Author: Carter

There’s a truly invigorating quality to collaborating with startups — something I’ve been deeply immersed in for over two years now. Startups function at a distinct pace: the sense of urgency is palpable, resources are limited, and the outcomes feel deeply personal. Guiding them through the process of validating their business model demands not only technical expertise but also a readiness to act swiftly, question established assumptions, and commit to architectural decisions even when the ideal data isn’t yet available. What excites me most is that the work is always tangible: every recommendation I provide to a startup directly influences…

The European Commission forecasts that 91% of enterprise workloads will shift to the cloud by 2028, signalling that the continent is prepared to operate at scale. The more compelling topic – the one uniting cloud architects, cybersecurity executives and enterprise buyers at GITEX AI EUROPE in Berlin this year – is not whether enterprises ought to migrate, but how to establish independence, and under what conditions. GITEX AI EUROPE runs from 30 June to 1 July 2026 at Messe Berlin, drawing over 800 enterprises and startups, 500 investors and 120 speakers from more than 100 countries – making it one…

However, this model works both ways. On the positive side, it enables businesses to attract funding by riding market enthusiasm. On the downside, it locks them into absorbing the swings of the underlying asset whenever prices drop.For a publicly traded company, the challenges are even more pronounced. Accounting rules require financial setbacks to be disclosed promptly, and any asset movements under such circumstances draw heavy scrutiny.The ongoing debate around Trump Media & Technology Group (TMTG) illustrates this perfectly. Facing paper losses on its crypto strategy, the company transferred 2,650 BTC to Crypto.com, after pulling its applications to launch its own…

Ravie LakshmananMay 25, 2026Cybersecurity / Hacking Monday roundup. Same chaos, fresh week. A shady developer tool led to compromises, long-dormant vulnerabilities resurfaced, and even security tools turned out to need protection from themselves. Plenty of organizations spent the week auditing legacy systems and neglected servers that should have been updated ages ago. Classic. Phishing operations are leveling up as well — fewer clumsy scam attempts, more carefully crafted campaigns that genuinely look legitimate. At the same time, botnets are scooping up every internet-exposed asset they can find like it’s going out of style. The web remains a hot mess. Here’s…

In this installment of my data engineering series, I laid out a 12-month plan for moving from data analyst to data engineer. Now, it’s time to start creating. When I put out my initial piece about learning data engineering, the reaction surprised me. It struck a chord with readers. I received messages from people I didn’t know, eager to join the ride. It was encouraging. It also brought a sense of obligation. This was no longer a private ambition I could quietly drop if the going got tough. Others were paying attention. Others were facing similar challenges. That sense of…

# Introduction Whether you’re working with traditional classifiers or cutting-edge models like large language models (LLMs), a persistent challenge in building machine learning systems is the risk that algorithms quietly absorb biases present in the historical data used for training. But in high-stakes or data-sensitive situations, how can you check whether a model is biased without exposing real personal information? This practical guide walks you through training a basic “loan approval” classifier using intentionally biased data. From there, we’ll leverage Mimesis, an open-source library for generating perfectly balanced, counterfactual datasets. You’ll learn to create “fake” applicants who share identical financial…

Looking at the content, I can see this is an article about Kubernetes governance and policy-as-code. Let me rewrite it for better readability while keeping all HTML structure identical. I notice the last heading is cut off (`Practical guidance for platform teams`). I’ll rewrite the content up to that point. — Posted on May 25, 2026 by Sajal Nigam, CNCF Community Member CNCF projects highlighted in this post Kubernetes has evolved into the foundation of today’s cloud-native infrastructure. Its adaptability enables teams to iterate rapidly, assemble intricate systems from independent components, and deploy seamlessly across diverse environments. However, that same…

Summer is just around the corner, bringing with it prime opportunities to snag laptops at reduced prices as retailers clear out existing stock. We’re monitoring some of the most compelling Memorial Day sales right now, with markdowns on MacBooks, Chromebooks, and PCs from Lenovo, Asus, HP, and others.Also: My top Memorial Day picks: Major savings on laptops, tablets, and moreWe only highlight products we’ve personally tested or would genuinely consider purchasing ourselves, prioritizing meaningful price reductions. After assessing key hardware specifications — including processors, memory, and storage — we evaluate build quality, design, intended usage, and above all, how the…

During the early stages of factory layout design, discrete event simulation and digital twin technology are essential tools. Source: Visual Components As more manufacturers adopt virtual tools, the aim goes beyond mere visualization. The real objective is to understand, test, and refine processes long before they hit the production floor. Although simulation and digital twin technologies are now key pillars of digital transformation, many manufacturers still struggle to tell them apart when considering virtual solutions for their operations. Understanding these differences—and knowing where each technology fits within the system design, planning, and operational lifecycle—is essential for making smart decisions that…

“Beauty will save the world” — Fyodor Dostoevsky A. Introduction Modern AI didn’t appear out of nowhere. Today’s transformer-based tools can seem almost magical, able to grasp context and even the subtle connections between concepts. However, the roots of today’s semantic search technology developed slowly over time. Long before embeddings, transformers, and large language models existed, researchers relied on keyword matching, TF–IDF vectors, and conventional machine learning techniques to process text. Many of those early approaches never really went away. In reality, current systems still draw on ideas that were created decades ago. The discipline advanced step by step, with…