Miriam Vizvary

Sergiu Manea, CEO of BCR, speaks in an interview with PwC about trust and how important it is when we talk about economic growth. The head of BCR says that in 2025 trust eroded for seven consecutive months, reaching its lowest level in five years in October, according to the Economic Sentiment Indicator (ESI). "When trust declines, everything around it declines as well. Consumers become more cautious, companies postpone investments, managers recalibrate their plans, and essentially, a form of mental stand-by sets in that pauses development. For me, this is the main concern. Not the numbers themselves, but the reflex, the tendency to slow down at a time when the world is going through the most accelerated technological transformation of the last 50 years. The advance of AI is rewriting the rules of the game. It is changing the way we produce, the way we work, and the way we create value. It is perhaps the first force that does not just transform one industry or another, but simultaneously rewrites the DNA of all industries. And here lies one of Romania’s greatest opportunities, an opportunity that does not allow us to postpone action or stay on the sidelines. In fact, the way we choose to implement technology, the pace and the investments we make, and our ability to make it easy for people to understand it, to integrate it into processes, education, and companies, are all key factors. All these will define Romania’s economic growth curve for the next 20 years", says Sergiu Manea. That observation is hard to dispute. The way we implement technology and the investments we make will define how Romania grows over the next 20 years. Perhaps even longer.

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It was a pleasure meeting our dear partner Marketeye’s Bartosz Nowak and eminent CPG brands of the thriving Polish market last week in Poland. Vispera’s #imagerecognition tech with Marketeye’s service experience and complementary offerings can contribute a great deal to the quality and efficiency of retail execution in Poland. Bartosz’s writeup is an insightful reading into this.

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🚀 The EU #AI Act is coming — but treating it as a tick-box exercise would be a missed opportunity. From 2025, companies using high-risk AI systems in the EU will be required to train their people to use them safely, ethically, and responsibly. It’s a strong step forward. But regulation alone won’t transform how businesses work. The shift happens when people actually understand how to use AI in the context of their day-to-day jobs. The demand is already there. According to McKinsey and the European Commission, over 25% of professionals in the EU use #generativeAI tools at least once a week. More than 30% use them several times a day. The interest is real—what’s missing is structure, guidance, and confidence. That’s why training matters. But it has to be more than a formality. It needs to be practical, relevant, and focused on outcomes. People need to know how AI helps them do their jobs better—whether they’re analysing data, writing copy, or making decisions. At FLO, we treat #AIenablement the same way we treat any transformation: embedded, purposeful, and built around real use. This isn’t about keeping up appearances. It’s about building skills that last. #AIliteracy should be as fundamental as Excel or Sheets. And the organisations that get this right won’t just comply. They’ll lead. Read more in CIOTrends (in Czech) 👇 https://lnkd.in/epNC5cnp

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As a child, I didn't just admire robots for the technology. I was fascinated by the elegance of the Three Laws of Robotics. 1️⃣ A robot may not injure a human being or, through inaction, allow a human being to come to harm. 2️⃣ A robot must obey the orders given it by human beings except where such orders would conflict with the First Law. 3️⃣ A robot must protect its own existence as long as such protection does not conflict with the First or Second Law. Simple. Precise. Safe. It seemed like the perfect framework. Yet, for a long time, I haven't heard them mentioned in serious debate. They felt like a concept for a distant sci-fi future. That changed when I heard Jaroslav Beck bring them up in the latest Fantastic Future episode with Petr Mára and Lubo Smid, https://lnkd.in/dDp5jpBc. And it made me realize something crucial: ➡️ It is time to put the Laws of Robotics back on the table. But we need to talk about them much more urgently than before. And not just in the context of physical hardware—robots that can walk or carry objects. We need to apply them to the virtual ones. The AI agents, algorithms, and models that are becoming invisible members of our teams. What do you think? Is it time to update these laws for the era of LLMs? 👇 #AI #Robotics #Ethics #FutureOfWork #Technology

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When we think of data applications, it’s easy to focus only on functionality, but what if we could merge analytical power with design that truly engages users? Learning to build Shiny apps with HTML, CSS, and JavaScript isn’t just about adding polish; it’s about reimagining how data stories are told and experienced. This course is designed to spark that shift in perspective: to see Shiny not as a static reporting tool, but as a canvas where interactivity, aesthetics, and insight come together to create something that resonates. Check comments for the link

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Magdalena Cebula puts it bluntly: early in a data career it’s super easy to fall into two traps that can slow you down for years 👇 💡 “I’ll learn it someday” - pushing harder topics (like neural networks) into an undefined future that… never really comes. 💡 Portfolio perfectionism - thinking your GitHub must only show “polished” projects, which often leads to… posting nothing at all. Sound familiar? 😅 Which one have you struggled with most? #datacareer #datascience #machinelearning #learning #portfolio #github

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New podcast episode out now! We’re diving into risk-taking, the advantages of being a small company, and the power of building strong relationships, all with Filip Dudek and Mateusz Niedzielski from NOITAC. Tune in here: https://lnkd.in/ePsKFuSq #techpodcast #startups #NOITAC

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The UK public sector is stuck in a data mess. Not because of a tech shortage — but because it still runs on scripts. The future? Autonomous data agents. They don’t just automate tasks. They achieve outcomes. → Clean data → Faster insights → Less manual work Engineers stop coding. They start commanding. This is the agentic shift. #AgenticAI #AIagents #PublicSectorInnovation #GovTech #DataOps #DigitalTransformation #AutonomousAI #AIinGovernment #AIforGood #SmartData #RplusAnalytics

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Who drives impactful analytics at Tesco? A team that leads with insight and execution.   The team starts by identifying the right problems - whether in marketing, pricing, promotions, or supply chain. From there, we build the right algorithmic solutions and work closely with the business to implement solutions that lead to real change.   In the second episode of Analytics Unfiltered, Venkat Raghavan explains how our strength lies in owning the full journey: problem identification, solution development, and execution. Archana Iyer Alexandra Smith (Chartered FCIPD) Dr. Sumit Mitra Elzbieta Golab James Glavey Manish Sethi Pooja Jois Priya Narasimhan Radhika S Rao Ramamoorthy R Shilpa Ahluwalia Somnath Baishya Vijay Krishna #TescoBusinessSolutions #AnalyticsUnfiltered #AIAndAnalytics #FutureReady #DecodeWithVenkat #EnterpriseAnalytics #InsightsThatMatter #AnalyticsForImpact #AdvancedAnalytics

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AI was invented for data people to... write documentation 🫢 A few weeks ago at dbt Coalesce, people could map how they use dbt - and one question was about how they use AI. Apparently, AI’s big breakthrough in data is writing documentation. Funny thing is, I never met one human who actually reads docs. But agents do! So we end up having agents reading docs made by agents 🌀 On the other hand, many data teams are building real use cases of AI for data: with the right context about their data and stack, they can have agents that write ETLs, check data quality, run analytics etc. Let's not be afraid to go there. Let's build things with AI that will actually be used by other humans. 🤩

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At a recent CatchIT Meetup, we had the pleasure of welcoming Kristóf Ignácz and Mátyás Regényi, who shared the story behind their student project at the University of Pécs Faculty of Business and Economics. Their journey started as a classroom assignment and has since grown into an official, funded AI project within the university. What makes this story special is not just the technology, but the combination of young talent, real institutional problems, and the progressive, innovative mindset. The team is building an AI-powered chatbot based on RAG (Retrieval-Augmented Generation) to make university knowledge more accessible, reduce administrative friction, and improve everyday communication for students, staff, and other stakeholders. In this context, AI is not a buzzword, but an accelerator that enables clearer communication and faster access to knowledge across the organization. For me, this project is a great example of how great ideas can emerge when students are trusted with real responsibility and supported with feedback, visibility, and a clear path from prototype to production. Over time, the team has moved from a rough prototype to a proof of concept, then to an agile, institution-backed project with real users and real impact. I admire university graduates who reach something like this. When I was in their position, building a real, production-ready solution inside felt incredibly far away. Seeing students today turn ideas into impact like this is both inspiring and reassuring, and it shows how much potential is unlocked when talent and technology meet in the right environment. I’m genuinely happy that we could support them with professional feedback and provide a stage where their work could be presented to a wider audience. This is exactly what the CatchIT Meetup series is about with Webstar: building bridges between business and IT, showing what becomes possible when these worlds collaborate. 👉 The full recording of their talk is now publicly available on YouTube here: https://lnkd.in/dqyQpTEn If you’re interested in AI, education, innovation, or student-driven projects with real-world impact, I highly recommend watching it. And if this resonates with you, keep an eye on our YouTube channel and my LinkedIn profile, because more content like this is coming soon. #CatchIT #Webstar #ITmeetup #meetup #h6todik #pecs

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Last year at the GoTechWorld summit in Bucharest, a CEO asked me something that I think about constantly: “How do you know when you’re ready to scale digital initiatives beyond the pilot phase?” Most leaders start listing technical requirements - Platform stability…Integration health…Infrastructure capacity… Fair enough. But here’s what I’ve learned after watching dozens of pilots succeed in small environments and then completely stall at scale: The technology is rarely the problem!! The real question is whether your organization is ready to be deeply uncomfortable for 12-18 months. Because scaling a pilot means: ∙ A 20-year department head loses the autonomy he’s built his career on ∙ The process everyone swears by gets retired (even though “it’s always worked fine”) ∙ The founder’s pet system—the one with his name practically on it—gets replaced ∙ Your star performers suddenly look less stellar because you’ve changed how you measure success I’ve watched technically perfect pilots collapse during scale-up. Not because of bugs or integration issues. But because nobody warned the VP of Operations that his entire team structure was about to change. Because the CFO wasn’t prepared to defend new metrics to the board. The transformations that actually work? They have leaders who can look their organization in the eye and say: “This is going to suck for a while. Here’s exactly why we’re doing it anyway. And here’s how I’m going to support you through it.” You can have the best technology stack in the world. If your people aren’t emotionally ready for what’s coming, you’re dead in the water. What’s stopped a transformation in your world—what was the real blocker underneath the official reason? #DigitalTransformation #ChangeManagement #Leadership #GoTechWorld

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Is AI dying? What we’ve called Artificial Intelligence has reached its limits. It’s a statistical machine rearranging past data, predicting the next token, wrapping probability in polish. It doesn’t create. It recombines. And that’s why every tool feels the same, same algorithms, same logic, same boundaries. But a new class of intelligence is emerging behind the scenes: Synthetic Intelligence. Unlike traditional AI, Synthetic Intelligence isn’t confined to static prompts or predictable pipelines. It builds autonomous design pathways, generating self-reconfiguring build chains that evolve as they execute. It doesn’t just write code, it architects systems. It integrates logic, interface, and deployment into a single, adaptive, real-time process. While AI is still iterating drafts, Synthetic Intelligence delivers finished realities. Ideas go in. Products come out. This is the new frontier where Artificial imitates… and Synthetic creates. AI isn’t dying — it’s evolving. #SyntheticIntelligence, #ArtificialIntelligence, #FutureOfAI, #AIEvolution, #NextGenAI

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For years, as the Chief Architect of Czech eGovernment, I tamed massive SQL structures and state systems. These were built on solid foundations but were often defined by their own rigidity. My recent recognition for services to the state became a catalyst for reflection. I realized that technology has finally reached a point where we can close the gap between the power of corporate giants and the practical needs of an ordinary family.  This is why, as an "IT Dinosaur," I am shifting gears to develop RKS (Rodinný Komplexní Systém).  The Vision: Models Over Code While visionaries like Matt Welsh discuss a new computer architecture based on models and natural language communication, I am bringing that concept to life today. I view Welsh’s vision as a confirmation of my direction, but my tools are pragmatic and ready for the "here and now": utilizing SurrealDB and a "flexible metadata" approach. This allows the system to grow organically through intelligent dialogue rather than rigid tables.  The RKS v4.0 Evolution: Mono-Node Intelligence The latest iteration, RKS v4.0 (Cary/Graham Edition), marks a major technical leap:  • Hardware Consolidation: We’ve moved from a distributed cluster to a high-performance Mac Mini.  • The Hybrid Engine: Using a Model Router, the system intelligently switches between Ollama (for private family data), Gemini/OpenAI (for professional archives), and Perplexity (for real-time research).  • Unified Context: Apple Silicon handles vectorization and embeddings natively, creating a seamless "brain capacity" across the entire system.  My Role: The Ontological Guardian I no longer code every line. Instead, I act as a high-level supervisor and the guardian of ontological purity:  • Defining Goals: I determine the evolution of the family’s digital organism.  • Maintaining Context: I ensure the AI never loses the thread within the sea of data.  • Consulting on Progress: I partner with the AI to design new structures.  • Approving Results: No change becomes "fact" without my final signature.  I am building a system where the computer finally understands me, rather than me having to understand the computer. It is a journey toward a new type of computing where models and language replace rigid code. What do you think? Are we witnessing the end of the "clickable app" era in favor of systems driven by models and natural language, or is this still a vision of the distant future? #IT #Architecture #eGovernment #SurrealDB #AI #MattWelsh #RKS #FutureOfComputing #ITDinosaur #DataManagement #NoCode

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🎙 When does data become real business value? 🎧 In our latest podcast episode, we walk through ASURA’s data journey with Marton Tarnok - from the early days to the key moments that proved how essential data is for strategic decision‑making. We discuss: 🔹 what true data‑driven decision‑making looks like in practice 🔹 how data shapes product development 🔹 what clients actually feel from a strong data foundation 🔹 and the mindset that makes a data team thrive in a fast‑changing tech landscape. Data isn’t value by default, it becomes value when it drives the business forward. 🎧 Tune in to the episode! Hosted by Szilvia Fehér YouTube: https://lnkd.in/ghcZwQ4B Spotify: https://lnkd.in/gUbvqWCw #ASURA #Podcast #TechPodcast #AIinPractice #AITalks #TrafficIntelligence #DataDrivenDecisions

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Hybrid vs. Remote Tech Roles: AI/ML Engineers vs. Support Specialists & Power BI Developers The tech industry is evolving rapidly—not just in terms of innovation, but also in how and where we work. Today’s professionals weigh not only skills and salaries but also flexibility, career growth, and global opportunities. Let’s explore the differences between two rising paths: AI/ML Engineers (hybrid roles) and Support Specialists or Power BI Developers (fully remote, B2B roles). 1. AI/ML Engineers (Hybrid Roles) AI/ML engineers often work in a hybrid setup, balancing onsite collaboration with remote flexibility. Experience: Exposure to cutting-edge projects in AI, machine learning, and automation. Benefits: Access to on-premise infrastructure, in-person collaboration for faster problem-solving, and strong career growth in AI-driven industries. Expectations: Frequent brainstorming sessions, working with large datasets, and aligning closely with R&D teams. 2. Support Specialists & Power BI Developers (Fully Remote, B2B) These roles thrive in fully remote, business-to-business models, giving professionals the freedom to work globally. Experience: Client-facing problem-solving, data visualization, and business intelligence insights. Benefits: Greater work-life balance, flexibility in location, and opportunities to collaborate with international clients. Expectations: High communication skills, self-management, and delivering solutions across time zones. The Big Picture: Flexibility & Global Reach Hybrid roles like AI/ML engineering offer deep innovation and collaborative synergy. Fully remote B2B roles such as Support Specialists or Power BI Developers spotlight the rise of a borderless workforce, where location is secondary to skill. 👉 Whether hybrid or remote, both paths reflect the future of work: flexible, global, and driven by expertise. For all our current open roles see: https://lnkd.in/dNi53vX #AI #MachineLearning #PowerBI #RemoteWork #HybridWork #FutureOfWork

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Continuing my reading of Storytelling with Data by Cole Nussbaumer Knaflic This time with M&Ms! 📖🍫   Chapter 2 is all about charts and how to choose one that effectively tells the story you want to tell. Lots of great advice on when to use particular charts and how to improve them to make them more understandable for the audience.   My partner has been a little obsessed buying mini M&Ms. Apart from a being a wee treat, they've been a fun tool for creating charts… I know, a little weird but hey ho, I had fun. How many of each M&M do I have? Do I have more red or green M&Ms?🤔 How easy is it to answer those questions using the image on the left?   Is it any easier using the middle image?   How about using the image on the right? Is there a more effective way to visualise the story I want to tell? And how can I make this chart more accessible? There weren't any M&Ms left after I wrote this post… 😅   storytelling with data Rupe Ltd

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