For Cloudflare’s Jamie Herre, trouble is the engineer’s version of Murphy’s Law: whatever can go wrong will go wrong, and at scale it’s not a matter of if but when. A drive fails. A server goes down. A certificate expires. A link breaks. “If you carry a pager, you know what I’m talking about,” he says. “You can always assume something is broken somewhere.”
Categorie archieven: Blogs
24
feb
feb
Om de snelle ontwikkeling van agentische AI te benutten, zoeken steeds meer mensen naar manieren om persoonlijke AI-agenten te ontwikkelen. Omdat daar ook beveiligingsrisico’s aan verbonden zijn, worden er momenteel veel Mac mini’s gekocht om OpenClaw te draaien. Dat is een open-source, zelfgehoste AI-agent, ontworpen om als persoonlijke assistent te fungeren.
23
feb
feb
Het succes van een professionele keuken is sterk afhankelijk van: mise en place. Letterlijk vertaald betekent dit op zijn plaats zetten. Dus het essentiële proces van het verzamelen, wassen, snijden en ordenen van alle ingrediënten voordat het fornuis wordt aangestoken. Zonder een goede mise en place worden de piekmomenten in een restaurant chaotisch.
17
feb
feb
Do you know where your data is? The number of people who can pat their server and say fondly, “Right here!” is decreasing. Instead, more people are lifting their eyes to the heavens and answering, “Um… up there… somewhere…” McKinsey reports that in 2025, large enterprises have 60% of their environment in the cloud.
14
jan
jan
Veel organisaties worstelen met het volgende: je wilt datagedreven werken, maar… je beslissingen lijken toch vaak te berusten op onderbuikgevoel of gedeeltelijke data. De kern? Je begrijpt niet altijd waar de data vandaan komt, hoe actueel deze is, wie ermee werkt, of welke regels van toepassing zijn. Kortweg: de context ontbreekt. En die context wordt geleverd door metadata – data over data.
04
aug
aug
Imagine this: you walk into your workplace and some of your colleagues are no longer human. They’re not robots in the traditional sense, but agents – autonomous software entities, each trained on vast datasets, equipped with decision-making power, and capable of performing economic, civic, and operational tasks at scale. These agents write policies, monitor supply chains, process health records, generate news, and even govern our digital interactions.
29
jul
jul
In recent discussions around artificial intelligence, skepticism often overshadows its transformative potential. The chatter sometimes dismisses the technology as mere hype, undermining its real-world applications. The problem is organizations haven’t yet exposed most of their data to AI. It’s held in proprietary silos, obfuscated by the potential insights and value that AI can deliver to the business. However, the creation of a data platform specifically designed for AI holds the promise to address long-standing issues in enterprise organizations, such as data silos. This problem, persistent for well over two decades, is only worsening without timely intervention.
18
jul
jul
You’ve probably heard the phrase ‘garbage in, garbage out’. That’s always been true in analytics, but in today’s AI-driven world, the consequences of poor data are greatly amplified. Flawed models, biased predictions and opaque decision-making all trace back to one root cause: a data foundation that just isn’t ready.
02
jun
jun
74% of global CIOs have a data lakehouse in their technology stack, with nearly all others planning to implement one within the next three years, according to Databricks. And it’s no wonder adoption is accelerating; modern data architecture is a necessity in the AI race. So, if your data platform can’t match your AI ambitions, you’re already behind. Data demands have changed, and traditional platforms can’t keep up.
30
mei
mei
Rapid advancements in artificial intelligence technologies, such as large language models (LLMs), have triggered radical transformation in insurance. While they have already reshaped how AI is used, LLMs alone are not sufficient for real-world decisioning.