Ali Niknam has built Dutch fintech Bunq into one of Europe’s biggest neobanks. But he fears the Netherlands is now driving entrepreneurs away. The Bunq founder and CEO is alarmed by the country’s business mindset. He believes risk-aversion, growing insularity, and hostility to ambition are pushing talent overseas. “Many of the best entrepreneurs I know have either left or are considering leaving,” Niknam tells TNW. Surveys back him up. A poll last year found that almost one in five Dutch entrepreneurs were considering relocating — up from nearly one in eight in 2023. The 💜 of EU techThe latest rumblings from the EU tech scene, a story from our wise ol' founder Boris, and some questionable AI art. It's free, every week, in your inbox. Sign up now!Another study found that 24% of large companies were contemplating moves abroad — nearly double the share from the year before.  Tech scaleups are also mulling exits. One of the country’s biggest — software unicorn Bird — recently announced plans to shift operations out of the country. The company’s CEO blamed “over-regulation” and a bad climate for tech businesses. Niknam — who’s set to speak at TNW Conference on June 20 in Amsterdam — has his own critiques of the Dutch business landscape. He calls its support for entrepreneurship “among the worst” he’s seen. Yet he still has deep faith in the country’s talent pool.  “There are very few countries I know that have such amazing, creative, smart people as the Dutch,” he says.  Those people have been integral to Bunq’s rapid growth. Building bridges at Bunq Niknam’s idea for Bunq emerged in the wake of the 2008 financial crisis. One of the causes, he believes, was groupthink at incumbent banks. He founded Bunq in 2012 to create an alternative.  To create a new approach to banking, Niknam sought to embrace diverse ideas. He points to the company’s approach to proposals, which can be pitched anonymously — even to Niknam himself. “On the one hand, that’s better for the company — the best ideas win. And on the other hand, it makes it more fair, because all that counts is the quality of your idea, not who you know, where you’re brought up, or what school you attended.” The strategy delivered rapid results. In 2015, Bunq became the first Dutch company in 35 years to obtain a greenfield banking license. It then grew into Europe’s second-largest neobank after Revolut — and one of the few to achieve profitability. The company now boasts over 17 million users with more than €8bn in deposits. Outside Bunq, however, Niknam sees a country that’s becoming more closed. He believes the Netherlands is abandoning its internationalist roots, which is damaging its tech ecosystem and chasing talent away.  “Historically, the Netherlands has been very entrepreneurial, very international… when this country retreats and closes the doors is when things start to get worse.” Even the country’s vast pension funds, he notes, avoid backing Dutch startups. “They know the returns are going to be less,” he says. “Why are the returns less? Because it’s a small country, and it is retreating and starting to focus within its own borders.” He contrasts the mood with developments in the Baltics. The region’s tech ecosystem has attracted admiring glances for its optimism, openness, and rapid growth. Niknam feels that many people in the Netherlands take their rights for granted. “It’s maybe a little bit of an entitlement disease — that we have forgotten that all these wonderful things that we enjoy today, somebody worked for them really, really hard,” he says. Born in Canada to Iranian parents and with homes in the Netherlands and the US, Niknam has diverse cultural experiences. Image: OLSjopera Niknam feels the Netherlands has become too risk-averse and inward-looking. Despite the liberal stereotype, Dutch society can be surprisingly conservative.  That caution, Niknam says, is embedded in the culture — even in local proverbs. One goes: “Steek je kop niet boven het maaiveld uit.” Loosely translated: “Don’t stick your head above the mowing line.” If you do, it might get chopped off. In Niknam’s eyes, that mentality thwarts ambitious entrepreneurs. “Success is not only not celebrated, but you’re almost faulted for being successful,” he says.  The international return The Netherlands is also losing its appeal to international talent. Over nine in ten expats and migrant workers no longer even consider coming to work in the country, according to research from last year. Tech firms have raised major concerns over losing access to global talent. The chip equipment maker ASML — the largest company in the Netherlands — has threatened to move abroad because of the country’s hardening stance on migrants. Peter Wennink, ASML’s former CEO — who will also speak at TNW Conference — recently warned against losing access to skilled workers. “If we cannot get those people here, we will get those people in Eastern Europe or in Asia or in the United States,” he said. Still, Niknam believes the tide can turn. For change to come, he believes the “silent majority” — those who value openness and diversity — must speak up.  Despite its problems, Niknam remains upbeat about the future for tech businesses in the Netherlands. “The people are great. The schooling is great. The infrastructure is great,” he says. “It is simply changing the attitude and mindset — which can happen in a relatively short amount of time — that will make all the difference.” If you want to catch the talks by Niknam and Wennink — or anything else on the agenda for TNW Conference — we have a special offer for you. Use the code TNWXMEDIA2025 at the checkout to get 30% off your ticket. Story by Thomas Macaulay Managing editor Thomas is the managing editor of TNW. He leads our coverage of European tech and oversees our talented team of writers. Away from work, he e (show all) Thomas is the managing editor of TNW. He leads our coverage of European tech and oversees our talented team of writers. Away from work, he enjoys playing chess (badly) and the guitar (even worse). Get the TNW newsletter Get the most important tech news in your inbox each week. Also tagged with

Author(s): Adam BEN KHALIFA Originally published on Towards AI. Why are agentic workflows essential for achieving AGI Let me ask you this, what if the path to truly smart and effective AI , the kind we call AGI, isn’t just about building one colossal, all-knowing brain? What if the real breakthrough lies not in making our models only smarter, but in making them also capable of acting, adapting, and evolving? Well, LLMs continue to amaze us day after day, but the road to AGI demands more than raw intellect. It requires agency. Getting Our Terms Straight: AGI, Agency, and Agentic Workflows Before we dive in, let’s define the main concepts here: AGI — Artificial General Intelligence: You can see it as an AI model that can perform any intellectual task a human can. This means not just understanding language or generating images, but adapting, learning, reasoning, and acting across entirely new domains. Agency: The capacity of an entity to act purposefully in its environment to achieve goals. A rock has no agency; a human planning their day has plenty. For an AI, agency means it’s not just passively responding to prompts but actively pursuing objectives. Simply put, it’s the capacity to pursue goals autonomously through planning, acting, and adapting. Agentic Workflows: If agency is the “what”, agentic workflows are the “how”. These are the dynamic processes and systems an AI uses to exercise its agency. Think beyond a simple input-output model. Agentic workflows involve: Autonomous Goal-Setting & Planning: the AI doesn’t just execute a pre-defined plan, it can formulate goals and strategize how to achieve them. Tool Use & Orchestration: like a skilled craftsperson, it can select, combine, and utilize various “tools” (other AI models, databases, APIs, code execution environments) to get the job done. Memory & Learning: it remembers past actions, learns from successes and failures, and adapts its strategies over time. Adaptation in Dynamic Environments: the real world is messy, an agentic AI can adjust its plan when encountering unexpected obstacles or new information. It’s vital to understand the difference here: An LLM calling a weather API is just tool use. An agentic workflow is when an LLM, tasked with “analyzing market trends for a new product,” autonomously decides to:1) search recent financial news, 2) query a sales database, 3) use a data analysis tool to spot correlations, 4) ask a specialized forecasting model for projections, and then 5) compile a summary report, re-evaluating its approach at each step.It’s like the difference between a single musician playing one note, and a conductor leading an entire orchestra. The Limitation of Isolated Intelligence Let’s consider a human analogy. Imagine a brilliant engineer, a genius in their field. Now, strip away their tools: no computer, no internet for research, no pen and paper for sketching ideas or taking notes, no lab for prototyping, no colleagues to bounce ideas off. Confine them to only their thoughts. How much could they truly achieve? Their raw intellect, however vast, becomes severely handicapped when uncoupled from the ability to interact, experiment, and leverage external resources. This “intelligence in isolation” scenario illustrates a fundamental truth: intelligence doesn’t operate in a vacuum. It thrives on interaction, tool use, and the ability to execute plans in the world. If we want AGI, we can’t just build a disembodied digital brain, we need to build something that can act. Agentic Workflows: AI can act like us, and perhaps even better Humans are masters of adapting their “workflows.” A painter uses different tools and processes than an engineer, who uses different methods than a chef. We intuitively understand context, choose the right approach, and even invent new methods when old ones fail. Agentic workflows aim to achieve similar capabilities: Contextual Flexibility: An Agentic AI could switch between “investigative journalist mode” (querying databases, cross-referencing sources, interviewing) and “creative writer mode” (generating narratives, exploring styles) as needed for a complex task. Learning by Doing (and Re-doing): Human learning is an iterative workflow: observe, hypothesize, experiment, analyze, conclude, refine. Agentic systems can embody this, trying approaches, evaluating outcomes, and improving their strategies. Beyond Monolithic Thought: We don’t store everything in our heads. We use notes, computers, books, and critically, we delegate tasks to others. Agentic AI can similarly leverage external knowledge bases, specialized sub-agents, and computational tools, creating a distributed, more powerful form of intelligence. Thinking About Thinking: Humans possess meta-cognition — the ability to reflect on our own thought processes and adjust them. Agentic workflows, with their capacity for self-monitoring and re-planning, are a foundational step towards AI developing its own form of meta-cognition. Inventing New Ways: Perhaps soon enough, an advanced agentic AI won’t just use existing tools and workflows, but identify the need for entirely new ones and even contribute to their creation. A hallmark of true general intelligence. Not Just Helpful, But Mandatory: Why AGI Needs Agentic Workflows These capabilities aren’t just fancy add-ons. They are arguably essential for anything we’d recognize as AGI: Tackling Complexity: Real-world problems are messy, multifaceted, and rarely solved by a single, linear process. Agentic workflows will allow AI to break down these complex challenges into manageable sub-tasks, orchestrating diverse capabilities. Achieving Scale: Imagine trying to manage global logistics, conduct large-scale scientific research, or personalize education for millions with a single, rigid program. Agentic systems offer the modularity and dynamic coordination needed for such scale. Adaptability and Robustness: What happens when the data changes, a tool fails, or an assumption proves wrong? A static AI might grind to a halt. An agentic AI can adapt, re-plan, find alternative solutions, and continue pursuing its goal. It can handle the unexpected. Resourcefulness: Like our engineer, an AGI needs to be able to identify and use the right “tool” (be it a specific algorithm, dataset, or external service) for the job at hand, rather than trying to be a jack-of-all-trades with a single block massive model. Surpassing Human Adaptability The first step is for AI to achieve a human-like ability to set goals, plan, use tools, and adapt through agentic workflows. But the true promise of AGI lies in surpassing these capabilities: Speed: Learn and adapt at speeds incomprehensible to us, iterating through problem-solving cycles in milliseconds. Scale: Manage and orchestrate operations of immense complexity, juggling thousands of variables and “tools” simultaneously. Novelty: Devise entirely new, perhaps counter-intuitive, workflows and solutions to problems that humans haven’t even conceived of. Self-Improvement of Workflows: An AGI that doesn’t just use workflows but actively refines, optimizes, and even discovers fundamentally new and more efficient ways to achieve its goals. Deeper Meta-Learning: Learning how to learn, plan, and strategize more effectively over time, becoming increasingly more intelligent and capable. Long-Horizon Reasoning: Successfully breaking down and navigating extremely complex, multi-stage goals that unfold over extended periods, adapting robustly along the way. Obviously, this is easier said than done. Building true AGI presents formidable challenges: How do we design systems that can reliably plan in open-ended environments? How can they discover and integrate new tools seamlessly? How does the system learn which part of a long, complex workflow was responsible for success or failure? These are active areas of research, pushing the boundaries of what AI can do. Thankfully we are witnessing more and more breakthroughs everyday, and RL — Reinforcement Learning based approaches are showing great promise (which make sense actually, but that’s for another article). Conclusion: Agency as the Cornerstone of AGI The quest for AGI is more than a race for larger models or faster processing. It’s a quest for intelligence that is versatile, adaptive, and purposeful. Agentic workflows provide the framework for such intelligence, enabling AI to move beyond mere pattern recognition to become an active participant in the problem-solving process. Just as human collective general intelligence emerged not merely from neurons, but from networks of thought, culture, and action — we must build AGI not as a single-block model, but as an AI capable of learning, adapting, and acting. Agency, in this light, isn’t just a feature; it’s the fundamental engine that will drive us towards true Artificial General Intelligence. If you liked this article, make sure to follow for more.And you can find me on: Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor. Published via Towards AI

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Unpatched systems are a ticking time bomb. Fifty-seven percent of cyberattack victims acknowledge that available patches would have prevented breaches, yet nearly one-third admit failing to act, compounding the risk. Ponemon research shows organizations now take an alarming average of 43 days to detect cyberattacks, even after a patch is released, up from 36 days the previous year. According to the Verizon 2024 Data Breach Investigations Report, attackers’ ability to exploit vulnerabilities surged by 180% from 2023 to 2024. Chronic firefighting makes manual or partially automated patching overly burdensome, further pushing patching down teams’ priority lists. Relying on manual or partially automated patching systems is considered too time-consuming, further reducing patching to the bottom of a team’s action item list. This is consistent with an Ivanti study that found that the majority (71%) of IT and security professionals think patching is overly complex, cumbersome and time-consuming. When it comes to patching, complacency kills Attackers aggressively exploit legacy Common Vulnerabilities and Exposures (CVEs), often ten or more years old. A sure sign of how effective attackers’ tradecraft is becoming at targeting legacy CVEs is their success with vulnerabilities in some cases, 10-plus years old. A sure sign that attackers are finding new ways to weaponize old vulnerabilities is reflected in the startling stat that 76% of vulnerabilities leveraged by ransomware were reported between 2010 and 2019. The misalignment between IT and security teams compounds delays, with 27% lacking cohesive patch strategies and nearly a quarter disagreeing on patch schedules. One of the unexpected benefits of automating patch management is breaking the impasse between IT and security when it comes to managing the patch workload.    “Typically, on average, an enterprise may patch 90% of desktops within two to four weeks, 80% of Windows servers within six weeks and only 25% of Oracle Databases within six months from patch release date”, writes Gartner in their recent report, “We’re not patching our way out of vulnerability exposure.” The report states that “the cold, hard reality is that no one is out patching threat actors at scale in any size organization, geography or industry vertical.” Ring deployment: proactive defense at scale Every unpatched endpoint or threat surface invites attackers to exploit it. Enterprises are losing the patching race, which motivates attackers even more. In the meantime, patching has become exponentially more challenging for security and IT teams to manage manually. Approximately a decade ago, ring deployment began to rely on Microsoft-dominated networks. Since then, ring deployments have proliferated across on-premise and cloud-based patch and risk management systems. Ring deployment provides a phased, automated strategy, shrinking attacker windows and breach risks. Ring deployment rolls out patches incrementally through carefully controlled stages or “rings:” Test Ring (1%): Core IT teams quickly validate patch stability. Early Adopter Ring (5–10%): A broader internal group confirms real-world compatibility. Production Ring (80–90%): Enterprise-wide rollout after stability is conclusively proven. Ivanti’s recent release of ring deployment is designed to give security teams greater control over when patches will be deployed, to which systems and how each sequence of updates will be managed. By addressing patching issues early, the goal is to minimize risks and reduce and eliminate disruptions. Gartner’s ring deployment strategy escalates patches from internal IT outward, providing continuous validation and dramatically reducing deployment risk. Source: Gartner, “Modernize Windows and Third-Party Application Patching,” p. 6. Ring deployment crushes MTTP, ends reactive patching chaos Relying on outdated vulnerability ratings to lead patch management strategies only increases the risk of a breach as enterprises race to keep up with growing patch backlogs. That’s often when patching becomes cybersecurity’s endless nightmare, with attackers looking to capitalize on the many legacy CVEs that remain unprotected. Gartner’s take in their recent report “Modernize windows and third-party application patching” makes the point brutally clear, showing how traditional patching methods routinely fail to keep pace. In contrast, enterprises embracing ring deployment are getting measurable results. Their research finds ring deployment achieves a “99% patch success within 24 hours for up to 100,000 PCs,” leaving traditional methods far behind. During an interview with VentureBeat, Tony Miller, Ivanti’s VP of enterprise services, emphasized that “Ivanti Neurons for Patch Management and implementing Ring Deployment is an important part of our Customer Zero journey.” He said the company uses many of its own products, which allows for a quick feedback loop and gives developers insight into customers’ pain points. Miller added: “We’ve tested out Ring Deployment internally with a limited group, and we are in the process of rolling it out organization-wide. In our test group, we have benefited from deploying patches based on real-world risk, and ensuring that updates don’t interrupt employee productivity–a significant challenge for any IT organization.” VentureBeat also spoke with Jesse Miller, SVP and director of IT at Southstar Bank, about leveraging Ivanti’s dynamic Vulnerability Risk Rating (VRR), an AI-driven system continuously recalibrated with real-time threat intelligence, live exploit activity, and current attack data. Miller stated clearly: “This is an important change for us and the entire industry. Judging a patch based on its CVSS now is like working in a vacuum. When judging how impactful something can be, you have to take everything from current events, your industry, your environment and more into the equation. Ultimately, we are just making wiser decisions as we are not disregarding CVSS scoring; we are simply adding to it.” Miller also highlighted his team’s prioritization strategy: “We have been able to focus on prioritizing Zero-Day and Priority patches to get out first, as well as anything being exploited live in the wild. Using patch prioritization helps us eliminate our biggest risk first so that we can reduce our attack surface as quickly as possible.” By combining ring deployment and dynamic VRR technology, Ivanti Neurons provides enterprises with structured visual orchestration of incremental patch rollouts. This approach sharply reduces Mean-Time-to-Patch (MTTP), accelerating patches from targeted testing through full deployment and significantly decreasing the exposure windows that attackers exploit. Caption: The Ivanti Neurons interface visually manages deployment rings, success thresholds, patching progress and streamlining operational clarity. Source: Ivanti Neurons Comparing Ivanti Neurons, Microsoft Autopatch, Tanium and ServiceNow: Key strengths and gaps When selecting enterprise patch management solutions, apparent differences emerge among leading providers, including Microsoft Autopatch, Tanium, ServiceNow and Ivanti Neurons. Microsoft Autopatch relies on ring deployment but is restricted to Windows environments, including Microsoft 365 applications. Ivanti Neurons expands on this concept by covering a broader spectrum, including Windows, macOS, Linux and various third-party applications. This enables enterprise-wide patch management for organizations with large-scale, diverse infrastructure. Tanium stands out for its robust endpoint visibility and detailed reporting features, but its infrastructure requirements typically align better with resource-intensive enterprises. Meanwhile, ServiceNow’s strength lies in workflow automation and IT service management integrations. Executing actual patches often demands significant additional customization or third-party integrations. Ivanti Neurons aims to differentiate by integrating dynamic risk assessments, phased ring deployments and automated workflows within a single platform. It directly addresses common enterprise challenges in patch management, including visibility gaps, operational complexity and uncertainty about vulnerability prioritization with real-time risk assessments and intuitive visual dashboards. Caption: Ivanti Neurons provides real-time patch status, vulnerability assessments, and risk exposure metrics, ensuring continuous visibility. Source: Ivanti Neurons Transforming patch management into a strategic advantage Patching alone cannot eliminate vulnerability exposure. Gartner’s analysts continue to stress the necessity of integrating compensating controls, including endpoint protection platforms (EPP), multifactor authentication, and network segmentation to reinforce security beyond basic patching. Combining ring deployment with integrated compensating controls that are part of a broader zero-trust framework ensures security, allows IT teams to shrink exposure windows, and better manage cyber risks. Ivanti’s approach to ring deployment incorporates real-time risk assessments, automated remediation workflows, and built-in threat management, directly aligning patch management with broader business resilience strategies. The design decision to make it part of Neurons for Patch Management delivers the scale enterprises need to improve risk management’s real-time visibility.   Bottom line: Integrating ring deployment with compensating controls and prioritization tools transforms patch management from a reactive burden to a strategic advantage. Daily insights on business use cases with VB Daily If you want to impress your boss, VB Daily has you covered. We give you the inside scoop on what companies are doing with generative AI, from regulatory shifts to practical deployments, so you can share insights for maximum ROI. Read our Privacy Policy Thanks for subscribing. Check out more VB newsletters here. An error occured.

Ali Niknam has built Dutch fintech Bunq into one of Europe’s biggest neobanks. But he fears the Netherlands is now driving entrepreneurs away. The Bunq founder and CEO is alarmed by the country’s business mindset. He believes risk-aversion, growing insularity, and hostility to ambition are pushing talent overseas. “Many of the best entrepreneurs I know have either left or are considering leaving,” Niknam tells TNW. Surveys back him up. A poll last year found that almost one in five Dutch entrepreneurs were considering relocating — up from nearly one in eight in 2023. The 💜 of EU techThe latest rumblings from the EU tech scene, a story from our wise ol' founder Boris, and some questionable AI art. It's free, every week, in your inbox. Sign up now!Another study found that 24% of large companies were contemplating moves abroad — nearly double the share from the year before.  Tech scaleups are also mulling exits. One of the country’s biggest — software unicorn Bird — recently announced plans to shift operations out of the country. The company’s CEO blamed “over-regulation” and a bad climate for tech businesses. Niknam — who’s set to speak at TNW Conference on June 20 in Amsterdam — has his own critiques of the Dutch business landscape. He calls its support for entrepreneurship “among the worst” he’s seen. Yet he still has deep faith in the country’s talent pool.  “There are very few countries I know that have such amazing, creative, smart people as the Dutch,” he says.  Those people have been integral to Bunq’s rapid growth. Building bridges at Bunq Niknam’s idea for Bunq emerged in the wake of the 2008 financial crisis. One of the causes, he believes, was groupthink at incumbent banks. He founded Bunq in 2012 to create an alternative.  To create a new approach to banking, Niknam sought to embrace diverse ideas. He points to the company’s approach to proposals, which can be pitched anonymously — even to Niknam himself. “On the one hand, that’s better for the company — the best ideas win. And on the other hand, it makes it more fair, because all that counts is the quality of your idea, not who you know, where you’re brought up, or what school you attended.” The strategy delivered rapid results. In 2015, Bunq became the first Dutch company in 35 years to obtain a greenfield banking license. It then grew into Europe’s second-largest neobank after Revolut — and one of the few to achieve profitability. The company now boasts over 17 million users with more than €8bn in deposits. Outside Bunq, however, Niknam sees a country that’s becoming more closed. He believes the Netherlands is abandoning its internationalist roots, which is damaging its tech ecosystem and chasing talent away.  “Historically, the Netherlands has been very entrepreneurial, very international… when this country retreats and closes the doors is when things start to get worse.” Even the country’s vast pension funds, he notes, avoid backing Dutch startups. “They know the returns are going to be less,” he says. “Why are the returns less? Because it’s a small country, and it is retreating and starting to focus within its own borders.” He contrasts the mood with developments in the Baltics. The region’s tech ecosystem has attracted admiring glances for its optimism, openness, and rapid growth. Niknam feels that many people in the Netherlands take their rights for granted. “It’s maybe a little bit of an entitlement disease — that we have forgotten that all these wonderful things that we enjoy today, somebody worked for them really, really hard,” he says. Born in Canada to Iranian parents and with homes in the Netherlands and the US, Niknam has diverse cultural experiences. Image: OLSjopera Niknam feels the Netherlands has become too risk-averse and inward-looking. Despite the liberal stereotype, Dutch society can be surprisingly conservative.  That caution, Niknam says, is embedded in the culture — even in local proverbs. One goes: “Steek je kop niet boven het maaiveld uit.” Loosely translated: “Don’t stick your head above the mowing line.” If you do, it might get chopped off. In Niknam’s eyes, that mentality thwarts ambitious entrepreneurs. “Success is not only not celebrated, but you’re almost faulted for being successful,” he says.  The international return The Netherlands is also losing its appeal to international talent. Over nine in ten expats and migrant workers no longer even consider coming to work in the country, according to research from last year. Tech firms have raised major concerns over losing access to global talent. The chip equipment maker ASML — the largest company in the Netherlands — has threatened to move abroad because of the country’s hardening stance on migrants. Peter Wennink, ASML’s former CEO — who will also speak at TNW Conference — recently warned against losing access to skilled workers. “If we cannot get those people here, we will get those people in Eastern Europe or in Asia or in the United States,” he said. Still, Niknam believes the tide can turn. For change to come, he believes the “silent majority” — those who value openness and diversity — must speak up.  Despite its problems, Niknam remains upbeat about the future for tech businesses in the Netherlands. “The people are great. The schooling is great. The infrastructure is great,” he says. “It is simply changing the attitude and mindset — which can happen in a relatively short amount of time — that will make all the difference.” If you want to catch the talks by Niknam and Wennink — or anything else on the agenda for TNW Conference — we have a special offer for you. Use the code TNWXMEDIA2025 at the checkout to get 30% off your ticket. Story by Thomas Macaulay Managing editor Thomas is the managing editor of TNW. He leads our coverage of European tech and oversees our talented team of writers. Away from work, he e (show all) Thomas is the managing editor of TNW. He leads our coverage of European tech and oversees our talented team of writers. Away from work, he enjoys playing chess (badly) and the guitar (even worse). Get the TNW newsletter Get the most important tech news in your inbox each week. Also tagged with

Junior ProducerTechlandWrocław Województwo dolnośląskie pl1 hour agoApplyJob DescriptionYour daily tasks:Supporting lead producers in the daily organization of work for development teamsCreating and updating tasks, schedules, and reportsAssisting in coordinating work between departmentsResponding to production issues and proposing solutionsParticipating in team meetings, taking notes on decisions, and ensuring they are followed throughTaking initiative — you will truly have an impactQualificationsA high level of commitment and willingness to learn — passion and attitude are more important to us than experience,Excellent organization of your own work and that of others,Proactiveness — you don't wait for someone to tell you what to do, you take initiative,Strong communication skills and the ability to work in a team,Resilience to stress and shifting priorities,Familiarity with tools like Jira / Confluence / Sheets is a plus, but we’ll teach you everything you need to know.Advanced English proficiency.Nice to haveAdvanced Polish proficiency.Additional InformationWhat we can offer:A wide array of benefits: private medical care, life insurance, pro-health campaigns, gifts for different occasions.An outstanding work atmosphere in a highly-skilled team of professionals, with flexible working hours, no dress code, and full support of the dedicated HR Business Partner.A constant stream of company newsletters, PR & project updates so you will always be in the know.Many opportunities for personal development: a dedicated development budget for each employee, extra two paid days for training and CSR, stable career paths, extensive internal and external training, and financing of English and Polish language classes.State-of-the-art offices filled with chillout zones, a fully equipped kitchen, a gym (Wrocław office), and a free car park (Wrocław/Warsaw office).Company DescriptionTechland is one of the biggest video game companies in Poland, with over 30 years of experience in the gaming industry. From our studios in Wroclaw and Warsaw, we’ve built an international team of more than 500 talented professionals, all dedicated to pushing the boundaries of game development. We’re known for creating iconic franchises like Call of Juarez and the zombie genre-defining Dying Light, which has been played by over 45 million players worldwide. With a focus on open-world action, storytelling, and community engagement, we’re committed to delivering unforgettable experiences to our players.We’re constantly striving to improve, innovate, and take on new challenges. With ambitious plans for the future, we’re looking for passionate people to be part of this exciting journey.Create Your Profile — Game companies can contact you with their relevant job openings. Apply

AI’s thirst for energy is ballooning into a monster of a challenge. And it’s not just about the electricity bills. The environmental fallout is serious, stretching to guzzling precious water resources, creating mountains of electronic waste, and, yes, adding to those greenhouse gas emissions we’re all trying to cut.As AI models get ever more complex and weave themselves into yet more parts of our lives, a massive question mark hangs in the air: can we power this revolution without costing the Earth?The numbers don’t lie: AI’s energy demand is escalating fastThe sheer computing power needed for the smartest AI out there is on an almost unbelievable upward curve – some say it’s doubling roughly every few months. This isn’t a gentle slope; it’s a vertical climb that’s threatening to leave even our most optimistic energy plans in the dust.To give you a sense of scale, AI’s future energy needs could soon gulp down as much electricity as entire countries like Japan or the Netherlands, or even large US states like California. When you hear stats like that, you start to see the potential squeeze AI could put on the power grids we all rely on.2024 saw a record 4.3% surge in global electricity demand, and AI’s expansion was a big reason why, alongside the boom in electric cars and factories working harder. Wind back to 2022, and data centres, AI, and even cryptocurrency mining were already accounting for nearly 2% of all the electricity used worldwide – that’s about 460 terawatt-hours (TWh).Jump to 2024, and data centres on their own use around 415 TWh, which is roughly 1.5% of the global total, and growing at 12% a year. AI’s direct share of that slice is still relatively small – about 20 TWh, or 0.02% of global energy use – but hold onto your hats, because that number is set to rocket upwards.The forecasts? Well, they’re pretty eye-opening. By the end of 2025, AI data centres around the world could demand an extra 10 gigawatts (GW) of power. That’s more than the entire power capacity of a place like Utah.Roll on to 2026, and global data centre electricity use could hit 1,000 TWh – similar to what Japan uses right now. And, by 2027, the global power hunger of AI data centres is tipped to reach 68 GW, which is almost what California had in total power capacity back in 2022. Towards the end of this decade, the figures get even more jaw-dropping. Global data centre electricity consumption is predicted to double to around 945 TWh by 2030, which is just shy of 3% of all the electricity used on the planet.OPEC reckons data centre electricity use could even triple to 1,500 TWh by then. And Goldman Sachs? They’re saying global power demand from data centres could leap by as much as 165% compared to 2023, with those data centres specifically kitted out for AI seeing their demand shoot up by more than four times.There are even suggestions that data centres could be responsible for up to 21% of all global energy demand by 2030 if you count the energy it takes to get AI services to us, the users.When we talk about AI’s energy use, it mainly splits into two big chunks: training the AI, and then actually using it.Training enormous models, like GPT-4, takes a colossal amount of energy. Just to train GPT-3, for example, it’s estimated they used 1,287 megawatt-hours (MWh) of electricity, and GPT-4 is thought to have needed a whopping 50 times more than that. While training is a power hog, it’s the day-to-day running of these trained models that can chew through over 80% of AI’s total energy. It’s reported that asking ChatGPT a single question uses about ten times more energy than a Google search (we’re talking roughly 2.9 Wh versus 0.3 Wh).With everyone jumping on the generative AI bandwagon, the race is on to build ever more powerful – and therefore more energy-guzzling – data centres.So, can we supply energy for AI – and for ourselves?This is the million-dollar question, isn’t it? Can our planet’s energy systems cope with this new demand? We’re already juggling a mix of fossil fuels, nuclear power, and renewables. If we’re going to feed AI’s growing appetite sustainably, we need to ramp up and diversify how we generate energy, and fast.Naturally, renewable energy – solar, wind, hydro, geothermal – is a huge piece of the puzzle. In the US, for instance, renewables are set to go from 23% of power generation in 2024 to 27% by 2026. The tech giants are making some big promises; Microsoft, for example, is planning to buy 10.5 GW of renewable energy between 2026 and 2030 just for its data centres. AI itself could actually help us use renewable energy more efficiently, perhaps cutting energy use by up to 60% in some areas by making energy storage smarter and managing power grids better.But let’s not get carried away. Renewables have their own headaches. The sun doesn’t always shine, and the wind doesn’t always blow, which is a real problem for data centres that need power around the clock, every single day. The batteries we have now to smooth out these bumps are often expensive and take up a lot of room. Plus, plugging massive new renewable projects into our existing power grids can be a slow and complicated business.This is where nuclear power is starting to look more appealing to some, especially as a steady, low-carbon way to power AI’s massive energy needs. It delivers that crucial 24/7 power, which is exactly what data centres crave. There’s a lot of buzz around Small Modular Reactors (SMRs) too, because they’re potentially more flexible and have beefed-up safety features. And it’s not just talk; big names like Microsoft, Amazon, and Google are seriously looking into nuclear options.Matt Garman, who heads up AWS, recently put it plainly to the BBC, calling nuclear a “great solution” for data centres. He said it’s “an excellent source of zero carbon, 24/7 power.” He also stressed that planning for future energy is a massive part of what AWS does.“It’s something we plan many years out,” Garman mentioned. “We invest ahead. I think the world is going to have to build new technologies. I believe nuclear is a big part of that, particularly as we look 10 years out.”Still, nuclear power isn’t a magic wand. Building new reactors takes a notoriously long time, costs a fortune, and involves wading through complex red tape. And let’s be frank, public opinion on nuclear power is still a bit shaky, often because of past accidents, even though modern reactors are much safer.The sheer speed at which AI is developing also creates a bit of a mismatch with how long it takes to get a new nuclear plant up and running. This could mean we end up leaning even more heavily on fossil fuels in the short term, which isn’t great for our green ambitions. Plus, the idea of sticking data centres right next to nuclear plants has got some people worried about what that might do to electricity prices and reliability for everyone else.Not just kilowatts: Wider environmental shadow of AI loomsAI’s impact on the planet goes way beyond just the electricity it uses. Those data centres get hot, and cooling them down uses vast amounts of water. Your average data centre sips about 1.7 litres of water for every kilowatt-hour of energy it burns through.Back in 2022, Google’s data centres reportedly drank their way through about 5 billion gallons of fresh water – that’s a 20% jump from the year before. Some estimates suggest that for every kWh a data centre uses, it might need up to two litres of water just for cooling. Put it another way, global AI infrastructure could soon be chugging six times more water than the entirety of Denmark.And then there’s the ever-growing mountain of electronic waste, or e-waste. Because AI tech – especially specialised hardware like GPUs and TPUs – moves so fast, old kit gets thrown out more often. We could be looking at AI contributing to an e-waste pile-up from data centres hitting five million tons every year by 2030. Even making the AI chips and all the other bits for data centres takes a toll on our natural resources and the environment. It means mining for critical minerals like lithium and cobalt, often using methods that aren’t exactly kind to the planet.Just to make one AI chip can take over 1,400 litres of water and 3,000 kWh of electricity. This hunger for new hardware is also pushing for more semiconductor factories, which, guess what, often leads to more gas-powered energy plants being built.And, of course, we can’t forget the carbon emissions. When AI is powered by electricity generated from burning fossil fuels, it adds to the climate change problem we’re all facing. It’s estimated that training just one big AI model can pump out as much CO2 as hundreds of US homes do in a year.If you look at the environmental reports from the big tech companies, you can see AI’s growing carbon footprint. Microsoft’s yearly emissions, for example, went up by about 40% between 2020 and 2023, mostly because they were building more data centres for AI. Google also reported that its total greenhouse gas emissions have shot up by nearly 50% over the last five years, with the power demands of its AI data centres being a major culprit.Can we innovate our way out?It might sound like all doom and gloom, but a combination of new ideas could help.A big focus is on making AI algorithms themselves more energy-efficient. Researchers are coming up with clever tricks like “model pruning” (stripping out unnecessary bits of an AI model), “quantisation” (using less precise numbers, which saves energy), and “knowledge distillation” (where a smaller, thriftier AI model learns from a big, complex one). Designing smaller, more specialised AI models that do specific jobs with less power is also a priority.Inside data centres, things like “power capping” (putting a lid on how much power hardware can draw) and “dynamic resource allocation” (shifting computing power around based on real-time needs and when renewable energy is plentiful) can make a real difference. Software that’s “AI-aware” can even shift less urgent AI jobs to times when energy is cleaner or demand on the grid is lower. AI can even be used to make the cooling systems in data centres more efficient.On-device AI could also help to reduce power consumption. Instead of sending data off to massive, power-hungry cloud data centres, the AI processing happens right there on your phone or device. This could slash energy use, as the chips designed for this prioritise being efficient over raw power.And we can’t forget about rules and regulations. Governments are starting to wake up to the need to make AI accountable for its energy use and wider environmental impact.Having clear, standard ways to measure and report AI’s footprint is a crucial first step. We also need policies that encourage companies to make hardware that lasts longer and is easier to recycle, to help tackle that e-waste mountain. Things like energy credit trading systems could even give companies a financial reason to choose greener AI tech.It’s worth noting that the United Arab Emirates and the United States shook hands this week on a deal to build the biggest AI campus outside the US in the Gulf. While this shows just how important AI is becoming globally, it also throws a spotlight on why all these energy and environmental concerns need to be front and centre for such huge projects.Finding a sustainable future for AIAI has the power to do some amazing things, but its ferocious appetite for energy is a serious hurdle. The predictions for its future power demands are genuinely startling, potentially matching what whole countries use.If we’re going to meet this demand, we need a smart mix of energy sources. Renewables are fantastic for the long run, but they have their wobbles when it comes to consistent supply and scaling up quickly. Nuclear power – including those newer SMRs – offers a reliable, low-carbon option that’s definitely catching the eye of big tech companies. But we still need to get our heads around the safety, cost, and how long they take to build.And remember, it’s not just about electricity. AI’s broader environmental impact – from the water it drinks to cool data centres, to the growing piles of e-waste from its hardware, and the resources it uses up during manufacturing – is huge. We need to look at the whole picture if we’re serious about lessening AI’s ecological footprint.The good news? There are plenty of promising ideas and innovations bubbling up. Energy-saving AI algorithms, clever power management in data centres, AI-aware software that can manage workloads intelligently, and the shift towards on-device AI all offer ways to cut down on energy use. Plus, the fact that we’re even talking about AI’s environmental impact more means that discussions around policies and rules to push for sustainability are finally happening.Dealing with AI’s energy and environmental challenges needs everyone – researchers, the tech industry, and policymakers – to roll up their sleeves and work together, and fast.If we make energy efficiency a top priority in how AI is developed, invest properly in sustainable energy, manage hardware responsibly from cradle to grave, and put supportive policies in place, we can aim for a future where AI’s incredible potential is unlocked in a way that doesn’t break our planet.The race to lead in AI has to be a race for sustainable AI too.(Photo by Nejc Soklič)Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.Explore other upcoming enterprise technology events and webinars powered by TechForge here.

Nails by Kumi. Image © Kumi Chantrill Fresh Sets: Tembe Denton-Hurst Celebrates 35 Boundary-Pushing Nail Artists May 16, 2025 BooksDesign Jackie Andres From the birth of the first modern nail parlor in 19th-century Paris to the rise of the Vietnamese nail industry in America after the fall of Saigon, nail beautification has always been connected to the world it adorns. Author Tembe Denton-Hurst reminds us of this in her new book, Fresh Sets: Contemporary Nail Art from Around the World. Setting the scene with her own experience of falling in love with manicures as a child in Brooklyn and a brief survey of the transformative history of nail embellishment throughout time, the book showcases 35 standout artists thriving today. Nails by Kumi. Image © Kiel Wode. All photos courtesy of Prestel Publishing, shared with permission While basic sets remain timeless, there’s no doubt that in the 21st century, contemporary aesthetics have flourished in a subversive, powerful way. From birthday candle pedicures and maximalist jeweled acrylics to moss-covered fingertips and sculpted claws channeling cyber sigilism, Fresh Sets features 300 vibrant images highlighting ongoing innovations in the medium. The democratization of nail art has allowed the creative form to flourish across time and space. Extravagant designs once only seen sauntering down the catwalk, for instance, are now within reach for daily wear. The rise of nail artists has uniquely blurred this line between luxury and everyday accessory, forging paths and connecting worlds. One such artist featured in Fresh Sets is Lauren Michelle Pires. With a methodical precision, she approaches her practice as a designer, collecting extensive archives of color combinations and references images. Once a fashion student, Pires now works with designer brands such as Loewe, Diesel, Miu Miu, and more. “I view being a nail artist as a very intricate and pristine job, and I definitely try to capture beauty in my work,” she explains. “But, over time, I’ve really learned how to experiment more and to lean into the awkwardness of beauty.” Nails by Kumi. Image © Kiel Wode As the realm of nail design continues to evolve in tremendous fashion, transforming one’s own fingernails as if they were ten tiny canvases—each a site for creating an extension of self, asserting identity, and even signifying resistance—has and always will be a deeply resonant gesture for many. As Denton-Hurst shares in the introduction, “long nails have become part of me, as identifiable as the brown of my skin or my loud laugh.” You can find your own copy of Fresh Sets on Bookshop. See more from Tembe Denton-Hurst on Instagram. Nails by Iksoxo. Image © Alona Sobolevska Nails by Dxpper Acrylics. Image © Black Archives Nails and image © Tomoya Nakagawa Nails and image © Naomi Yasuda Nails by Juan. Image © Juan Alvear Nails by Yeswhat Nails. Image © Violetta Kurilenko Nails and image © Tomoya Nakagawa Nails and image © Nikki Panic Next article

Junior ProducerTechlandWrocław Województwo dolnośląskie pl1 hour agoApplyJob DescriptionYour daily tasks:Supporting lead producers in the daily organization of work for development teamsCreating and updating tasks, schedules, and reportsAssisting in coordinating work between departmentsResponding to production issues and proposing solutionsParticipating in team meetings, taking notes on decisions, and ensuring they are followed throughTaking initiative — you will truly have an impactQualificationsA high level of commitment and willingness to learn — passion and attitude are more important to us than experience,Excellent organization of your own work and that of others,Proactiveness — you don't wait for someone to tell you what to do, you take initiative,Strong communication skills and the ability to work in a team,Resilience to stress and shifting priorities,Familiarity with tools like Jira / Confluence / Sheets is a plus, but we’ll teach you everything you need to know.Fluent English and fluent Polish proficiency.Additional InformationWhat we can offer:A wide array of benefits: private medical care, life insurance, pro-health campaigns, gifts for different occasions.An outstanding work atmosphere in a highly-skilled team of professionals, with flexible working hours, no dress code, and full support of the dedicated HR Business Partner.A constant stream of company newsletters, PR & project updates so you will always be in the know.Many opportunities for personal development: a dedicated development budget for each employee, extra two paid days for training and CSR, stable career paths, extensive internal and external training, and financing of English and Polish language classes.State-of-the-art offices filled with chillout zones, a fully equipped kitchen, a gym (Wrocław office), and a free car park (Wrocław/Warsaw office).Company DescriptionTechland is one of the biggest video game companies in Poland, with over 30 years of experience in the gaming industry. From our studios in Wroclaw and Warsaw, we’ve built an international team of more than 500 talented professionals, all dedicated to pushing the boundaries of game development. We’re known for creating iconic franchises like Call of Juarez and the zombie genre-defining Dying Light, which has been played by over 45 million players worldwide. With a focus on open-world action, storytelling, and community engagement, we’re committed to delivering unforgettable experiences to our players.We’re constantly striving to improve, innovate, and take on new challenges. With ambitious plans for the future, we’re looking for passionate people to be part of this exciting journey.Create Your Profile — Game companies can contact you with their relevant job openings. Apply

Air travel is remarkably, astonishingly safe. Every year, commercial US airlines take more than 800 million domestic passengers to their destinations, and in a typical year, zero of them are killed and very few are injured. It’s a track record made possible by a fairly intense commitment to safety. But increasingly over the last few years, we’ve been testing these limits.This story was first featured in the Future Perfect newsletter.Sign up here to explore the big, complicated problems the world faces and the most efficient ways to solve them. Sent twice a week.Right now the example in the headlines is New Jersey’s Newark Liberty International Airport, which had three air traffic controllers on duty when it was supposed to have 14 and which over the last couple of weeks suffered three “communications blackouts” where air traffic controllers couldn’t communicate with approaching planes.But it’s not just Newark. There has been an alarming rise in near-misses, communications blackouts, and other serious problems over the last few years at airports across the country, often a consequence of understaffing and high traffic. The midair collision near Reagan National Airport in Washington earlier this year that killed over 60 people was the deadliest air crash in the US since 2001.Even with the Washington disaster, very few of these incidents, thankfully, get anyone killed. That’s because the US achieves the astonishing safety of our air travel system with defense in depth, which means a bunch of different things have to go wrong for a crash to happen.Planes have on-board systems that should alert them if they’re too near another plane, even if air traffic control is sleeping on the job. There are backup emergency frequencies in case a communications blackout occurs. There are pre-published procedures for what to do in the event of a landing that looks unsafe, so if the pilots find themselves abruptly entirely out of contact with the ground, or coming in for a landing on a runway that they realize too late isn’t clear, they have been trained on precisely how to respond.Pushing our defenses against disaster to the limitsIn the risk analysis world, this is called the “Swiss cheese” model of how to prevent a disaster. Every layer of a system made up of humans — with all our flaws — is going to have some gaps. Air traffic controllers will have a bad day, or be tired, or let something slip their mind. Technological solutions will have limitations and edge cases. Pilots will make mistakes or have a medical emergency or get confused by unusual instructions. So each layer of the defenses against disaster has “holes” in it. But so long as the holes don’t all line up — so long as there isn’t a gap in every single layer at the same time — the defenses hold, and the planes land safely. All of this means that despite the absurd strain on air traffic controllers, flying out of Newark is still almost certainly going to go fine. But to achieve and maintain the exceptionally low accident levels that we’ve taken pride in over the last 20 years, “almost certainly” isn’t good enough. If you want not just 99.9 percent of planes but every single plane, every single year, to land safely, you can’t afford to let one of the layers of our defenses get more and more full of holes. A “near miss” where several layers of defenses fail should be taken incredibly seriously and prompt changes, even if one other layer sufficed to save us.Any event which would have been a mass casualty event if not for the good judgment and quick thinking of the pilots, or if not for good weather, or if not for an activation of the automatic TCAS collision avoidance system, needs to be treated as a major emergency. If we let near-misses become business as usual, then it’s inevitable that some percentage of them will convert into actual mass disasters — as happened in Washington this January, where a helicopter and plane collided in an airspace that was known to have risky amounts of helicopter traffic and a bunch of alarming near-misses.This is, of course, important in its own right, since every single commercial plane crash is a preventable tragedy. But it’s also, I sometimes fear, a symptom of a broader cultural malaise. Plane crashes used to be horrifyingly common. We made them rarer through a comprehensive, aggressive program to add layers of defense against human error, revising our procedures through tragedy after tragedy. And we succeeded.If you read the description of almost any plane crash that occurred in the 1970s, one thing stands out: It could not have happened today. Through mechanical improvements, procedural improvements, training improvements, and backup systems, we’ve built planes that are much, much harder to crash. But then, as frequent deadly plane crashes became a distant cultural memory, we immediately started testing how far we could underresource those systems. We ignored near-misses and staffing shortages; we failed to heed warnings that our systems are in trouble and our procedures need changes. Boeing pushed out a dangerous new plane, hoping that other layers of our collective defenses against crashes would suffice to keep them in the air; in the US, those other layers were sufficient, but in poorer countries, they were not. We’ve lost our fearThe parallels to other areas of modern life stand out. It used to be that half of children were dead before age 5; vaccination changed that, but in the world made safe by vaccination, parents grew skeptical of it. Now kids are dying of measles again. It’s been observed that “what if we hike tariffs?” is an idea that comes around once a century or so, and goes badly enough we’re warned off it for a while. We have to touch the hot stove ourselves to learn that it burns us, it seems: The cultural memory doesn’t last for all that long.This isn’t necessarily a bad thing, by itself. I wouldn’t want to live in a world where caution only ever ratchets up; safety is a trade-off, and it’s reasonable to relax precautions if we still get good results without those precautions. But in some cases — like understaffing air traffic control or not vaccinating against measles — the precaution in question passes any reasonable cost-benefit calculation. Our “lesson” is taught by the deaths of innocent people. And more terrifyingly, it’s not clear we’re even learning from our brush with reality. Were the deaths of children in Texas enough to turn around measles vaccination rates? Did the crash over the Potomac teach us to start paying more attention to near-misses? It’s too early to say, but it doesn’t look good so far — and that is what really scares me.A version of this story originally appeared in the Future Perfect newsletter. Sign up here!You’ve read 1 article in the last monthHere at Vox, we're unwavering in our commitment to covering the issues that matter most to you — threats to democracy, immigration, reproductive rights, the environment, and the rising polarization across this country.Our mission is to provide clear, accessible journalism that empowers you to stay informed and engaged in shaping our world. By becoming a Vox Member, you directly strengthen our ability to deliver in-depth, independent reporting that drives meaningful change.We rely on readers like you — join us.Swati SharmaVox Editor-in-ChiefSee More: Future Perfect