Reality Check: Inside Americas Next Top Model doesnt begin in 2003, when Americas Next Top Model premiered and took television by storm. It doesnt begin in the 1990s, when eventual host Tyra Banks rose to superstardom in the modeling industry. Instead, it begins in 2020, when the pandemic led a new generation to binge early-aughts reality TV, this time watching with a modern lensand, naturally, tearing it to shreds on TikTok.
From there, Netflixs newest docuseries rewinds to tell the full story of Americas Next Top Model, from its pre-production through its 24 scandalous cycles and into its modern-day legacy, featuring interviews with contestants, producers, and judges, including Banks herself. Reality Check leans into the same trend that inspired its creation: reexamining years-old media, like a cult classic reality TV show, with a critical eye.
What viewers casually did on TikTok in 2020, Reality Check does with finesse. It dissects the surface-level controversies fans already know about, from body shaming to the show’s infamous race-swapping photoshoot (and its oft-forgotten sequel four years later).
Shandi Sullivan [Photo: Netflix]
It also brings new revelations that cast the series in an even darker light, like Cycle 2 contestant Shandi Sullivan alleging that she was sexually assaulted on camera, with production doing nothing to step in or help her. Instead, the docuseries details Top Model portraying the incident as Sullivan cheating on her boyfriend, even filming her tearful call home to break the news to him. Through it all, Banks dodges accountability, even teasing that the show could come back for a 25th cycle.
Reality Check is the latest entry in a trend of exposé documentaries around TV that many young adults watched in their childhoods, cashing in on nostalgia by peddling its opposite. In 2024, Quiet on Set: The Dark Side of Kids TV dove into the controversies surrounding Nickelodeon series, particularly those created under Dan Schneiders tenure as a producer and showrunner. (That series built on the fervor generated by Jennette McCurdys best-selling 2022 memoir Im Glad My Mom Died, which included stories from her time starring in iCarly and Sam & Cat.)
Also in 2024, VICE released Dark Side of Reality TV, a 10-part docuseries with each episode focusing on the behind-the-scenes truth of a different reality TV show, including Toddlers & Tiaras, Hells Kitchen, Survivor, andyesAmericas Next Top Model.
Even as the aesthetics of 2000s pop culture are celebrated and embraced, their actual pop culture artifacts are subject to renewed criticism. Everyone loves to binge-watch. Everyone loves to hate-watch. Documentaries like Reality Check provide the perfect crossover.
Snap is hoping to snap up another revenue stream in its quest to reduce its dependency on advertising. The social media company announced on Tuesday that it will begin offering subscriptions to select creators so they can earn income from their most engaged fans.
In a move that supports both creators and its bottom line, Snap will begin testing Creator Subscriptions next week with a group of 15 Snapchat creators that includes Jeremiah Brown, Harry Jowsey, and Skai Jackson. Combined, these three creators have more than 3 million followers on Snap, and the company is betting that some portion of those followers will convert to paid subscribers to receive exclusive content, priority replies, and an ad-free experience.
Creators will have the ability to set the monthly pricing for their subscriptions within Snap-recommended tiers that range from $4.99 to $19.99 per month, according to reporting by CNBC, and creators will receive approximately 60% of subscription revenue. Starting next Monday, Snapchatters will be able to subscribe to participating subscribers so long as they have Apple devices; the company hasnt said when the feature will be available for Android users.
This launch builds on our continued investment in a creator-first monetization ecosystemone designed to help creators strengthen relationships with their communities and build sustainable, scalable businesses on Snapchat, the company said in a statement.
MOVING BEYOND ADVERTISING
By embracing the creator-to-consumer subscription model, Snapchat is hoping to build on the success of longer-running monetization offerings like the Unified Monetization Program and the Snap Star Collab Studio, both designed for creators.
Snap is focused on revenue diversification, as CEO Evan Spiegel has repeatedly emphasized in recent quarters.
Thats seen the Santa Monica, California-based company test the waters to gauge what (and how much) Snapchatters are willing to pay for social media content. The company launched Snapchat+ in 2022 for $3.99 per month, which unclocks some exclusive features, and about four months ago, it announced it would begin charging for storage plans for Memories on the platform.
Both Snapchat+ and the Memories Storage Plans have proven successful, even if theres been some grumbling among users. Thanks to those subscription offerings, and others, Snap ended 2025 with 24 million subscribers, a 71% increase from the same period in 2024, according to the companys fourth-quarter results released earlier this month.
CAN SUBSCRIPTIONS REVIVE THE STOCK?
By looping in creators with the newest monetization features, Snapchat wants to give them the freedom to experiment while fostering connections on the platform.
We want the next step in our long-term creator monetization journey to be one thats really rooted in real relationships, Jim Shepherd, Snaps head of content partnerships, said in an interview with CNBC.
But the social media platform arrives late to whats already become a crowded market for subscriptionsand at a time when subscription creep is becoming a more vexing issue. Whats more, a recent survey found that Gen Z, a core demographic for Snap, is feeling the subscription fatigue with respect to streaming servicesa sentiment that might extend elsewhere.
And investors remain skeptical about Snaps recent efforts to diversify its revenue stream. The stock fell nearly 2% in mid-day trading on Tuesday, extending a year-to-date selloff of more than 41%.
One of the companies best known for cranking out ultracheap goods is facing a serious investigation in Europe over concerns about illegal products and predatory business practices.
The EUs European Commission said Tuesday that it has opened formal proceedings against Shein under the Digital Services Act, which sets ground rules for online services that Europeans use. In the announcement, the commission says it is targeting Shein over worries that the shopping platform is addictive by design, powered by opaque algorithms, and engages in the sale of illegal goods, including weapons and child sexual abuse material in the form of child-like sex dolls.
Late last year, French watchdog agency the Directorate General for Competition, Consumer Affairs and Fraud Control flagged the Chinese online retailer to authorities after finding sex dolls constituting child sexual abuse material for sale along with other pornographic content not restricted by an age gate. These acts fall within the scope of serious criminal offences under French law, the regulator wrote at the time, noting that the violations could be punishable by imprisonment and a 100,000 fine under the countrys criminal code.
Based on the findings, French authorities initiated a criminal investigation into Shein over the sale and distribution of child sexual abuse material and kicked off a coordinated European investigation under the Digital Services Act. The French consumer protection agency found childlike sex dolls for sale on Chinese e-commerce site AliExpress, owned by Alibaba Group.
In a parallel investigation, French customs agents inspected 200,000 Shein packages for compliance with French laws and found that eight out of 10 products it examined potentially ran afoul of the law, including cosmetics containing banned ingredients and unsafe childrens toys.
In response, Shein said that it would restrict the sale of sex dolls and permanently ban “all seller accounts linked to illegal or non-compliant sex-doll products” on its platform. The fight against child exploitation is non-negotiable for Shein, Shein Executive Chairman Donald Tang said in a statement addressing the controversy. These were marketplace listings from third-party sellersbut I take this personally.
Regulators catch up to fast fashion
Fast fashion retailers like Shein and Temu, which ship lightning fast from China and offer hundreds of thousands of designs, have exploded in recent years. Regulators are only beginning to catch up to the controversial business model, which has seen Shein sprint toward $2 billion in revenue in 2025, in spite of the companys many headwinds.
The online shopping frenzy over trendy, ultracheap clothes took off during the pandemic and got a massive boost from TikTok, where Gen Z influencers reveal and review their clothing shipments in haul videos.
Shein and other fast fashion retailers rely on a test and repeat model that throws many thousands of clothing designs at the wall to see what sticks, producing small batches of 50 to 100 items. Designs that flop are swiftly retired and if a design takes off, its production scales up to meet demand.
While the fast fashion trend keeps TikTok creators well-stocked with fresh content, the phenomenons major players have faced an array of serious concerns during their rise. The fast fashion worlds quick cycles and frequent returns create vast amounts of waste destined for the landfill, not to mention the emissions consequences of shipping so many small packages around the globe on short notice.
Beyond the steep environmental price of cheap goods, investigations have found that the laborers constantly sewing new designs for Shein and its ilk often work grueling shifts in difficult conditionsand sometimes those workers arent even old enough to legally be there.
Shein also got wrapped up in Trumps tariff wars last year, when the president ended the de minimis loophole that made it possible for Chinese companies to ship small, low-value packages into the U.S. without paying tariffs and extra duties. EU finance ministers followed suit late last year, announcing that Europe would begin to impose customs duties on low value packages shipped into Europe some time in 2026.
Right now, criminal and state-sponsored hackers are intercepting and storing encrypted data they cannot yet decode. Likely targets include everything from corporate secrets and medical records to legal agreements and military communications. Why would these actors bother to steal data they cant read? Because they are betting on developments in quantum computing that will eventually let them crack this encrypted data wide open.
This isnt a fringe theory. The NSA (National Security Agency), NIST (National Institute of Standards and Technology), and ENISA (European Agency for Cybersecurity) are all treating this harvest now, decrypt later scenario as a live threat that is serious enough to demand immediate action. The NSA has mandated that all U.S. national security systems must transition to quantum-resistant cryptography by 2035with new acquisitions required to be compliant by 2027. In Europe, ENISA issued updated guidance in April 2025 warning that the threat is sufficient to warrant caution, and to warrant mitigating actions to be taken, and recommending that organizations begin deploying post-quantum cryptography immediately. NIST has launched a parallel global effort to develop the new cryptographic standards on which these transitions will depend.
The message from all three bodies is the same: organizations are running a grave risk if they wait until quantum computers can break current encryption standards to begin upgrading. That is the reason business leaders need to pay attention to quantum computing nownot because the technology is ready, but because the risk is grave, and the cost of preparation is trivial compared to the cost of being caught flat-footed.
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Quantum Computing 101
Classical computers store and process information as bits, where each bit is either a 0 or a 1. Quantum computers, by contrast, exploit the properties of quantum mechanics, working instead with qubits, which can exist in multiple states simultaneously. Tapping into the unusual features of quantum states in this way allows quantum computers to explore vast numbers of possibilities in parallel rather than working through them one by one.
This doesnt mean that quantum computers are generally better than, or a replacement for, classical computers. Rather, quantum computers are a specialist tool for handling a specific class of problems that involve enormous combinatorial complexitythe kind of problems where the number of possible solutions explodes so fast that even the most powerful classical supercomputers cant meaningfully explore them. In areas like these, quantum computers have the potential to offer not just incremental improvements on classical computing, but to redefine what is computationally possible in whole fields.
Logistics optimization, financial modeling, drug discovery, and cryptography are all examples of fields that involve exactly the kind of combinatorial complexity that quantum computers are built to handle. Of these, it is cryptography that demands the most immediate attention.
Hype and Reality
Disentangling the reality from the hype about quantum computing is genuinely difficultand not just for casual observers. In January 2025, Nvidia CEO Jensen Huang suggested that useful quantum computers could be decades away, sending stocks in quantum-related companies into freefall. By mid-2025, he was far more bullish, describing the field as being on the cusp of an inflection point. If one of the most technically informed CEOs on the planet can shift his assessment that dramatically in six months, the rest of us should be humble about our ability to call the timing.
As is often the case with new technologies, there is real momentum on both sides. On the bullish side, Google announced in late 2024 that its Willow quantum chip solved a problem in five minutes that they claimed would have taken a classical supercomputer ten septillion years. In February 2025, Microsoft unveiled its Majorana 1 chip, claiming that they had implemented a new approach to building qubits that could scale faster than competing designs. IBM continues to publish ambitious roadmaps.
Credible researchers such as Nathalie de Leon, an experimental quantum physicist at Princeton, say that there has recently been a vibe shift in the fielda growing sense that useful quantum machines could arrive within ten years rather than thirty. I am much more certain that quantum computation will be realized, and that the timeline is much shorter than people thought, Dorit Aharonov, a computer scientist at Hebrew University in Jerusalem, told Nature. Capital markets are paying attention too.
But the bear case is also serious. Quantum computing stocks like Rigetti and D-Wave have traded at more than 500 times estimated saleswith almost no real-world revenue and few practical applications. The machines remain fragile, error-prone, and require operating temperatures near absolute zero. There is a persistent and uncomfortable pattern in the research: researchers working on quantum computing announce a speedup, and classical computing researchers almost immediately find ways to match it. Quantum computing could be the next big thingor it could be the next hot air balloon.
The point isnt to resolve this debate. The point is that smart, informed people disagree sharply about whenor whetherquantum computing will deliver on its promise. And that disagreement should sound uncomfortably familiar.
Weve Been Here Before
When ChatGPT launched in November 2022, it became the fastest-growing consumer application in history. Within two months, it had 100 million users. Enterprises scrambled to adapt. Boards demanded AI strategies overnight. It felt like a bolt from the blue.
But it wasnt. Machine learning as a discipline dates back to the 1950s. Neural networks were being explored seriously in the 1980s. Even looking at the more recent past, the technology had been visibly advancing for over a decade. In 2016, AlphaGo defeated world champion Lee Sedol 41. In 2017, transformer architecture was introduced, which became the foundation for modern large language models.
This is not a story about AI. Rather, its a long-running, frequently recurring story about institutional blindness to technological disruption. With AI, the technology was visibly coming, and still most companies were caught without a plan, a team, or any institutional understanding of what was happening. Quantum computing is following a similar pattern: once again we see real scientific progress, genuine uncertainty about timescales, sharp disagreement among experts, and a business community that is mostly not paying attention.
Those who cannot remember the past are doomed to repeat it, said the philosopher George Santayana. So let us remember the general state of unpreparedness around AI, and try to do better with quantum computing.
What Businesses Should Do Today
The whole point of learning from the AI experience is that preparation doesnt have to be expensiveit just has to start early.
1. Develop organizational literacy. You dont need to hire quantum physicists. You need a small number of peoplein strategy, technology, and risk managementwho can follow developments, read past the hype, and flag when something becomes relevant to your business. The goal is to ensure that when a headline lands about a qubit milestone or a new standard, someone in your organization can tell you whether it matters and why.
2. Identify your exposed workflows. The potential impact of quantum computing on your business extends well beyond cryptography. Which of your core operations involve the kind of complex optimization, simulation, or modeling processes that could be disruptedor where a competitor with quantum capabilities could leapfrog you? You dont need to solve for this today. You need to know where to look when the time comes.
3. Define your trigger conditions. What specific developmentsa demonstrated commercial application in your sector, a regulatory mandate, a breakthrough in error correctionwould move you from monitoring to investing? Set these thresholds now, so that when news breaks, youre executing a plan rather than reacting to a headline.
4. Get your cryptographic house in order. This is the most concrete and most urgent action. The NSA, ENISA, and NIST are all moving toward post-quantum cryptographic standards, but those standards are still evolving. That means you need two things. First, you need an understanding of where encryption actually sits in your organizationwhich of your systems depend on which cryptographic standards and where does encrypted data flow to third parties whose security posture you dont control? Second, you need architecture that lets you swap cryptographic components independently when the standards settle, without forcing a rebuild of everything around them. Engineers call this crypto-agility. Think of it as future-proofing your security not against a specific threat, but against the certainty that the regulatory and threat landscape will keep shifting.
None of this is to say that quantum computing is certain to become practically relevant to your organization in the near future or even in any future. Experts themselves disagree over this question. The point is that businesses cannot afford to wait for the experts to reach consensus. If quantum computing becomes practically useful within the next decade, the implications could be enormous. The cost of paying attention is low; the cost of being caught flat-footed could be devastating.
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Hotel magnate Thomas Pritzker will step down as the executive chairman of Hyatt Hotels after details of his affiliation with Jeffrey Epstein were revealed in documents related to the burgeoning investigation of ties between the notorious sex trafficker and the elite and powerful.
Pritzker, in a prepared statement, said he deeply regrets his association with Jeffrey Epstein and Ghislaine Maxwell, a long time associate of Epstein who is serving a 20-year sentence for sex trafficking.
I exercised terrible judgment in maintaining contact with them, and there is no excuse for failing to distance myself sooner, Pritzker said in a statement. “I condemn the actions and the harm caused by Epstein and Maxwell and I feel deep sorrow for the pain they inflicted on their victims.
There are numerous emails between Pritzker and Epstein included in a cache of Epstein-related documents recently released by the U.S. Department of Justice, with several detailing attempts for dinner meet ups and invitations to various functions.
Interactions between the two continued even after Epstein pleaded guilty in 2008 to soliciting prostitution from an underage girl. Emails made public late last year show the crime did little to diminish the desire of that network to stay connected to the financier.
Epstein died by suicide while incarcerated in 2019.
Pritzker, 75, who is the cousin of Illinois Governor JB Pritzker, was the executive chairman at Hyatt for more than 20 years. His retirement is effective immediately. Hyatt CEO Mark Hoplamazian will succeed Pritzker as chairman.
Hyatt has more than 1,500 hotels and all-inclusive resorts in more than 83 countries.
Revelations of ties to Epstein have led to the departure or ousting of multiple high-profile individuals in recent days.
Dubai announced last week that it was replacing the chairman of one of the worlds largest logistics companies, DP World, because of his ties to Epstein.
Also last week, Kathy Ruemmler, the top lawyer at storied investment bank Goldman Sachs and former White House counsel to President Barack Obama, announced her resignation after emails between her and Jeffrey Epstein showed a close relationship where she described him as an older brother and downplayed his sex crimes.
Brad Karp resigned as chairman of one of the most prestigious U.S. law firms earlier this month, saying news coverage of his exchanges with Epstein had created a distraction.
Karp had served as chairman of Paul, Weiss, Rifkind, Wharton & Garrison since 2008. The New York firm has advanced the cause of civil rights, handled the legal affairs of corporate power brokers and grown into a multibillion-dollar global enterprise.
Late last year, King Charles III striped his brother, formerly Prince Andrew, of all his titles and honors, for his relationship with Epstein. This month, King Charles said that he is ready to support UK police examining claims that his brother gave confidential information to Epstein.
Michelle Chapman, AP business writer
Restaurant operators have been automating customer service processes for years. Implementing kiosks, self-checkout, and mobile ordering has helped margins and cut labor costs. But now there’s a problem. Friendliness scores dropped 12 points in just one year. Thirty-three percent of customers actively avoid restaurants that feel too automated. And AI is about to flood the market.
Here’s the choice operators face: double down on customer-facing automation and watch friendliness scores keep falling or use AI differently. Its time to stop automating what customers value and instead start automating what they don’t see.
Smart operators recognize that having AI take orders is not the win. The win is using AI to orchestrate back-of-house operations. That includes tasks like:
Making sure your kitchen doesn’t run out of the appetizer everyone wants on Friday night.
Triggering loyalty promos when inventory starts piling up.
Adjusting labor schedules in real time when online orders spike.
Thats AI as a conductor, coordinating information across your tech stack so your staff can focus on what drives loyalty, making guests feel seen.
THE NEXT AI REVOLUTION
There IS a consumer-facing AI revolution coming. Just not the one operators expect. It’s not in the dining room. It’s on phones, in cars, and through smart speakers.
Half of consumers already use AI-powered search for buying decisions. Soon they’ll place orders directly through ChatGPT or voice assistants or their car dashboard.
Before long, customers will say, “Hey Siri, order our usual from [Restaurant]” while they are driving. Soon they will be able to order a pizza from the ad they see while watching a game. This isn’t science fiction. The infrastructure is already in everyone’s pockets and living rooms.
So now you’ve got a new front door. Great. Except most operators can’t even walk through it. Why? Because their tech stack is a mess:
POS doesn’t talk to inventory.
The loyalty platform won’t integrate with voice ordering.
Menu data is scattered.
Operators deploying chatbots to replace hostesses? They’re building on sand. The ones investing in integrated platforms that let AI coordinate inventory, labor, loyalty, and ordering? They’re building the foundation. When voice ordering becomes default, operators can capture more market share.
3 AUTOMATION STRATEGIES
Successful automation requires going back to the basics.
1. Audit your tech stack. Look for integration gaps. If your systems can’t share data, you’re not ready.
2. Stop automating guest interactions. Kill pilot programs. Instead, shift the budget to technology that supports operational intelligence, such as predictive inventory, dynamic scheduling, loyalty engines that learn.
3. Clean up your menu data. Make it structured with consistent item names, modifiers, and rules that machines can understand. Make it API-ready, so other systems can reliably query whats available and order it correctly. When voice ordering goes mainstream in 2026, restaurants that can’t be found by AI agents will be invisible. Simple as that.
Here’s what it comes down to. AI isn’t replacing your people. It’s making them better. And it’s making sure you show up when someone says “order pizza” to their car. Miss that, and you’re invisible.
Savneet Singh is the president and CEO of PAR Technology Corp.
Nothing is certain, they say, but death and taxes. But a new idea from Meta could add social media to that list.
The tech giant was granted a patent in December that would allow it to simulate a user via artificial intelligence when he or she is absent from the social network for extended periods, including, “for example, when the user takes a long break or if the user is deceased.”
The patent covers a bot that could simulate your activity across Metas products, including Facebook, Instagram, and Threadsmaking posts, leaving comments, and interacting with other users. It could even, potentially, communicate directly with people via chats or video calls, the patent reads.
Andrew Bosworth, Metas chief technology officer, is listed as the primary inventor, and the patent was first filed in November 2023. A Meta spokesperson tells Fast Company the company has “no plans to move forward with this example.”
Withdrawing from a social media platform can affect “the user experience of several users,” the patent reads. “The impact on the users is much more severe and permanent if that user is deceased and can never return to the social networking platform.”
Creepy? Sure seems it. Unprecedented? Not as much as you might think.
In 2021, Microsoft obtained a patent for a chatbot that would let you talk with dead people, both loved ones and celebrities. Like Meta, Microsoft said it had no plans to use the technologyand Tim OBrien, Microsofts general manager of AI programs at the time, said in a social media post he agreed it was “disturbing.” Meanwhile, startups like Eternos and HereAfter AI let people create a “digital twin” that can engage with loved ones after they have passed away.
Meta first publicly discussed the concept of a chatbot for the dead about two-and-a-half years ago, when founder Mark Zuckerberg, in an interview with podcaster Lex Fridman (in the Metaverse, of course), said, If someone has lost a loved one and is grieving, there may be ways in which being able to interact or relive certain memories could be helpful. Zuckerberg did note, however, that the technology could become “unhealthy.”
Metas take on a postmortem chatbot would analyze user-specific data, including posts, voice messages, chats, comments, and likes, to build a sense of who the person was. It would amalgamate that data into a digital persona designed to mimic the users activity.
The bot would identify that any responses were not actually generated by the user, the patent says, but rather were the result of a simulation.
Now, there are some hurdles Meta doesnt mention in the patent. What people say in a direct message to a close friend or loved one isnt necessarily meant for wider consumption. Picture, for instance, one spouse venting to the other about how frustrated they were with their child after some “terrible twos” or teenage incidentonly for that child to later be told by the bot how much they annoyed their now-dead loved one.
After all, AI has yet to grasp social niceties, or when silence or a white lie is better than the truth.
Presently, when someone dies, Meta offers several options for survivors. The page can be permanently removed (assuming you have the necessary paperwork, such as a death certificate), or it can be turned into a memorial, where people can read past posts and leave messages of their own.
As unpleasant as the topic is, Meta has good reason to think about death. One study predicts that by 2050, the number of dead users on Facebook will outnumber the living. By 2100, there could be more than 4.9 billion dead profiles on the platform.
Variant, a generative design tool that promises endless UI exploration, recently introduced a feature most creative people and designers have used for decades: the eyedropper. In Variant, the tool picks vibes: It lets you click on one AI-generated interface and inject its aesthetic DNAtypography, spatial relationships, and color palettesinto another. After so much hype around vibecoding and its text-based imprecision, seeing a familiar, direct manipulation tool applied to generative AI feels great.
The new AI modality takes a nice step to close the gap between the impenetrable ways of large language model black boxes and the tools designers actually use with their eyes and hands. Adopting a universally understood tool to control AI in any way other than words is exactly the kind of innovation the sector needs now.
Its just too bad that Variant itself is the vessel for it. The tools underlying AI engine suffers from a distinct lack of differentiation. Everything it makes looks flat and same-y, so the new style absorb-and-drop tool is not really that useful. Yes, the transformed UI changes, but the results already looked very similar anyway (except for the color palettes).
That said, the implementation is cute. When you click on a previously generated UI, the eyedropper animates the design as it is sucking its soul. You then move the eyedropper, click on another generated UI, and the new style spills over it, rearranging it to match the source. Its a satisfying bit of UI theater, an illusion broken by the fact that you have to wait a little to see the results, as the AI works it all out.
The problem is the little variance in Variant. You cant eyedrop a bitmap image or a Figma project and tell the AI, make this new app UI look like this. Currently, Variants eyedropper feels like trying to paint in Photoshop when your palette only contains five shades of beige.
A for effort
Thats too bad, considering the eyedropper is one of the most resilient and powerful metaphors in computing history. The concept dates back to SuperPaint in 1973, which introduced the ability to sample hue values from a digital canvas. While MacPaint popularized digital painting tools in 1984, it was Adobe Photoshop 1.0 in 1990 that locked the eyedropper icon as the standard for color sampling.
Then, in 1996, Adobe Illustrator 6.0 evolved the tool into a style thief. It allowed designers to absorb entire sets of attributesstroke weights, fill patterns, and effectsand inject them into other objects. Now Variant is effectively trying to take this to its UI design arsenal. The difference is that Adobes tools offered precision. You knew exactly what you were getting. With Variant, you are making a visual suggestion to a probabilistic engine and hoping for the best.
But it is a good change that highlights why we need more tools like this eyedropper and fewer text prompts. Unlike the latest generation of multi-modal video generative AIs, the lack of precision in vibecoding tools is unnerving to me. It reminds me of an exercise I did in communication design class, back in college: A professor made us play a game where one student built a shape with Tangram pieces and had to verbally describe to a partner how to reproduce it with another Tangram set. It was impossible to match it.
We are humans, orders of magnitude better semantic engines than any AI, and even we fail at describing visuals with words. We need interfaces that allow for direct, exact manipulation, not just crossing fingers and hoping for the best. Variants eyedropper shows us the way. Generative AI tool makers, more of this, please. Stop forcing designers to talk to the machine, and let us show what we want.
We made a tool that lets you absorb the vibe of anything you point it at and apply it to your designsIt's absurd and it just worksStyle Dropper, now available in @variantui pic.twitter.com/B3eXDntYtw— Ben South (@bnj) February 10, 2026
The new year has so far not been kind to the share price of Big Tech stocks, particularly the so-called Magnificent 7. These seven companiesAlphabet, Amazon, Apple, Meta, Microsoft, Nvidia, and Teslaare Americas tech crown jewels.
Combined, they have their hands in the hottest areas of tech, including artificial intelligence, mobile computing, chipmaking, and transportation. Yet all of these tech companies have seen their share prices decline since the beginning of the year. Here are some possible reasons why.
The Magnificent 7 is seeing red in 2026
As of this writing, there isnt a single Magnificent 7 stock in the green for 2026. Their year-to-date returns are as follows:
Alphabet Inc. (Nasdaq: GOOG): down 3.3%
Amazon.com, Inc. (Nasdaq: AMZN): down 13.5%
Apple Inc. (Nasdaq: AAPL): down 4.8%
Meta Platforms, Inc. (Nasdaq: META) down 2.7%
Microsoft Corporation (Nasdaq: MSFT): down 17.4 %
Nvidia Corporation (Nasdaq: NVDA): down 1.6%
Tesla, Inc. (Nasdaq: TSLA): down 8.2%
While all seven companies have their own strengths (Amazon, e-commerce; Nvidia, AI chips; Apple, smartphones, etc.), they share one thread: they are traded on the already tech-heavy Nasdaq.
And given the massive market caps of these companies, all seven have an outsized impact on the Nasdaq as a whole. Keeping that in mind, its little surprise that the NASDAQ Composite itself is down over 3% year to date as well.
The question is why? Here are two of the most likely reasons.
AI capex spend is immense
In the business world, capex refers to a companys capital expenditurehow much money a business spends on building out assets in order to grow its business, and thus its finances.
Capex is why the phrase you have to spend money to make money exists. But while it has been normal for decades for tech giants to spend billions in capex per year, lately capital expenditures are explodingreaching highs never seen before.
The Motley Fool estimated that in 2025, the Magnificent 7 spent about $400 billion on AI-related capex. In 2026, that number is set to grow by around 70% to reach $680 billion. That is a staggering sum of money on a technology that no tech company has found a way to make a profit from yet.
What many investors have begun to increasingly worry about is that if the ever-present threat of an AI bubble does materialize, the Magnificent 7 companies, particularly those that have had massive capital expenditures on the technology, like Amazon, Alphabet, and Microsoft, might not ever see a return on that investment.
Economic and global uncertainty abounds
Outside the immediate fears of overzealous AI capex and an AI bubble, the Magnificent 7 are also vulnerable to broader economic and geopolitical uncertainties.
President Trumps penchant for announcing tariffs out of the blue has harmed relations with Americas closest economic allies and trading partnersand caused massive uncertainty for businesses. These tariffs have also raised the costs of goods for American consumers. When prices rise, and incomes dont, people tend to cut back on spending, which slows the economy.
And when the economy slowsor people worry it willinvestors tend to sell off riskier investments, or investments where theyve already made a good return, to protect their profits. While shares of Magnificent 7 companies have delivered massive returns over the last decade, they are also highly volatile. And this volatility, when combined with broader market uncertainty, generally causes investor apprehension, leading to further selloffs.
Of course, theres no guarantee where Mag 7 stocks go from here. If AI bulls are right and we are on the cusp of unprecedented AI prosperity, its reasonable to assume that the fall in Mag 7 stocks at the start of 2026 has so far just been a temporary anomaly, and AI-related stocks like those in the Mag 7 will be seeing plenty of green in the years ahead.
However, if the AI bubble does indeed burst and takes the broader economy down with it, 2026 year-to-date declines in Mag 7 stock prices so far could seem relatively minor compared to what is yet to come.
When it comes to EVs, a bigger battery isnt always better.
Ford Motor Company is making that bet as part of its effort to manufacture a new suite of more affordable electric vehiclesbeginning with a $30,000-starting-price mid-size electric truck set to launch in 2027.
To get more out of a smaller battery, Ford has had to reimagine every step of its manufacturing process. It has scrapped the typical assembly line process in favor of what the automaker calls its Ford Universal EV Platform, and simplified every part of its EV, from the miles of wiring inside the electric system to the number of parts that make up its frame.
And its had to rethink the battery itself, to make it both more efficient and less expensive to produce. Ford credits many of those innovations to the team from Auto Motive Power, an EV charging startup Ford acquired back in 2023.
[Photo: Ford]
Ford Bounties to increase efficiency
Batteries are a massive challenge to designing affordable, efficient EVs. The battery makes up at least 25% of an EVs total weight and around 40% of its total cost.
In recent years, EV batteries have kept getting bigger. A bigger battery can add miles to an EVs range, but that also means adding more weight, which makes an EV less efficient, and potentially more difficult to handle. It also means more production costs, which could make that EV more expensive.
To make more affordable EVs, then, Ford has rethought every part of its EV in service of that battery.
Every engineer, whether working on the vehicles aerodynamics or its interior ergonomics, uses metrics that Ford calls bounties to weigh design tradeoffs in terms of how they affect the vehicles range and battery costs.
Alan Clarke [Photo: Ford]
That has led to a system-level optimization that the team has done to turn over every rock to find dollars of cost and watts of efficiency, says Alan Clarke, executive director of Fords Advanced EV Development department.
Ford removed 4,000 feet of wiring from its Universal EV Platform, for example, shaving off 22 pounds compared to the wiring used in Fords first-gen electric SUV. While the Ford Maverick has 146 structural parts in its frame, Fords forthcoming midsized EV will have just two parts, thanks to a lighter and simpler “unicasting” process.
[Photo: Ford]
A more efficient battery
Besides the design tradeoffs it made, Ford also redesigned its battery to make it both smaller and more efficient. That can translate to a better range and charging experience for customers, too.
The pipe of electrons coming out of the wall is always the same for every customer, Clarke says. But how many miles that translates into is directly defined by efficiency of the power electronics and efficiency of the vehicle.
[Photo: Ford]
In its forthcoming midsized EV, Ford will use lithium-iron-phosphate, or LFP, batteries. With no nickel or cobalt, these batterieswhich are common in Chinese EVsuse less expensive chemical ingredients than lithium ion and other battery types.
How efficient an EV battery is depends largely on its software, and thats where the team from Auto Motive Power comes in.
An EV battery pack is composed of multiple cells, and “the performance of that battery pack is limited by your worst cell,” Clarke explains. Battery cells are sensitive to temperature, voltage, and other conditions around them.
“You want to buy [an EV] from whatever company understands their batteries the best, thermally manages them the best from a software standpoint, can measure where they are and balance them and charge them at the rates that don’t deteriorate them,” he adds.
The E-box is a single module that controls power distribution, battery management, and provides AC power back to your home during an outage. [Photo: Ford]
Algorithms can monitor a batterys voltage, temperature, and regenerative braking in order to maximize the vehicles energy use.
Software controls how an EV takes energy out of its battery and puts it into the vehicle’s drive unit. And it also allows the automaker to optimize a battery in real time, responding to the drivers behaviors and real-world data to reduce battery degradation and protect its lifespan.
Each customer has different ways of utilizing batteries, explains Anil Paryani, formerly the CEO of Auto Motive Power and now an executive director of engineering at Ford.
In Arizona, they might have different heat challenges . . . so we have user-optimized controls to minimize those trade offs, he says.
Sometimes customers just have different charging behaviors. For example, Paryani says that his mom lives in a condo, and so she almost exclusively uses fast chargers, which can negatively impact an EVs battery life.
What do we have to do to avoid [battery] deterioration? he says. We are addressing that with our software.
Ford is making its battery cells at its BlueOval Battery Park in Michigan.
Akshaya Srinivasan leads vehicle efficiency and performance for the Universal EV Platform team, helping develop bounties. [Photo: Ford]
Staying a startup inside Ford
Auto Motive Power was founded in 2017, and was previously a supplier to Ford before it was acquired by the automaker in 2023.
At the time, the team was still operating as a very scrappy startup, Paryani says. Becoming part of a $56 billion automaker could have drastically changed that, but they were able to maintain that startup energy.
Executives decided to keep the team walled off, Paryani says, so that we can take design risks that I don’t think traditional auto companies would ever think of taking.
[Photo: Ford]
Big companies like Ford can often get caught up in analysis paralysis, Clarke admits, while startups are known for failing fast. Paryani and his team held on to that ethos, while taking advantage of Fords resources, like access to its EV development center.
[Through] all of the different things that Anil’s team have tried, we’ve learned so much about different materials, interaction between different devices, that we wouldn’t have, Clarke says. “Or in order to learn it, we probably would have spent two years building models and realizing it wasn’t a good idea.”
Paryanis team, instead, tried out multiple ideas quickly through prototypes. This work is crucial to developing better EVs, which are ultimately still an early technology.
“Internal combustion engine vehicles have had 120 years of maturation, of engineering work, of optimization, of innovation, that have gone into them,” Clarke says.
EVs, by contrast, are in “inning oneor maybe inning two.”
