Radically different
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Good morning. Big news: I’ve convinced at least one other STAT staffer to re-read “The Odyssey” with me ahead of the movie this summer. Starting today, that means we’ll read three books (chapters), or about 1,500 lines, per week for the next eight weeks. Care to join us?
Artificial intelligence is moving quickly in the enterprise, from experimentation to everyday use. Organizations are deploying copilots, agents, and predictive systems across finance, supply chains, human resources, and customer operations. By the end of 2025, half of companies used AI in at least three business functions, according to a recent survey.
But as AI becomes embedded in core workflows, business leaders are discovering that the biggest obstacle is not model performance or computing power but the quality and the context of the data on which those systems rely. AI essentially introduces a new requirement: Systems must not only access data — they must understand the business context behind it.
Without that context, AI can generate answers quickly but still make the wrong decision, says Irfan Khan, president and chief product officer of SAP Data & Analytics.
“AI is incredibly good at producing results,” he says. “It moves fast, but without context it can’t exercise good judgment, and good judgment is what creates a return on investment for the business. Speed without judgment doesn’t help. It can actually hurt us.”
In the emerging era of autonomous systems and intelligent applications, that context layer is becoming essential. To provide context, companies need a well-designed data fabric that does more than just integrate data, Khan says. The right data fabric allows organizations to scale AI safely, coordinate decisions across systems and agents, and ensure that automation reflects real business priorities rather than making decisions in isolation.
Recognizing this, many organizations are rethinking their data architecture. Instead of simply moving data into a single repository, they are looking for ways to connect information across applications, clouds, and operational systems while preserving the semantics that describe how the business works. That shift is driving growing interest in data fabric as a foundation for AI infrastructure.
Traditional data strategies have largely focused on aggregation. Over the past two decades, organizations have invested heavily in extracting information from operational systems and loading it into centralized warehouses, lakes, and dashboards. This approach makes it easier to run reports, monitor performance, and generate insights across the business, but in the process, much of the meaning attached to that data — how it relates to policies, processes, and real-world decisions — is lost.
Take two companies using AI to manage supply-chain disruptions. If one uses raw signals such as inventory levels, lead times, and supply scores, while the other adds context across business processes, policies, and metadata, both systems will rapidly analyze the data but likely come up with different conclusions.
Information such as which customers are strategic accounts, what tradeoffs are acceptable during shortages, and the status of extended supply chains will allow one AI system to make strategic decisions, while the other will not have the proper context, Khan says.
“Both systems move very quickly, but only one moves in the right direction,” he says. “This is the context premium and the advantage you gain when your data foundation preserves context across processes, policies and data by design.”
In the past, companies implicitly managed a lack of context because human experts provided the missing information, but with AI, there is a shortfall and that creates serious limitations. AI systems do not just display information; they act on it. If a system does not explain why data matters, an AI model may optimize for the wrong outcome. Inventory numbers, payment histories, or demand signals might be accurate, but they do not necessarily reveal which customers must be prioritized, which contractual obligations apply, or which products are strategically important. As a result, the system can produce answers that are technically correct but operationally flawed.
This realization is changing how companies think about AI readiness. Most acknowledge that they do not have the mature data processes and infrastructure in place to trust their data and their AI systems. Only one in five organizations consider their approach to data to be highly mature, and only 9% feel fully prepared to integrate and interoperate with their data systems.
The emerging solution is a data fabric: An abstraction layer that spans infrastructure, architecture, and logical organization. For agentic AI, the fabric becomes the primary interface, allowing agents to interact with business knowledge rather than raw storage systems. Knowledge graphs play a central role, enabling agents to query enterprise data using natural language and business logic.
The value of the data fabric relies on three components: Intelligent compute to provide speed, a knowledge pool to provide business understanding and context, and agents to provide autonomous action are grounded in that understanding. What makes this powerful is how these capabilities work together, says Khan.
The technology provides the architecture — a foundation that makes agent-to-agent communication and coordination possible. The process will define how businesses and IT share ownership, and establish governance and a culture in which people trust enough to adopt it. Now all three things must work together for a business data fabric to truly be successful.
“It empowers confident, consistent decisions, and when these elements all come together, AI just doesn’t analyze and interpret the data — it drives smarter, faster decisions that really create business impact,” he says. “This is the promise of a thoughtfully designed business data fabric, where every part reinforces the other, and every insight is grounded in trust and clarity.”
Technically, building a data-fabric layer requires several capabilities. Data must be accessible across multiple environments through federation rather than forced consolidation. A semantic or knowledge layer is needed to harmonize meaning across systems, often supported by knowledge graphs and catalog-driven metadata. Governance and policy enforcement must also operate across the fabric so that AI systems can access data securely and consistently.
Together, these elements create a foundation where AI interacts with business knowledge instead of raw storage systems — an essential step for moving from experimentation to real enterprise automation.
In the emerging era of agentic AI, the responsibility for monitoring, analyzing, and making decisions based on data increasingly shifts to software. AI agents can monitor events, trigger workflows, and make decisions in real time, often without direct human intervention. That speed creates new opportunities, but it also raises the stakes. When multiple agents operate across finance, supply chain, procurement, or customer operations, they must be guided by the same understanding of business priorities.
Without a common knowledge layer connecting disparate data together, coordination between systems quickly breaks down. One system might optimize for margin, another for liquidity, and another for compliance, each working from a different slice of data.
Importantly, most enterprises already possess much of the knowledge needed to make this work, says Khan. Years of operational data, master data, workflows, and policy logic already exist across business applications — companies just need to make it accessible. Companies that deploy data fabrics gain greater trust in their data, with more than two thirds of enterprises seeing improved data accessibility, data visibility, and exerting more control over their data.
“The opportunity isn’t just inventing context from scratch, it’s activating and connecting the context across your business that already exists,” he continues, adding that a data fabric is the “architecture that ensures data semantics, business processes and policies are connected as a unified system across all the clouds.”
This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff. It was researched, designed, and written by human writers, editors, analysts, and illustrators. This includes the writing of surveys and collection of data for surveys. AI tools that may have been used were limited to secondary production processes that passed thorough human review.
Los Angeles deserves its reputation as the quintessential car city—the rhythms of its 2,200 square miles are dictated by wide boulevards and concrete arcs of freeways. But it once had a world-class rail transit system, and for the last three decades, the city has been rebuilding a network of trolleys and subways. In May, a new four-mile segment with three new subway stations will open along Wilshire Boulevard, a key east-west corridor that connects downtown LA to the Pacific Ocean. What today can be an hours-long drive through a busy, museum-packed stretch of the city will be, if all goes well, a 25-minute train ride.
The existence of subway stops in this part of town—known as Miracle Mile—is a technological triumph over geography and geology. The ground underneath it is literally a disaster waiting to happen—it’s tarry and full of methane. One of those methane deposits actually exploded in 1985, destroying a department store in the neighborhood. In response, the city pushed its new train routes to other parts of town.
These days, dirt full of flammable goo is no longer a problem. “The technology finally caught up with the concerns,” says LA Metro’s James Cohen, a longtime manager of the engineering for this stretch of subway. The key was an earth-pressure-balance tunnel-boring machine, an automated digger that is designed to chew through ground packed with explosive gas. It sends removed dirt topside via conveyor belts and slides precast concrete liner segments into the tunnel, which are joined together with gaskets to create a gas- and waterproof tube. All that let the machine dig about 50 feet every day.
Meanwhile, engineers excavated the stations from the street level down. They worked mostly on weekends, digging out a space and then decking it with concrete so that work could go on underneath while LA drivers continued to exercise their God-given right to get around by car above.
Did the project finish on time? No. Did it come in under budget? Also no; this segment alone cost nearly $4 billion. Is the city now racing to build housing and walkable areas to take full advantage of the extension? Oh, please. Yet the new stations still manage to feel, in the end, transformative—as if Los Angeles’s train has finally come in.
When people talk about “nature,” they’re generally talking about things that aren’t made by human beings. Rocks. Reefs. Red wolves. But while there is plenty of God’s creation to go around, it is hard to think of anything on Earth that human hands haven’t affected.
In the Brazilian rainforest, scientists have found microplastics in the bellies of animals ranging from red howler monkeys to manatees. In remotest Yakutia, where much of the earth remains untrodden by human feet, the carbon in the sky above melts the permafrost below. In the Arctic Ocean, artificial light from ship traffic—on the rise as the polar ice cap melts away—now disrupts the nightly journey of zooplankton to the ocean surface, one of the largest animal migrations on the planet. The remote mountain lakes of the Alps are contaminated with all kinds of synthetic chemicals. Polar bears are full of flame retardants. Cesium-137, fallout from nuclear bomb explosions, lightly rimes the entire planet.
These examples are mostly pollution—nuclear, carbon, chemical, light—but I raise them not to highlight the ways human industry and technology degrade the environment but to note how the things humans build change it. Nobody really knows what the exact effects of all that will be, but my point is that no part of the globe is free of human fingerprints. We have literally changed the world.
We’ve changed ourselves as well. Humans are especially adept at bending human nature. Everything about us is up for grabs—appearance, health, our very thoughts. Pharmaceuticals, surgeries, vaccines, and hormones give us longer lives, take away our pain, ease our anxiety and depression, make us faster, stronger, more resilient. We’re getting glimpses of technologies that will let us change who our children will become before they’re even born. Electrodes implanted in people’s brains let them control computers and translate thoughts into speech. Prosthetics and exoskeletons straight out of comic books restore and enhance physical abilities, while gene-editing technologies like CRISPR are rewriting our very DNA. And meanwhile, people have taken the sum total of all the information we have ever written down and poured it into vast calculating machines in an effort—at least by some—to build an intelligence greater than our own.
So what even is nature, or natural, in this context? Is it “environmentalist,” in the conventional sense, to try to preserve what one could argue no longer exists? Should we employ technology to try to make the world more “natural”?
Those questions led us to approach this Nature issue with humility. We try to grapple with them all the time—MIT Technology Review is, after all, a review of how people have altered and built upon nature.
And it’s a place to think about how we might repair it. Take solar geoengineering, for example—a subject we have covered with increasing frequency over the past few years. The basic idea of geoengineering is to find a technological fix for a problem technology caused: Burning petrochemicals to fuel the Industrial Revolution turned Earth’s atmosphere into a heat sink, fundamentally breaking the climate. Some geoengineers think that releasing particulate matter into the stratosphere would reflect sunlight back into space, thus reducing global temperatures. After years of theoretical discussions, some companies have begun to actively experiment with such technologies. This might seem like a great way to restore the world to a more natural state. It’s also fraught with controversy and peril. It could, for example, benefit some nations while harming others. It may give us license to continue burning fossil fuels and releasing greenhouse gases. The list goes on.
Nature isn’t easy.
In our May/June issue, we have attempted to take a hard look at nature in our unnatural world. We have stories about birds that can’t sing, wolves that aren’t wolves, and grass that isn’t grass. We look for the meaning of life under Arctic ice and within ourselves—and in the far future, on a distant world, courtesy of new fiction by the renowned author Jeff VanderMeer. I don’t know if any of that will answer the questions I’ve been asking here—but we can’t help but try. It’s in our nature.
“Pull over!” I order my brother one sunny February afternoon. Our target is in sight: a gaggle of Canada geese, pecking at grass near the dog park. As I approach, tiptoeing over their grayish-white poop, I notice that one bird wears a white cuff around its slender black neck. It’s a GPS tracker—part of a new tech-centered campaign to drive the geese out of my hometown of Foster City, California.
About 300 geese live in this sleepy Bay Area suburb, equal to nearly 1% of our human population—and some say this town isn’t big enough for the both of us. Goose poop notoriously blanketed our middle school’s lawn, and the birds have hassled residents for generations. My own grandmother remembers when geese took over her garage for five whole minutes before waddling out. She says, “I wanted to kill them, but I thought I’d get in trouble.”
Indeed, that idea doesn’t fly here. City officials backed out of a previous plan to kill 100 geese following uproar from local environmentalists. Still, the poop creates a public health hazard; the birds need to go.
So the city paid nearly $400,000—roughly $1,300 per goose—to Wildlife Innovations, a company that resolves conflicts between humans and wildlife, to haze the geese with gadgets. The company’s approach is “basically, making the geese less comfortable,” Dan Biteman, head of the goose management plan and senior wildlife biologist at Wildlife Innovations, tells me.
The need for such conflict resolution is on the rise as land development collides with changes in animal behavior. Though overpopulation of Canada geese is a national nuisance in the US, such tensions also surface with other species in this country and elsewhere, including grizzlies on the Montana prairies, coyotes on San Francisco streets, and savanna elephants in Tanzania parks.
So the people whose job it is to deal with recalcitrant critters are bringing on the gadgets.
Back in Foster City, I spot a black camera mounted to a tree trunk at Gull Park by the lagoon. They’re in seven parks around town, programmed to snap photos every 15 minutes and transmit them back to Wildlife Innovations HQ. If they detect geese, a biologist immediately drives over to disperse the birds. One team member uses devices like lasers or drones; another brings along a goose-hating border collie named Rocky.
As a special measure, staff deploy the “Goosinator,” a small, remote-controlled neon-orange pontoon boat with a fearsome dog-like mouth painted on its bow, meant to evoke geese’s fear of coyotes and bright colors. It comes with attachable wheels and can zoom around on land or water to chase birds away. Biteman tells me the company is thinking about mounting speakers on trees and flying drones that will screech the calls of goose predators like red-tailed hawks or golden eagles.
The company received federal permits required by the Migratory Bird Treaty Act to stick GPS trackers on 10 geese, too. This way, staff can surveil the geese and research their behavior and movements.
At local goose hangouts, signs that look like “Wanted” posters alert the public to the new plan. As I watch some culprits graze (and defecate) on a church lawn, I think to myself: Enjoy it while it lasts.
Annika Hom is an award-winning independent journalist. She’s written for National Geographic, Wired, and more.
If you thought K-pop was weird, virtual idols—humans who perform as anime-style digital characters via motion capture—will blow your mind. My favorite is a girl group called Isegye Idol, created by Woowakgood, a Korean VTuber (a streamer who likewise performs as a digital persona). Isegye Idol’s six members are anonymous, which seems to let them deploy a rare breed of honesty and humor. They play games (League of Legends, Go, Minecraft), chitchat, and perform kitschy music that’s somewhere between anime soundtrack and video-game score. It’s very DIY—and very intimate. And the group’s wild popularity speaks to the mood of Gen Z South Koreans, famously lonely and culturally adrift—struggling to find work, giving up on dating, trying to find friendships online. Isegye Idol shows what a magical online universe people can build when reality stops working for them.
Pavel Talankin didn’t have the easiest life as a schoolteacher in the copper-smelting town of Karabash, Russia; UNESCO once called it the most toxic place on Earth. But video he shot, partially in secret, makes it clear he loved it—the smokestacks, the cold, the ice mustache he’d get walking around outside, and, most of all, his bright-eyed students. That makes it all the more painful when a distant, grinding war and state propaganda change the town. An antiwar progressive with a democracy flag in his classroom, Talankin had to deal with a new patriotic curriculum, mandatory parades, visits from mercenaries—and the loss of the creative space he’d built with his students. Talankin’s footage tells his story in this Oscar-winning documentary from director David Borenstein, and what struck me most is how strange it is being an adult around kids. We shape them in profound ways we might not even recognize.
I am the kind of person who will pay $150 to watch a comedian in a smelly theater in San Francisco that charges $20 for a can of water—because I am crazy enough to hope that standup will not die. In February, I saw the British comedian James Acaster perform live … and it was a mediocre show. But Repertoire, his 2018 miniseries on Netflix, is gold. Shot shortly after Acaster went through a breakup, the four-part show features him portraying, among other characters, a cop who goes undercover as a standup comedian, forgets who he is, and gets divorced. And then things get weird. “What if every relationship you’ve ever been in,” Acaster asks, “is somebody slowly figuring out they didn’t like you as much as they hoped they would?” If the best comedy comes from paying attention to the hellhole that you’re in, I wish Acaster many more pitfalls.
Fluorescent probes have reshaped how biologists study living systems, making it possible to watch viruses invade cells, follow the cell’s internal waste‑disposal machinery, and track the signaling events that fuel tumor growth. Yet even with decades of innovation, a fundamental limitation has persisted: most fluorescent nanobody probes glow whether or not they are bound to their targets. That constant background haze can blur the very molecular details researchers are trying to resolve.
A new imaging platform developed by scientists at Albert Einstein College of Medicine and the Salk Institute for Biological Studies aims to eliminate that problem entirely. The technology, described in Nature Methods in a paper titled “Synthetic multicolor antigen-stabilizable nanobody platform for intersectional labelling and functional imaging,” uses engineered fluorescent nanobodies that become brightly fluorescent only when they bind their intended protein targets. These “on‑demand” probes, known as VIS‑Fbs (visible-spectrum target-stabilizable fluorescent nanobodies), illuminate proteins inside living cells and animals with far greater clarity than conventional tools.
“The key advantage of our approach is that the signal appears only where the target protein is present,” said Vladislav Verkhusha, PhD, co‑corresponding author and professor of genetics at Einstein. “That eliminates the background glow that has long limited the precision of intracellular imaging.” His collaborator, Axel Nimmerjahn, PhD, professor and the Françoise Gilot‑Salk Chair at Salk, added, “This work establishes a versatile platform for imaging proteins with high specificity and minimal background. It opens new opportunities to study how molecular and cellular processes unfold in real time across diverse biological systems.”
Nanobodies have become increasingly valuable for live‑cell imaging because they can be engineered to bind specific proteins with high affinity. But their ongoing fluorescence has remained a stubborn obstacle. The VIS‑Fb design solves this by making the probes unstable when unbound; they rapidly degrade unless they encounter their target. Binding stabilizes the nanobody and triggers bright fluorescence, reducing background noise by as much as 100‑fold. The team also created VIS‑Fbs that span nearly the entire visible spectrum, from blue to far red, enabling simultaneous tracking of multiple proteins or cellular processes within the same cell.
The researchers developed a modular engineering platform, instead of a single probe, capable of generating VIS‑Fbs for a wide range of targets and experimental needs. They integrated more than 20 fluorescent proteins and biosensors into multiple nanobody scaffolds, creating a flexible system that supports multicolor imaging, light‑switchable variants for precise temporal control, and functional readouts of ions and metabolites. This allows the probes not only to show where proteins are but also to show what those proteins are doing in real time. According to first author Natalia Barykina, PhD, “The VIS‑Fb approach allows us to identify and track specific cell populations in living organisms based on the proteins they express, rather than just their location.”
In mice, VIS‑Fbs allowed for high‑contrast imaging of neuronal and astrocyte activity during behavior. In zebrafish embryos, the probes captured rapid developmental changes and responses to drugs that modulate signaling pathways. “Our results show that this imaging platform offers a much clearer and more precise view of how proteins behave inside living systems,” Verkhusha said. “It opens the door to studying complex biological processes, such as cell signaling, development, and disease progression, in new ways.”
The post Antigen‑Stabilized Nanobody Probes Enable On‑Demand, Multicolor Protein Imaging appeared first on GEN – Genetic Engineering and Biotechnology News.
In the aftermath of the successful Artemis II mission, NASA is moving forward with the next steps of its plans to establish a base on the moon. According to NASA Administrator Jared Isaacman, crews will be operating at the lunar base within the next decade with an even more ambitious long-term goal: Mars.
Human health in the space environment will be an important factor in these efforts. Among the concerns NASA should consider is the potential impacts of immunology and infectious disease.
Vani Hari has 2.3 million followers on Instagram, and about as many ideas for healthy food swaps. An entrepreneur and influential food activist in the Make America Healthy Again movement, Hari gives regular shout-outs to substitutes for snacks that contain corn syrup, seed oils, and other ingredients on health-conscious Americans’ blacklist.
For Valentine’s Day, YumEarth choco yums instead of artificially dyed M&Ms. (“Let me say these treats are BETTER, but they are still candy,” Hari writes.) For Super Bowl parties, Jackson’s avocado oil potato chips rather than Lay’s. Looking for a less processed alternative to Chick-fil-A’s frosted lemonade? Why not make your own with lemon-flavored protein powder from Hari’s own brand, Truvani. At least one attempt at a healthy food swap struck out with Hari: PepsiCo’s recently debuted dye-free line of Cheetos and Doritos. “This is dumb,” she wrote on Instagram. “Creating a whole NEW product, instead of FIXING their old product.”
Though the vast majority — 84% — of Americans said eating healthfully was at least moderately important to them in a recent Deloitte survey, most admit their own habits fall short of their aspirations. The $156 billion packaged snack industry has spotted a business opportunity in catering to people seeking a more enlightened way of noshing.