Science News
24 articles in science
Women, science and the price of integrity
From the shadow of the Acropolis to the forefront of nuclear materials research, Professor Konstantina Lambrinou reflects on ambition, injustice The post Women, science and the price of integrity appeared first on The European Magazine.
The year of the ‘hectocorn’: the $100bn tech companies that could float in 2026
OpenAI, Anthropic, SpaceX and Stripe are rumoured to be among ten of the biggest companies considering IPOs You’ve probably heard of “unicorns” – technology startups valued at more than $1bn – but 2026 is shaping up to be the year of the “ hectocorn ”, with several US and European companies potentially floating on stock markets at valuations over $100bn (£75bn). OpenAI, Anthropic, SpaceX and Stripe are among the big names said to be considering an initial public offering (IPO) this year. Continue reading...
Smart Door Lock Market Set To Reach USD 14.90 Billion By 2033, Driven By Smart Home Adoption And Rising Security Demand Research By SNS Insider
(MENAFN - GlobeNewsWire - Nasdaq) The smart door lock market is expanding as consumers adopt connected home security solutions, with the U.S. segment growing from USD 0.96 billion in 2025E to USD ...
The Oceans Just Keep Getting Hotter
For the eighth year in a row, the world’s oceans absorbed a record-breaking amount of heat in 2025. It was equivalent to the energy it would take to boil 2 billion Olympic swimming pools.
Trump Wants Venezuela’s Oil. Getting It Might Not Be So Simple
The administration has made it clear that Nicolás Maduro's capture was tied to Venezuela’s vast oil reserves. Much less certain is how US companies will actually access them—or if they even want to.
'Intelition' changes everything: AI is no longer a tool you invoke
AI is evolving faster than our vocabulary for describing it. We may need a few new words. We have “cognition” for how a single mind thinks, but we don't have a word for what happens when human and machine intelligence work together to perceive, decide, create and act. Let’s call that process intelition. Intelition isn’t a feature; it’s the organizing principle for the next wave of software where humans and AI operate inside the same shared model of the enterprise. Today’s systems treat AI models as things you invoke from the outside. You act as a “user,” prompting for responses or wiring a “human in the loop” step into agentic workflows. But that's evolving into continuous co-production: People and agents are shaping decisions, logic and actions together, in real time. Read on for a breakdown of the three forces driving this new paradigm. A unified ontology is just the beginningIn a recent shareholder letter, Palantir CEO Alex Karp wrote that “all the value in the market is going to go to chips and what we call ontology,” and argued that this shift is “only the beginning of something much larger and more significant.” By ontology, Karp means a shared model of objects (customers, policies, assets, events) and their relationships. This also includes what Palantir calls an ontology’s “kinetic layer” that defines the actions and security permissions connecting objects.In the SaaS era, every enterprise application creates its own object and process models. Combined with a host of legacy systems and often chaotic models, enterprises face the challenge of stitching all this together. It’s a big and difficult job, with redundancies, incomplete structures and missing data. The reality: No matter how many data warehouse or data lake projects commissioned, few enterprises come close to creating a consolidated enterprise ontology. A unified ontology is essential for today’s agentic AI tools. As organizations link and federate ontologies, a new software paradigm emerges: Agentic AI can reason and act across suppliers, regulators, customers and operations, not just within a single app. As Karp describes it, the aim is “to tether the power of artificial intelligence to objects and relationships in the real world.” World models and continuous learningToday’s models can hold extensive context, but holding information isn’t the same as learning from it. Continual learning requires the accumulation of understanding, rather than resets with each retraining. To his aim, Google recently announced “Nested Learning” as a potential solution, grounded direclty into existing LLM architecture and training data. The authors don’t claim to have solved the challenges of building world models. But, Nested Learning could supply the raw ingredients for them: Durable memory with continual learning layered into the system. The endpoint would make retraining obsolete. In June 2022, Meta's chief AI scientist Yann LeCun created a blueprint for “autonomous machine intelligence” that featured a hierarchical approach to using joint embeddings to make predictions using world models. He called the technique H-JEPA, and later put bluntly: “LLMs are good at manipulating language, but not at thinking.”Over the past three years, LeCun and his colleagues at Meta have moved H-JEPA theory into practice with open source models V-JEPA and I-JEPA, which learn image and video representations of the world. The personal intelition interface The third force in this agentic, ontology-driven world is the personal interface. This puts people at the center rather than as “users” on the periphery. This is not another app; it is the primary way a person participates in the next era of work and life. Rather than treating AI as something we visit through a chat window or API cal, the personal intelition interface will be always-on, aware of our context, preferences and goals and capable of acting on our behalf across the entire federated economy. Let’s analyze how this is already coming together.In May, Jony Ive sold his AI device company io to OpenAI to accelerate a new AI device category. He noted at the time: “If you make something new, if you innovate, there will be consequences unforeseen, and some will be wonderful, and some will be harmful. While some of the less positive consequences were unintentional, I still feel responsibility. And the manifestation of that is a determination to try and be useful.” That is, getting the personal intelligence device right means more than an attractive venture opportunity. Apple is looking beyond LLMs for on-device solutions that require less processing power and result in less latency when creating AI apps to understand “user intent.” Last year, they created UI-JEPA, an innovation that moves to “on-device analysis” of what the user wants. This strikes directly at the business model of today’s digital economy, where centralized profiling of “users” transforms intent and behavior data into vast revenue streams.Tim Berners-Lee, the inventor of the World Wide Web, recently noted: “The user has been reduced to a consumable product for the advertiser ... there's still time to build machines that work for humans, and not the other way around." Moving user intent to the device will drive interest in a secure personal data management standard, Solid, that Berners-Lee and his colleagues have been developing since 2022. The standard is ideally suited to pair with new personal AI devices. For instance, Inrupt, Inc., a company founded by Berners-Lee, recently combined Solid with Anthropic’s MCP standard for Agentic Wallets. Personal control is more than a feature of this paradigm; it is the architectural safeguard as systems gain the ability to learn and act continuously.Ultimately, these three forces are moving and converging faster than most realize. Enterprise ontologies provide the nouns and verbs, world-model research supplies durable memory and learning and the personal interface becomes the permissioned point of control. The next software era isn't coming. It's already here.Brian Mulconrey is SVP at Sureify Labs.
Best 5 Wind Turbine Inspection Software Platforms
Wind energy is one of the fastest-growing sources of renewable power, but as wind farms expand in size and complexity, maintaining turbine integrity becomes increasingly challenging. Turbines operate in extreme environments, exposed to constant mechanical stress, weather erosion, salt corrosion (offshore), and lightning strikes. Each of these factors can accelerate structural wear and reduce performance [...]
Data Holds the Key in Slowing Age-Related Illnesses
More accurate and individualized health predictions will allow for preventative factors to be implemented well in advance.
Data centers could soon be orbiting in space
The AI revolution is going cosmic
FDA Approves Pill Version of Wegovy
Novo Nordisk’s semaglutide will soon be available in a daily pill Americans can take for weight loss.
The Doomsday Glacier Is Getting Closer and Closer to Irreversible Collapse
An analysis of the expansion of cracks in the Thwaites Glacier over the past 20 years suggests that a total collapse could be only a matter of time.
Even Google and Replit struggle to deploy AI agents reliably — here's why
2025 was supposed to be the year of the AI agent, right? Not quite, acknowledge Google Cloud and Replit — two big players in the AI agent space and partners in the "vibe coding" movement — at a recent VB Impact Series event.Even as they build out agentic tools themselves, leaders from the two companies say the capabilities aren’t quite there yet. This constrained reality comes down to struggles with legacy workflows, fragmented data, and immature governance models. Also, enterprises fundamentally misunderstand that agents aren’t like other technologies: They require a fundamental rethink and reworking of workflows and processes. When enterprises are building agents to automate work, “most of them are toy examples,” Amjad Masad, CEO and founder of Replit, said during the event. “They get excited, but when they start rolling it out, it's not really working very well.”Building agents based on Replit’s own mistakesReliability and integration, rather than intelligence itself, are two primary barriers to AI agent success, Masad noted. Agents frequently fail when run for extended periods, accumulate errors, or lack access to clean, well-structured data. The problem with enterprise data is it’s messy — it’s structured, unstructured, and stored all over the place — and crawling it is a challenge. Added to that, there are many unwritten things that people do that are difficult to encode in agents, Masad said. “The idea that companies are just going to turn on agents and agents will replace workers or do workflow automations automatically, it's just not the case today,” he said. “The tooling is not there.” Going beyond agents are computer use tools, which can take over a user’s workspace for basic tasks like web browsing. But these are still in their infancy and can be buggy, unreliable, and even dangerous, despite the accelerated hype. “The problem is computer use models are really bad right now,” Masad said. “They're expensive, they're slow, they're making progress, but they're only about a year old.” Replit is learning from its own blunder earlier this year, when its AI coder wiped a company's entire code base in a test run. Masad conceded: “The tools were not mature enough,” noting that the company has since isolated development from production. Techniques such as testing-in-the-loop, verifiable execution, and development isolation are essential, he noted, even as they can be highly resource-intensive. Replit incorporated in-the-loop capabilities into version 3 of its agent, and Masad said that its next-gen agent can work autonomously for 200 minutes; some have run it for 20 hours. Still, he acknowledged that users have expressed frustration around lag times. When they put in a “hefty prompt,” they may have to wait 20 minutes or longer. Ideally, they’ve expressed that they want to be involved in more of a creative loop where they can enter numerous prompts, work on multiple tasks at once, and adjust the design as the agent is working. “The way to solve that is parallelism, to create multiple agent loops and have them work on these independent features while allowing you to do the creative work at the same time,” he said. Agents require a cultural shiftBeyond the technical perspective, there’s a cultural hurdle: Agents operate probabilistically, but traditional enterprises are structured around deterministic processes, noted Mike Clark, director of product development at Google Cloud. This creates a cultural and operational mismatch as LLMs steam in with all-new tools, orchestration frameworks and processes. “We don't know how to think about agents,” Clark said. “We don't know how to solve for what agents can do.”The companies doing it right are being driven by bottoms-up processes, he noted: no-code and low-code software and tool creation in the trenches funneling up to larger agents. As of yet, the deployments that are successful are narrow, carefully scoped and heavily supervised. “If I look at 2025 and this promise of it being the year of agents, it was the year a lot of folks spent building prototypes,” Clark said. “Now we’re in the middle of this huge scale phase.”How do you secure a pasture-less world?Another struggle is AI agent security, which also requires a rethink of traditional processes, Clark noted. Security perimeters have been drawn around everything — but that doesn’t work when agents need to be able to access many different resources to make the best decisions, said Clark. “It's really changing our security models, changing our base level,” he said. “What does least privilege mean in a pasture-less defenseless world?”Ultimately, there must be a governance rethink on the part of the whole industry, and enterprises must align on a threat model around agents. Clark pointed out the disparity: “If you look at some of your governance processes, you'll be very surprised that the origin of those processes was somebody on an IBM electric typewriter typing in triplicate and handing that to three people. That is not the world we live in today.”
Americans Are Increasingly Convinced That Aliens Have Visited Earth
Polling shows that nearly half of Americans now believe aliens have visited this planet—and that the number who aren't sure has dropped by two-thirds. The reasons why, experts say, are complicated.
El Paso Students Showcase STEM Prowess at VEX V5 Robotics Tournament
El Paso high school students participated in the VEX V5 Robotics Tournament, showcasing STEM skills and robotic designs.
Pumped Hydro Energy Storage Is Having a Renaissance
As the world looks to incorporate more renewables into energy grids, centuries-old systems that can balance supply and demand are being reappraised and innovated upon.
JP Morgan’s AI adoption hit 50% of employees. The secret? A connectivity-first architecture
When Derek Waldron and his technical team at JPMorgan Chase first launched an LLM suite with personal assistants two-and-a-half years ago, they weren’t sure what to expect. That wasn’t long after the game-changing emergence of ChatGPT, but in enterprise, skepticism was still high. Surprisingly, employees opted into the internal platform organically — and quickly. Within months, usage jumped from zero to 250,000 employees. Now, more than 60% of employees across sales, finance, technology, operations, and other departments use the continually evolving, continually connected suite.“We were surprised by just how viral it was,” Waldron, JPMorgan’s chief analytics officer, explains in a new VB Beyond the Pilot podcast. Employees weren’t just designing prompts, they were building and customizing assistants with specific personas, instructions, and roles and were sharing their learnings on internal platforms. The financial giant has pulled off what most enterprises still struggle to achieve: large-scale, voluntary employee adoption of AI. It wasn’t the result of mandates; rather, early adopters shared tangible use cases, and workers began feeding off each other’s enthusiasm. This bottom-up usage has ultimately resulted in an innovation flywheel. “It’s this deep rooted innovative population,” Waldron says. “If we can continue to equip them with really easy to use, powerful capabilities, they can turbocharge the next evolution of this journey.” Ubiquitous connectivity plugged into highly sophisticated systems of recordJPMorgan has taken a rare, forward-looking approach to its technical architecture. The company treats AI as a core infrastructure rather than a novelty, operating from the early contrarian stance that the models themselves would become a commodity. Instead, they identified the connectivity around the system as the real challenge and defensible moat.The financial giant invested early in multimodal retrieval-augmented generation (RAG), now in its fourth generation and incorporating multi-modality. Its AI suite is hosted at the center of an enterprise-wide platform equipped with connectors and tools that support analysis and preparation. Employees can plug into an expanding ecosystem of critical business data and interact with “very sophisticated” documents, knowledge and structured data stores, as well as CRM, HR, trading, finance and risk systems. Waldron says his team continues to add more connections by the month. “We built the platform around this type of ubiquitous connectivity,” he explains. Ultimately, AI is a great general-purpose technology that will only grow more powerful, but if people don’t have meaningful access and critical use cases, “you're squandering the opportunity.” As Waldron puts it, AI’s capabilities continue to grow impressively — but they simply remain shiny objects for show if they can’t prove real-world use. “Even if super intelligence were to show up tomorrow, there's no value that can be optimally extracted if that superintelligence can't connect into the systems, the data, the tools, the knowledge, the processes that exist within the enterprise,” he contends. Listen to the full episode to hear about: Waldron’s personal strategy of pausing before asking a human colleague and instead assessing how his AI assistant could answer that question and solve the problem. A "one platform, many jobs" approach: No two roles are the same way, so strategy should center on reusable building blocks (RAG, document intelligence, structured data querying) that employees can assemble into role-specific tools.Why RAG maturity matters: JPMorgan evolved through multiple generations of retrieval — from basic vector search to hierarchical, authoritative, multimodal knowledge pipelines.Subscribe to Beyond the Pilot on Apple Podcasts and Spotify.
Test Article on AI: Revolutionizing Romania's Economy and Society
Test Article on AI explores how artificial intelligence is transforming industries worldwide, with profound implications for Romania's citizens and economy. As Romania invests heavily in digital innovation, AI advancements promise to boost productivity in Bucharest's tech hubs and rural areas alike, creating jobs for Romanian workers while addressing challenges like labor shortages in manufacturing and agriculture. This matters deeply to Romanians, enhancing competitiveness in the European Union and improving daily life through smarter public services and healthcare.
The Best Meteor Shower of the Year Is Coming—Here’s How to Watch
The highlight of the year, the Geminids are the most active and colorful meteor shower, offering the chance to see hundreds of shooting stars every hour when they peak in mid-December.
Alumni Profile: Kejun Ying, S.M. '24, Ph.D. '25
Computing new enzymes to fight neurodegenerative disease
How the Next Big Thing in Carbon Removal Sunk Without a Trace
With support from Microsoft, Stripe, and Shopify, Running Tide billed itself as on the cutting edge of carbon removal. In the end, it resorted to dumping thousands of tons of wood chips in the sea.
Doctor's Note: Advancements in surgical technology and technique benefit patients
While robotic technology has been in operating rooms for a decade, continued development, and advancement in techniques are improving outcomes for patients across Montana.
How to Measure the Earth’s Radius With Legos
With just a friend, a phone, and a few Lego bricks, you can accurately measure the size of our planet.
Flying with whales: Drones are remaking marine mammal research
Aerial drones are giving scientists a new view of life at sea.
Curium’s expansion into transformative therapy offers fresh hope against cancer
Curium’s transformative radioligand therapy targets cancer cells directly, reducing side effects and offering new hope for patients worldwide. The post Curium’s expansion into transformative therapy offers fresh hope against cancer appeared first on The European Magazine.