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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.
Category:
E-Commerce
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.
Category:
E-Commerce
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.
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E-Commerce
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
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E-Commerce
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.”
Category:
E-Commerce
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