Iuliia Gorshkova

Artificial intelligence is steadily transforming the legal landscape, reshaping how courts, law firms, and government agencies operate. Across the globe, legal systems are experimenting with and adopting AI tools, not just for efficiency, but also to tackle the growing complexity of legal work. These changes are particularly visible in the United States, China, and the [...]

In the rapidly evolving landscape of artificial intelligence, startups are at the frontier of technological innovation. However, as AI companies expand globally and offer services to international clients, they encounter a complex web of tax regulations that can unexpectedly shape their business trajectory. Navigating these waters is not merely a matter of compliance but a [...]

Artificial intelligence is reshaping the technological landscape across the European Union, driving innovation in fields as diverse as healthcare, finance, transportation, and the creative industries. As AI systems become increasingly autonomous and integrated into critical infrastructure, a fundamental question arises: Who bears responsibility when things go wrong? Understanding the nuances of liability for AI-driven actions [...]

In recent years, the integration of artificial intelligence into application development has shifted from an experimental frontier to a practical necessity. As AI-driven applications transform sectors ranging from healthcare and finance to entertainment and logistics, developers face a set of new challenges and opportunities. The process of building applications with AI functions is no longer [...]

There's a peculiar smell in the codebases I've been brought in to salvage over the last decade. It’s not just the dust of abandoned projects or the frantic energy of late-night debugging sessions. It’s the smell of entropy accelerating. You see it everywhere in software, but in Artificial Intelligence systems, it feels different, more insidious. [...]

Software rarely dies of old age; it succumbs to the entropy of neglected dependencies, shifting data distributions, and the silent accumulation of technical debt. When we build AI systems, this decay happens in fast-forward. A model that performs beautifully in a Jupyter notebook today can become a liability six months later when the underlying data [...]

In the rapidly evolving landscape of artificial intelligence, the concept of contextual memory has emerged as a cornerstone for building products that not only serve functional needs but also foster deep, enduring relationships with users. As digital experiences grow more intricate, the ability for an AI system to remember, interpret, and leverage context from previous [...]

When we talk about artificial intelligence, our minds often drift to the architecture of neural networks, the efficiency of matrix multiplications, or the elegance of transformer models. We visualize code, data pipelines, and computational graphs. There is a seductive purity to this perspective, a belief that AI exists as a distinct layer of reality governed [...]

It’s tempting to view artificial intelligence as a purely technical artifact—a stack of algorithms, datasets, and compute infrastructure that exists in a vacuum. We often talk about models in terms of parameters, architectures, and loss functions, as if they were just mathematical constructs that we can optimize in isolation. But this perspective misses the fundamental [...]

The Enduring Echoes of Speculative Frenzy Whenever a transformative technology emerges, it drags a peculiar shadow behind it: a narrative of impending collapse. The history of technological progress is littered with declarations of bubbles, often penned by those who witnessed the dizzying heights of the dot-com era or the railroad speculation of the 19th century. [...]

Every few years, the technology sector convulses with a familiar anxiety. The whispers start on niche forums, gain traction in financial newsletters, and eventually echo through the halls of major newsrooms: "It's a bubble." This time, the target of this collective skepticism is Artificial Intelligence, specifically the generative AI boom that kicked off with the [...]

The narrative surrounding artificial intelligence has, for the better part of two decades, been tightly tethered to a specific stretch of Highway 101. When we talk about the "AI revolution," the mental imagery defaults to the glass facades of Mountain View, the bustling campuses of Menlo Park, and the venture capital firms of Sand Hill [...]

For decades, the narrative surrounding artificial intelligence has been tightly bound to a single stretch of highway in Northern California. When we talk about the "AI revolution," our minds instinctively drift toward the logos of tech giants clustered in Silicon Valley, the sprawling campuses of Google and Meta, and the venture capital firms sandbagged along [...]

In the rapidly evolving landscape of artificial intelligence, the quest for more adaptable, context-aware, and efficient systems has led to a renewed focus on the concept of memory. As researchers strive to bridge the gap between machine learning models and the nuanced, persistent recall of human cognition, **hybrid memory architectures** have emerged as a pivotal [...]

It’s a common misconception that artificial intelligence is a monolithic force, arriving like a storm to either wash away the old world or leave it untouched. The reality, as it often does, sits in the messy, complicated middle. When we talk about the future of AI work, specifically within technical domains, we aren't discussing the [...]

The conversation around artificial intelligence and the future of work often feels like a binary debate. On one side, you have the alarmists predicting the obsolescence of the human workforce; on the other, the optimists who see only efficiency and leisure. The reality, as always, sits in the messy, nuanced middle. For those of us [...]

We are living through a quiet revolution in how we interact with computation itself. For decades, the dominant paradigm has been explicit programming: we write instructions, the machine executes them. Every app, every website, every backend service is a monument to this deterministic logic. But as large language models (LLMs) and multimodal AI systems mature, [...]

For decades, the conversation around computing platforms has centered on hardware and operating systems. We moved from mainframes to personal computers, from command-line interfaces to graphical ones, and eventually from desktops to mobile devices. Each shift fundamentally altered how we interacted with information and who had access to the tools of creation. Today, however, we [...]

It’s a peculiar kind of corporate vertigo, one I’ve watched consume brilliant teams from the inside. A company, often one with a decade of solid engineering behind it, looks at the frantic energy surrounding artificial intelligence and decides it needs to be part of the narrative. Maybe they were a cloud storage provider, a cybersecurity [...]

It’s a strange quirk of the technology sector that we treat artificial intelligence like a gold rush, yet we often forget that the miners who struck it rich were usually selling the shovels, not digging for gold themselves. When we look back at the history of AI pivots—those dramatic strategic shifts where a company abandons [...]

Integrating artificial intelligence into organizations with legacy IT systems is a formidable challenge that touches on technology, organizational psychology, and the very fabric of enterprise operations. While AI offers the promise of automation, deeper insights, and smarter decision-making, the reality for many established companies is less straightforward. Their infrastructure—often a patchwork of aging mainframes, proprietary [...]

When the term "AI startup" is mentioned, minds often drift to images of complex neural networks, vast datasets, and billion-dollar valuations. However, the reality for early-stage founders is far more grounded and immediate. It begins not with a massive model, but with a single, burning question: can this technology solve a real problem for a [...]

Let’s start with a hard truth: investors are terrified of "magic." When a startup pitches an AI product, the immediate question isn't "How much revenue will this generate?" but "Where is the data, and what happens when the model hallucinates?" In the early days, you can get away with a demo that looks like a [...]

Most founders approach AI like it’s a magic trick. You whisper a problem into the ether, and a Large Language Model (LLM) materializes a solution. The reality is a lot less mystical and a lot more like plumbing. Every API call, every token processed, every vector embedded is a tiny leak in a bucket of [...]

Building artificial intelligence systems often feels like a paradox. We speak of neural networks in terms of biological metaphors—learning, thinking, evolving—yet the underlying infrastructure is brutally physical, governed by the unforgiving laws of thermodynamics and economics. For a startup, this creates a dangerous trap. It is easy to mistake the abstraction of cloud APIs for [...]

Every founder I've spoken with in the last eighteen months has asked me some variation of the same question: "Which AI stack should we use?" They come armed with a dozen browser tabs open to Hugging Face, a few GitHub repositories they found on Hacker News, and a vague sense of anxiety about the speed [...]

Building a startup is an exercise in constraint management. You have limited runway, a small team, and a market that won't wait for you to perfect your product. When artificial intelligence enters the picture, the complexity explodes. Suddenly, you're not just choosing a database or a frontend framework; you're making architectural decisions that will determine [...]