios for ETF Investors, Tax-Sheltered Retirement-Bucket Portfolios for ETF Investors, and Tax-Sheltered ESG Retirement-Bucket Portfolios for ETF Investors.Research ETFs based on your personal selection criteria by using our Morningstar Investor Screener. The tool, which is available to Morningstar Investor members, allows investors to screen ETFs based on various criteria, including asset class, Morningstar Category, Medalist Rating, and fee level.Visit Morningstar’s ETF page for the latest articles and videos from our ETF specialists.

Success isn’t just built in boardrooms, offices, or businesses. It’s built at home.
For many high achievers, it’s easy to focus all our energy on career goals, growth strategies, and professional wins. But the truth is that the habits we model inside our homes shape something far more important than our next milestone.
They shape the people around us.
Between work deadlines, school schedules, and the constant pace of modern life, it’s easy to fall into survival mode. We respond to the urgent and tell ourselves we’ll focus on well-being later.
But the families that thrive long-term don’t rely on big, dramatic changes. They rely on small habits practiced consistently.
A healthy and resilient family culture isn’t something that happens by accident. It’s built quietly in everyday moments, at the dinner table, during conversations in the car, or through the example parents set without even realizing it.
Success Starts With the Environment You Create
Entrepreneurs and high performers understand something powerful: environment shapes behavior.
We think carefully about the workspaces we build, the people we surround ourselves with, and the tools we use to perform at our best. But the same principle applies inside our homes.
Your home is an ecosystem. The products you use, the routines you establish, and the atmosphere you create all influence how your family feels day to day.
Many families are becoming more intentional about the environments they build, from the food they eat to the products they use around the house.
That’s why some people choose to learn more about The Wellness Company, which focuses on wellness-oriented products designed to support healthier living environments.
Founded in 1985 by Frank VanderSloot, the company was built around the belief that families deserve access to everyday products designed with health and safety in mind.
From cleaning products to supplements and essential oils, the goal is simple: helping households make choices that support well-being over the long term.
The idea isn’t perfection. It’s awareness. When we make small changes in the environments we live in, those changes quietly influence our health and daily habits over time.
The Power of the Dinner Table
If there’s one habit that consistently shows up in studies about strong families, it’s this:
Shared meals matter. Family dinners may seem simple, but they are one of the most powerful rituals a household can create.
Research consistently shows that children who regularly eat meals with their families tend to have stronger emotional health, better academic outcomes, and stronger communication skills.
But the real value isn’t the food. It’s the connection. Dinner creates a natural pause in the day where everyone slows down long enough to talk.
A simple practice many families use is asking everyone to describe their day in one word or share a small win and challenge from the day. These kinds of “emotional check-ins” normalize conversations about feelings and experiences.
And the best part? It doesn’t require elaborate meals or perfect schedules. Even three device-free meals a week can create a powerful sense of connection.
Children Learn More From What You Do Than What You Say
One of the most important truths about parenting is also one of the simplest:
Children watch everything. They don’t just listen to instructions. They observe behavior.
If parents constantly criticize themselves, children learn self-criticism.
If parents reach for their phones the moment they sit down, children learn that screens are how people unwind.
But when parents model positive habits, drinking water, going for walks, apologizing when they make mistakes, children absorb those behaviors naturally.
The goal isn’t to appear perfect. In fact, perfection often sends the wrong message. What matters is consistency.
When children see adults working on habits, trying again after setbacks, and showing resilience, they learn that growth is a lifelong process. That’s a far more valuable lesson than any lecture about discipline or perseverance.
Simple Habits That Strengthen Family Culture
One of the biggest mistakes people make when trying to improve their well-being is attempting to overhaul everything at once. The better approach is to start small.
Here are a few simple habits that can quietly strengthen your family culture over time:

Create device-free moments
Choose a few daily moments, like dinner or the first hour after waking, where phones are put away.
Move together whenever possible
Walk after dinner, stretch in the morning, or turn a living room into a spontaneous dance floor.
Make hydration the default
Keeping water easily accessible encourages healthier daily habits without forcing the issue.
Celebrate small wins
A “wins list” on the refrigerator can highlight positive moments from the week — trying something new, solving a problem, or showing kindness.
Protect sleep routines
Creating a family charging station outside bedrooms helps protect sleep quality and reduce nighttime screen habits.

These small actions may seem insignificant on their own. But over months and years, they shape the culture of a household.
Playing the Long Game
The most important habits aren’t the ones that deliver instant results. They’re the ones that compound over time.
A family that values connection, movement, awareness, and intentional living develops something incredibly powerful: resilience.
Some days will go smoothly. Others won’t. Dinner might happen at the table one night and in the car the next. A planned walk might get skipped. A routine might fall apart during a busy week.
That’s normal. The goal isn’t perfection. The goal is direction.
Every small choice from the conversations you encourage to the environment you create, sends a message to your family about what matters. And over time, those messages become the foundation of a strong, healthy, and supportive home.
Because in the end, success isn’t just about the life you build for yourself. It’s about the culture you build for the people around you.
The post The Habits Successful People Use to Build Strong Families and Meaningful Lives appeared first on Addicted 2 Success.

Nvidia on Monday took the wraps off Vera Rubin, a sweeping new computing platform built from seven chips now in full production — and backed by an extraordinary lineup of customers that includes Anthropic, OpenAI, Meta and Mistral AI, along with every major cloud provider.The message to the AI industry, and to investors, was unmistakable: Nvidia is not slowing down. The Vera Rubin platform claims up to 10x more inference throughput per watt and one-tenth the cost per token compared with the Blackwell systems that only recently began shipping. CEO Jensen Huang, speaking at the company’s annual GTC conference, called it “a generational leap” that would kick off “the greatest infrastructure buildout in history.” Amazon Web Services, Google Cloud, Microsoft Azure and Oracle Cloud Infrastructure will all offer the platform, and more than 80 manufacturing partners are building systems around it.”Vera Rubin is a generational leap — seven breakthrough chips, five racks, one giant supercomputer — built to power every phase of AI,” Huang declared. “The agentic AI inflection point has arrived with Vera Rubin kicking off the greatest infrastructure buildout in history.”In any other industry, such rhetoric might be dismissed as keynote theater. But Nvidia occupies a singular position in the global economy — a company whose products have become so essential to the AI boom that its market capitalization now rivals the GDP of mid-sized nations. When Huang says the infrastructure buildout is historic, the CEOs of the companies actually writing the checks are standing behind him, nodding.Dario Amodei, the chief executive of Anthropic, said Nvidia’s platform “gives us the compute, networking and system design to keep delivering while advancing the safety and reliability our customers depend on.” Sam Altman, the chief executive of OpenAI, said that “with Nvidia Vera Rubin, we’ll run more powerful models and agents at massive scale and deliver faster, more reliable systems to hundreds of millions of people.”Inside the seven-chip architecture designed to power the age of AI agentsThe Vera Rubin platform brings together the Nvidia Vera CPU, Rubin GPU, NVLink 6 Switch, ConnectX-9 SuperNIC, BlueField-4 DPU, Spectrum-6 Ethernet switch and the newly integrated Groq 3 LPU — a purpose-built inference accelerator. Nvidia organized these into five interlocking rack-scale systems that function as a unified supercomputer.The flagship NVL72 rack integrates 72 Rubin GPUs and 36 Vera CPUs connected by NVLink 6. Nvidia says it can train large mixture-of-experts models using one-quarter the GPUs required on Blackwell, a claim that, if validated in production, would fundamentally alter the economics of building frontier AI systems.The Vera CPU rack packs 256 liquid-cooled processors into a single rack, sustaining more than 22,500 concurrent CPU environments — the sandboxes where AI agents execute code, validate results and iterate. Nvidia describes the Vera CPU as the first processor purpose-built for agentic AI and reinforcement learning, featuring 88 custom-designed Olympus cores and LPDDR5X memory delivering 1.2 terabytes per second of bandwidth at half the power of conventional server CPUs.The Groq 3 LPX rack, housing 256 inference processors with 128 gigabytes of on-chip SRAM, targets the low-latency demands of trillion-parameter models with million-token contexts. The BlueField-4 STX storage rack provides what Nvidia calls “context memory” — high-speed storage for the massive key-value caches that agentic systems generate as they reason across long, multi-step tasks. And the Spectrum-6 SPX Ethernet rack ties it all together with co-packaged optics delivering 5x greater optical power efficiency than traditional transceivers.Why Nvidia is betting the future on autonomous AI agents — and rebuilding its stack around themThe strategic logic binding every announcement Monday into a single narrative is Nvidia’s conviction that the AI industry is crossing a threshold. The era of chatbots — AI that responds to a prompt and stops — is giving way to what Huang calls “agentic AI”: systems that reason autonomously for hours or days, write and execute software, call external tools, and continuously improve.This isn’t just a branding exercise. It represents a genuine architectural shift in how computing infrastructure must be designed. A chatbot query might consume milliseconds of GPU time. An agentic system orchestrating a drug discovery pipeline or debugging a complex codebase might run continuously, consuming CPU cycles to execute code, GPU cycles to reason, and massive storage to maintain context across thousands of intermediate steps. That demands not just faster chips, but a fundamentally different balance of compute, memory, storage and networking.Nvidia addressed this with the launch of its Agent Toolkit, which includes OpenShell, a new open-source runtime that enforces security and privacy guardrails for autonomous agents. The enterprise adoption list is remarkable: Adobe, Atlassian, Box, Cadence, Cisco, CrowdStrike, Dassault Systèmes, IQVIA, Red Hat, Salesforce, SAP, ServiceNow, Siemens and Synopsys are all integrating the toolkit into their platforms. Nvidia also launched NemoClaw, an open-source stack that lets users install its Nemotron models and OpenShell runtime in a single command to run secure, always-on AI assistants on everything from RTX laptops to DGX Station supercomputers.The company separately announced Dynamo 1.0, open-source software it describes as the first “operating system” for AI inference at factory scale. Dynamo orchestrates GPU and memory resources across clusters and has already been adopted by AWS, Azure, Google Cloud, Oracle, Cursor, Perplexity, PayPal and Pinterest. Nvidia says it boosted Blackwell inference performance by up to 7x in recent benchmarks.The Nemotron coalition and Nvidia’s play to shape the open-source AI landscapeIf Vera Rubin represents Nvidia’s hardware ambition, the Nemotron Coalition represents its software ambition. Announced Monday, the coalition is a global collaboration of AI labs that will jointly develop open frontier models trained on Nvidia’s DGX Cloud. The inaugural members — Black Forest Labs, Cursor, LangChain, Mistral AI, Perplexity, Reflection AI, Sarvam and Thinking Machines Lab, the startup led by former OpenAI executive Mira Murati — will contribute data, evaluation frameworks and domain expertise.The first model will be co-developed by Mistral AI and Nvidia and will underpin the upcoming Nemotron 4 family. “Open models are the lifeblood of innovation and the engine of global participation in the AI revolution,” Huang said.Nvidia also expanded its own open model portfolio significantly. Nemotron 3 Ultra delivers what the company calls frontier-level intelligence with 5x throughput efficiency on Blackwell. Nemotron 3 Omni integrates audio, vision and language understanding. Nemotron 3 VoiceChat supports real-time, simultaneous conversations. And the company previewed GR00T N2, a next-generation robot foundation model that it says helps robots succeed at new tasks in new environments more than twice as often as leading alternatives, currently ranking first on the MolmoSpaces and RoboArena benchmarks.The open-model push serves a dual purpose. It cultivates the developer ecosystem that drives demand for Nvidia hardware, and it positions Nvidia as a neutral platform provider rather than a competitor to the AI labs building on its chips — a delicate balancing act that grows more complex as Nvidia’s own models grow more capable.From operating rooms to orbit: how Vera Rubin’s reach extends far beyond the data centerThe vertical breadth of Monday’s announcements was almost disorienting. Roche revealed it is deploying more than 3,500 Blackwell GPUs across hybrid cloud and on-premises environments in the U.S. and Europe — the largest announced GPU footprint in the pharmaceutical industry. The company is using the infrastructure for biological foundation models, drug discovery and digital twins of manufacturing facilities, including its new GLP-1 facility in North Carolina. Nearly 90 percent of Genentech’s eligible small-molecule programs now integrate AI, Roche said, with one oncology molecule designed 25 percent faster and a backup candidate delivered in seven months instead of more than two years.In autonomous vehicles, BYD, Geely, Isuzu and Nissan are building Level 4-ready vehicles on Nvidia’s Drive Hyperion platform. Nvidia and Uber expanded their partnership to launch autonomous vehicles across 28 cities on four continents by 2028, starting with Los Angeles and San Francisco in the first half of 2027. The company introduced Alpamayo 1.5, a reasoning model for autonomous driving already downloaded by more than 100,000 automotive developers, and Nvidia Halos OS, a safety architecture built on ASIL D-certified foundations for production-grade autonomy.Nvidia also released the first domain-specific physical AI platform for healthcare robotics, anchored by Open-H — the world’s largest healthcare robotics dataset, with over 700 hours of surgical video. CMR Surgical, Johnson & Johnson MedTech and Medtronic are among the adopters.And then there was space. The Vera Rubin Space Module delivers up to 25x more AI compute for orbital inferencing compared with the H100 GPU. Aetherflux, Axiom Space, Kepler Communications, Planet Labs and Starcloud are building on it. “Space computing, the final frontier, has arrived,” Huang said, deploying the kind of line that, from another executive, might draw eye-rolls — but from the CEO of a company whose chips already power the majority of the world’s AI workloads, lands differently.The deskside supercomputer and Nvidia’s quiet push into enterprise hardwareAmid the spectacle of trillion-parameter models and orbital data centers, Nvidia made a quieter but potentially consequential move: it launched the DGX Station, a deskside system powered by the GB300 Grace Blackwell Ultra Desktop Superchip that delivers 748 gigabytes of coherent memory and up to 20 petaflops of AI compute performance. The system can run open models of up to one trillion parameters from a desk.Snowflake, Microsoft Research, Cornell, EPRI and Sungkyunkwan University are among the early users. DGX Station supports air-gapped configurations for regulated industries, and applications built on it move seamlessly to Nvidia’s data center systems without rearchitecting — a design choice that creates a natural on-ramp from local experimentation to large-scale deployment.Nvidia also updated DGX Spark, its more compact system, with support for clustering up to four units into a “desktop data center” with linear performance scaling. Both systems ship preconfigured with NemoClaw and the Nvidia AI software stack, and support models including Nemotron 3, Google Gemma 3, Qwen3, DeepSeek V3.2, Mistral Large 3 and others.Adobe and Nvidia separately announced a strategic partnership to develop the next generation of Firefly models using Nvidia’s computing technology and libraries. Adobe will also build a cloud-native 3D digital twin solution for marketing on Nvidia Omniverse and integrate Nemotron capabilities into Adobe Acrobat. The partnership spans creative tools including Photoshop, Premiere Pro, Frame.io and Adobe Experience Platform.Building the factories that build intelligence: Nvidia’s AI infrastructure blueprintPerhaps the most telling indicator of where Nvidia sees the industry heading is the Vera Rubin DSX AI Factory reference design — essentially a blueprint for constructing entire buildings optimized to produce AI. The reference design outlines how to integrate compute, networking, storage, power and cooling into a system that maximizes what Nvidia calls “tokens per watt,” along with an Omniverse DSX Blueprint for creating digital twins of these facilities before they are built.The software stack includes DSX Max-Q for dynamic power provisioning — which Nvidia says enables 30 percent more AI infrastructure within a fixed-power data center — and DSX Flex, which connects AI factories to power-grid services to unlock what the company estimates is 100 gigawatts of stranded grid capacity. Energy leaders Emerald AI, GE Vernova, Hitachi and Siemens Energy are using the architecture. Nscale and Caterpillar are building one of the world’s largest AI factories in West Virginia using the Vera Rubin reference design.Industry partners Cadence, Dassault Systèmes, Eaton, Jacobs, Schneider Electric, Siemens, PTC, Switch, Trane Technologies and Vertiv are contributing simulation-ready assets and integrating their platforms. CoreWeave is using Nvidia’s DSX Air to run operational rehearsals of AI factories in the cloud before physical delivery.”In the age of AI, intelligence tokens are the new currency, and AI factories are the infrastructure that generates them,” Huang said. It is the kind of formulation — tokens as currency, factories as mints — that reveals how Nvidia thinks about its place in the emerging economic order.What Nvidia’s grand vision gets right — and what remains unprovenThe scale and coherence of Monday’s announcements are genuinely impressive. No other company in the semiconductor industry — and arguably no other technology company, period — can present an integrated stack spanning custom silicon, systems architecture, networking, storage, inference software, open models, agent frameworks, safety runtimes, simulation platforms, digital twin infrastructure and vertical applications from drug discovery to autonomous driving to orbital computing.But scale and coherence are not the same as inevitability. The performance claims for Vera Rubin, while dramatic, remain largely unverified by independent benchmarks. The agentic AI thesis that underpins the entire platform — the idea that autonomous, long-running AI agents will become the dominant computing workload — is a bet on a future that has not yet fully materialized. And Nvidia’s expanding role as a provider of models, software, and reference architectures raises questions about how long its hardware customers will remain comfortable depending so heavily on a single supplier for so many layers of their stack.Competitors are not standing still. AMD continues to close the gap on data center GPU performance. Google’s TPUs power some of the world’s largest AI training runs. Amazon’s Trainium chips are gaining traction inside AWS. And a growing cohort of startups is attacking various pieces of the AI infrastructure puzzle.Yet none of them showed up at GTC on Monday with endorsements from the CEOs of Anthropic and OpenAI. None of them announced seven new chips in full production simultaneously. And none of them presented a vision this comprehensive for what comes next.There is a scene that repeats at every GTC: Huang, in his trademark leather jacket, holds up a chip the way a jeweler holds up a diamond, rotating it slowly under the stage lights. It is part showmanship, part sermon. But the congregation keeps growing, the chips keep getting faster, and the checks keep getting larger. Whether Nvidia is building the greatest infrastructure in history or simply the most profitable one may, in the end, be a distinction without a difference.

When an AI agent loses context mid-task because traditional storage can’t keep pace with inference, it is not a model problem — it is a storage problem. At GTC 2026, Nvidia announced BlueField-4 STX, a modular reference architecture that inserts a dedicated context memory layer between GPUs and traditional storage, claiming 5x the token throughput, 4x the energy efficiency and 2x the data ingestion speed of conventional CPU-based storage.The bottleneck STX targets is key-value cache data. KV cache is the stored record of what a model has already processed — the intermediate calculations an LLM saves so it does not have to recompute attention across the entire context on every inference step. It is what allows an agent to maintain coherent working memory across sessions, tool calls and reasoning steps. As context windows grow and agents take more steps, that cache grows with them. When it has to traverse a traditional storage path to get back to the GPU, inference slows and GPU utilization drops.STX is not a product Nvidia sells directly. It is a reference architecture the company is distributing to its storage partner ecosystem so vendors can build AI-native infrastructure around it.STX puts a context memory layer between GPU and diskThe architecture is built around a new storage-optimized BlueField-4 processor that combines Nvidia’s Vera CPU with the ConnectX-9 SuperNIC. It runs on Spectrum-X Ethernet networking and is programmable through Nvidia’s DOCA software platform.The first rack-scale implementation is the Nvidia CMX context memory storage platform. CMX extends GPU memory with a high-performance context layer designed specifically for storing and retrieving KV cache data generated by large language models during inference. Keeping that cache accessible without forcing a round trip through general-purpose storage is what CMX is designed to do.”Traditional data centers provide high-capacity, general-purpose storage, but generally lack the responsiveness required for interaction with AI agents that need to work across many steps, tools and different sessions,” Ian Buck, Nvidia’s vice president of hyperscale and high-performance computing said in a briefing with press and analysts.In response to a question from VentureBeat, Buck confirmed that STX also ships with a software reference platform alongside the hardware architecture. Nvidia is expanding DOCA to include a new component referred to in the briefing as DOCA Memo. “Our storage providers can leverage the programmability of the BlueField-4 processor to optimize storage for the agentic AI factory,” Buck said. “In addition to having a reference rack architecture, we’re also providing a reference software platform for them to deliver those innovations and optimizations for their customers.”Storage partners building on STX get both a hardware reference design and a software reference platform — a programmable foundation for context-optimized storage.Nvidia’s partner list spans storage incumbents and AI-native cloud providersStorage providers co-designing STX-based infrastructure include Cloudian, DDN, Dell Technologies, Everpure, Hitachi Vantara, HPE, IBM, MinIO, NetApp, Nutanix, VAST Data and WEKA. Manufacturing partners building STX-based systems include AIC, Supermicro and Quanta Cloud Technology.On the cloud and AI side, CoreWeave, Crusoe, IREN, Lambda, Mistral AI, Nebius, Oracle Cloud Infrastructure and Vultr have all committed to STX for context memory storage.That combination of enterprise storage incumbents and AI-native cloud providers is the signal worth watching. Nvidia is not positioning STX as a specialty product for hyperscalers. It is positioning it as the reference standard for anyone building storage infrastructure that has to serve agentic AI workloads — which, within the next two to three years, is likely to include most enterprise AI deployments running multi-step inference at scale.STX-based platforms will be available from partners in the second half of 2026.IBM shows what the data layer problem looks like in productionIBM sits on both sides of the STX announcement. It is listed as a storage provider co-designing STX-based infrastructure, and Nvidia separately confirmed that it has selected IBM Storage Scale System 6000 — certified and validated on Nvidia DGX platforms — as the high-performance storage foundation for its own GPU-native analytics infrastructure.IBM also announced a broader expanded collaboration with Nvidia at GTC, including GPU-accelerated integration between IBM’s watsonx.data Presto SQL engine and Nvidia’s cuDF library. A production proof of concept with Nestlé put numbers on what that acceleration looks like: a data refresh cycle across the company’s Order-to-Cash data mart, covering 186 countries and 44 tables, dropped from 15 minutes to three minutes. IBM reported 83% cost savings and a 30x price-performance improvement.The Nestlé result is a structured analytics workload. It does not directly demonstrate agentic inference performance. But it makes IBM and Nvidia’s shared argument concrete: the data layer is where enterprise AI performance is currently constrained, and GPU-accelerating it produces material results in production.Why the storage layer is becoming a first-class infrastructure decisionSTX is a signal that the storage layer is becoming a first-class concern in enterprise AI infrastructure planning, not an afterthought to GPU procurement.

General-purpose NAS and object storage were not designed to serve KV cache data at inference latency requirements. STX-based systems from partners including Dell, HPE, NetApp and VAST Data are what Nvidia is putting forward as the practical alternative, with the DOCA software platform providing the programmability layer to tune storage behavior for specific agentic workloads.The performance claims — 5x token throughput, 4x energy efficiency, 2x data ingestion — are measured against traditional CPU-based storage architectures. Nvidia has not specified the exact baseline configuration for those comparisons. Before those numbers drive infrastructure decisions, the baseline is worth pinning down.Platforms are expected from partners in the second half of 2026. Given that most major storage vendors are already co-designing on STX, enterprises evaluating storage refreshes for AI infrastructure in the next 12 months should expect STX-based options to be available from their existing vendor relationships.

“I would likely give little to nothing to his children because they are irresponsible spendthrifts.”

One of the biggest beneficiaries of the Iran conflict has been the battered U.S. dollar, which traded near one of its strongest levels in months on Monday.

The studio’s films took home 11 Oscars after a banner year at the box office and a tumultuous and politically charged sales process for its parent company.