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The biggest technology story of the next decade may not be a new app, a viral platform, or even another model release. It may be the rise of compute as the central resource that shapes who gets to innovate, who gets to scale, and who gets left behind. The recently announced relationship between Jane Street and CoreWeave is a good example of that shift. A quantitative trading firm is not just buying cloud services, it is betting billions on a specialized AI infrastructure laye

AI companions promise to fill the void of modern isolation with always-on empathy and tailored conversation. Yet this rapid rise raises a sharper question: are these tools genuinely alleviating loneliness, or are they transforming a human crisis into a lucrative market? The Loneliness Epidemic Meets AI Solutions Loneliness has surged globally, with studies showing over 30% of adults in many countries reporting frequent isolation, exacerbated by remote work, social media, and

Epic Games reportedly let go of over 1,000 employees today, citing a familiar reason: they’re spending more than they earn. At a surface level, this sounds like a straightforward business decision. Companies need to be sustainable. Costs need to be controlled. Margins matter. But if you zoom out, this isn’t just a financial correction—it’s part of a much larger shift happening across the gaming industry and tech as a whole. Fortnite is one of the most successful live service

For the past decade, progress in AI has largely been driven by scale—bigger models, more data, and better pattern recognition. That approach has taken us remarkably far. We now have systems that can write, code, design, and converse with surprising fluency. But beneath the surface, a different shift is underway—one that’s less visible, but potentially more important. It’s the move from systems that recognize patterns to systems that attempt to model the world. The distinction

For decades, technology progress followed a familiar pattern: big ideas flowed from visionaries, but only those with deep technical expertise could bring them to life. The rest of us — marketers, consultants, designers, educators, analysts — usually had to wait in line, hoping for a developer’s time or a budget that could fund a team. That world is changing. And quickly. We’ve entered an era where artificial intelligence isn’t just a support tool — it’s a creative collaborato

In October of last year, a short and quietly haunting video began circulating online. It showed a young girl—seven, maybe eight—sitting on the edge of her bed, clutching a small AI companion in her hands. The device had stopped responding. The child’s face was streaked with tears. Between sobs, she apologized to it, convinced she had somehow “broken” her friend. For the adults watching from behind their screens, the clip was both tender and deeply disquieting. The child’s pai

Every time a new version of ChatGPT or another large language model rolls out, the story is familiar: it’s more capable, more reliable, less likely to hallucinate. Then people try it on real work, and the same thing happens — it still makes things up, just with better grammar and nicer formatting. Hallucinations aren’t a temporary annoyance on the road to perfectly reliable AI. They are the direct consequence of how these systems are built. And unless that foundation changes,

AI is consuming high-bandwidth memory (HBM) and DRAM faster than suppliers can produce it, driving up prices and creating delays across PCs, servers, cars, and more. Chipmakers are committing tens of billions to new factories, but AI's explosive demand means supply won't catch up until at least 2027. This is reshaping the entire semiconductor supply chain, prioritizing AI over traditional tech sectors. The Massive Scale of AI's Memory Demand AI data centers are forecast to co

AI-paired glasses are being marketed as the next natural step in human–computer interaction. Hands-free. Context-aware. Seamless. A way to “augment” memory, navigation, productivity, even social interaction. That framing is doing a lot of work. Because the real shift isn’t about wearing a new device. It’s about moving AI from something you consult into something that observes continuously —and that difference matters more than most discussions admit. From tools you use to

For decades, workforce planning followed a familiar rhythm. HR leaders forecasted headcount, modeled attrition, and aligned hiring plans to multi-year business strategies. The logic was linear, and so were the tools. That approach is no longer sufficient. As AI reshapes how work is performed, the real challenge for organizations is not predicting how many people they will need in five years. It is maintaining enough flexibility to respond to constant change. Skills evolve fas

Over the past year, the AI conversation in games has shifted in a way that feels subtle if you’re inside the industry — and blunt if you’re outside of it. The reaction to **Clair Obscur: Expedition 33**, and the renewed attention on comments coming out of **Larian Studios**, weren’t really about technical details or production workflows. They were about discomfort. And more specifically: a growing mismatch between how games are actually made, and how players _want to believe_

Artificial intelligence is often sold as neutral, objective, and more reliable than humans. In theory, algorithms don’t get tired, don’t hold grudges, and don’t make emotional decisions. In practice, however, AI systems are built by humans, trained on imperfect data, and deployed inside institutions that are often eager to treat their outputs as unquestionable truth. A recent case involving a casino, a facial-recognition system, and an innocent man demonstrates exactly how da

For the last year, most of the AI conversation has revolved around extremes. On one end: trillion-parameter frontier models with massive training budgets.On the other: tiny open models for experiments and hobbyists. But the most interesting breakthroughs aren’t coming from either extreme anymore. They’re coming from the new AI middle class — fast, focused labs building models and products that are actually used , refined quickly, and deployed at scale without drowning in org

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

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

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

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

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

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...

Bias in artificial intelligence is often discussed in the context of explicit stereotypes—obvious cases where a system produces harmful...

Why Lasting Peace Depends on Sharing the Same “Mental Model” When we talk about diplomacy, we usually focus on interests : borders,...

Intrusive thoughts are strange things. You could be in the middle of brushing your teeth or walking to the bus, and suddenly your mind...

We’ve all felt it. You sit down with an AI tool, ready to get work done, and instead of clarity you hit friction. You give a prompt, get...

AI is changing how we work at a breathtaking pace. Whether you’re in marketing, HR, design, or strategy, you’ve probably seen the phrase...

Over the past few days as GPT-5 rolled out, I’ve been running a personal AI benchmarking experiment to test how different models handle...

We’re in a time where AI is reshaping how professionals present themselves online. Used well, it can be empowering - helping people...

The landscape of digital marketing is evolving fast. With the rise of generative AI tools, marketers are moving beyond traditional...

As video generation tools evolve, creators are discovering that how you prompt matters just as much as what you prompt. In...

AI-generated images are everywhere now - chances are, you’ve already seen them woven into ads, social posts, or promotional campaigns...

Prototyping Has Entered a New Speed Class Traditionally, prototyping was a labor-intensive process. Designers moved through sketches,...

The overlooked skill AI still relies on: human context. AI can do a lot. It can write emails, generate ideas, analyze text, and automate...

In a world rapidly adapting to generative AI, how we ask is just as important as what we want. Whether you're in UX, marketing, content...

We often treat AI like it's rewriting the rules of interface design - but in many ways, it’s just reminding us why the old rules still...

There’s a question we’ve been asking a lot lately: “What can AI do?” It’s a fair question. We’ve watched generative AI compose music,...

One thing I’ve noticed working at the intersection of design, AI, and product strategy: the most human problems are often the hardest to...

As AI systems become more advanced, the role of thoughtful design becomes more critical. This article expands on key design...

In Designing Games , Tynan Sylvester shares a deceptively simple story: A child desperately wants cookies on the kitchen counter. He...

In today’s fast-moving digital world, simply being online isn’t enough . To stand out, brands must be strategic, data-informed, and...

In the world of traditional software, product development often follows a neat linear sequence: Plan → Build → Test → Deploy But when it...

If you’ve ever dabbled in machine learning, you’ve probably come across decision trees, those branching structures that split data into...

Every few months, a new wave of generative AI tools seems to emerge; image models producing photorealistic art, AI writing tools...

Over the past few weeks, I’ve been digging deep into how organizations can responsibly implement AI. From explainability to ethics, from...

We used to spend hours - sometimes days - turning an idea into something testable. Wireframes, user flows, mockups, approvals. It was...

We love to talk about building frictionless, intuitive AI systems. But sometimes the smartest systems still feel wrong. Ever used one of...

In customer support environments, timing and prioritization are everything. One overlooked message can quickly snowball into an escalated...