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For years, the AI world has been obsessed with one idea: if you make a model bigger, it becomes smarter.More data, more parameters, more compute — repeat. This mindset gave us impressive tools. Chatbots that can write essays, models that generate images from a sentence, assistants that summarize long documents in seconds. Scaling worked… up to a point. But lately, we’re running into a wall. Even the best models still make obvious mistakes. They reason poorly, forget informati

A recent tweet featuring two nearly identical café portraits has reignited a rapidly escalating conversation: we have reached the point where AI-generated imagery is no longer meaningfully distinguishable from real photography.   The post shows a young woman seated at a wooden table, head resting in her palm, with a bartender working in the background. One image was generated by artificial intelligence. The other was a genuine photograph. What makes the tweet so compelling—a

Every time a major entertainment brand announces a new experiment involving generative AI, social media erupts with quick takes, hot opinions, and fears about what comes next. It’s become almost predictable. But outside the noise, something more interesting is happening:the creative industry is entering a transition period where AI isn’t replacing people — it’s expanding what creators and audiences can do. Rather than framing these announcements as a cultural crisis, it’s wor

This time, we’re going deeper. These five meta-techniques aren’t about phrasing or tone — they’re about how to think with AI as a parallel mind. If the last two taught you how to talk to AI, this one teaches you how to reason alongside it. 👇 1. Start with the Tension, Not the Task AI thinks best when it has something to resolve. Don’t say: “Explain creativity.” Say: “Why do people fear creative AI — and are they right?” Tension activates comparative reasoning — the model s

We need to stay critical about AI — not cynical, but realistic. Everywhere you look, AI is being described as the solution to everything — a cure-all for creativity, productivity, even meaning itself. But behind that optimism, there’s a growing problem: false hope. AI is powerful, yes. It can help us work faster, explore new creative ground, and reveal insights we might never have seen on our own. But it’s also imperfect — biased, brittle, and often built on systems that harm

I’ve been running a series of experiments to see how different AI models handle true  macro-scale detail — the kind of extreme close-ups you’d normally need a dedicated lens, controlled lighting rigs, and a patient subject to capture. Insects turned out to be the perfect test. Macro photography pushes every part of an imaging system to its limits. You’re dealing with: ultra-thin depth of field micro-textures and surface inconsistencies reflective and iridescent materials tiny

Lately I’ve been testing Midjourney and Luma AI side by side for video generation — not to compare aesthetics, but to understand how each interprets motion. Both tools are impressive in their own ways. Midjourney is phenomenal at generating cinematic moments — sweeping perspectives, painterly lighting, and fluid motion that feels straight out of a film trailer. It’s so good at this that it’s almost too good. When you ask it to “sit still,” it still wants to move. For example,

Everyone’s talking about the “AI bubble.” Some whisper it. Some shout it. But almost everyone feels it — that uneasy tension between unstoppable hype and uncertain reality. Every week brings another record valuation, another model launch, another promise to “redefine the future.” Yet behind the noise, a quieter anxiety is spreading: is this sustainable? Are we watching history’s next great tech revolution — or simply inflating another bubble destined to pop? The truth lies so

Most people still treat AI like a vending machine: type in a request, get an output. But professionals know that the real power comes from shaping the relationship, not the command. Here’s how to shift from prompting to collaborating 👇 1. Stop Asking — Start Negotiating  AI isn’t a genie. It’s a mirror of your reasoning.  When you ask, “Write me a paragraph,” you get compliance.  When you say, “Let’s explore two tones — bold and conservative,” you get a conversation.  Negoti

When most people talk about “prompt engineering,” they imagine it as a technical skill — choosing the right words to make AI do what you want. But that’s not actually what separates amateurs from professionals. What matters more isn’t what  you say to AI, but how closely its frame of understanding matches yours. That’s called Context Symmetry  — and it’s the real foundation of advanced AI work. The Real Problem Isn’t Bad Prompts — It’s Asymmetrical Context When you ask AI for

A new frontier is emerging in the evolution of artificial intelligence — not smarter algorithms, but more human-seeming ones. These are the systems that smile in text, mimic empathy, recall your past chats, and even apologize when they “hurt your feelings.” They don’t actually feel remorse, curiosity, or affection — but they’re designed so convincingly that many people forget that difference. This phenomenon now has a name among AI ethicists and developers: Seemingly Consciou

I’ve been experimenting with Midjourney to create a short video filled with playful Halloween scenes — animals in costumes, carving pumpkins, and getting into all sorts of autumn mischief. The goal was to explore how generative AI can produce light-hearted, story-driven visuals that feel made for kids’ content — colorful, curious, and full of personality. It’s amazing how AI can turn a simple prompt into a world that feels ready for a children’s book or an animated short. 🦊✨

Most people write prompts like orders. Professionals design contexts — because AI doesn’t just respond to words, it responds to frames of thought. Here’s how to shape that thought process 👇 1️⃣ Frame the AI’s mental model Before asking for output, define how you want the model to think.  You’re not giving it a task — you’re assigning it a mindset. “You’re a senior UX designer mentoring a junior colleague.”  Now it reasons like a teacher, not a typist.  Framing changes how it

Generative AI is changing everything — how we write, design, code, and even think about creativity. But beneath the excitement, there’s a quiet crisis unfolding: the same technology built on the shoulders of open source might end up destroying it. For decades, open source software — known as FOSS, short for “Free and Open Source Software” — has been the invisible engine of the internet. Every time you check your email, stream a show, or use an app, you’re relying on code buil

Most people treat prompting like trial and error — throwing words at a model and hoping for magic. But professionals don’t rely on luck. They use context. In one of my lessons, I unpack three foundational techniques that transform how you communicate with GenAI — so your outputs stop feeling random and start feeling intentional. 📘 1. Priming with Examples Before you ask for an answer, show the model what “good” looks like. By providing a few precise examples, you prime the A

I recently read an article by Sacha Alanoca and Maroussia Lévesque arguing that the US is  regulating AI — just not where we expect it. And yet, as interesting as that is, my gut feeling is that the regulation still isn’t enough . The authors correctly highlight that while a lot of attention is on whether AIs like ChatGPT or image-generators are being checked for bias, misinformation or misuse, the U.S. government has been more active behind the scenes: restricting access to

Understanding Luma’s visual reasoning and how machines “read” emotion without words Most AI visuals begin with language — prompts, modifiers, camera angles, style keywords. But what happens when you remove language entirely? Recently, I gave Luma AI not a prompt, but an image I had already generated — a quiet, surreal scene of a lone figure surrounded by blurred, ghostlike faces. No description. No keywords. Just the raw visual. The original image provided. Luma responded — n

What sets Luma apart isn’t just detail or realism; it’s dynamicity — that sense of physical weight, camera inertia, and believable motion that most AI videos still struggle to achieve. Movements no longer feel stitched together frame-by-frame. They flow. Reflections track naturally as the camera moves. Light shifts in sync with motion. Physics finally feel intuitive — tires bounce, hair ripples, shadows stretch correctly across space. Even in chaotic scenes (say, a squirrel r

Lately, I’ve been revisiting Geoffrey Moore’s Crossing the Chasm , a classic that explains why breakthrough technologies so often stall...

Not long ago, my feed filled with photos of Friend.com ’s  New York subway campaign—bright, minimalist posters for a necklace that...