generative ai examples

AI's Deep Dive: Redefining Art, Embodiment, and Human Creativity

The classic science fiction film 2001: A Space Odyssey offers a potent thought experiment on the nature of intelligence. When the AI, HAL 9000, is shut down, it appears to "die." This scene, when re-examined, challenges our very assumptions about what it means to be alive and to possess knowledge. N. Katherine Hayles, a prominent theorist, argues that information acquisition and knowledge are deeply tied to a physical form — a human body. However, the rise of advanced machine learning pushes us to consider disembodiment beyond this human-centric view.

From Factories to Features: AI's Impact on Labor, Art, and Memory

The AI Shift: Redefining Labor, Art, and Our Place in the World

Stepping into an art gallery, imagine encountering a robot that hums softly, gliding along walls to draw vertical lines. These lines change in size, growing longer when more people are in the room. This isn't just a quirky art piece; it's Sabrina Raaf’s "Translator II: Grower" (2004–2006), an automated robot that records carbon dioxide levels, transforming environmental data into green and brown "grass fields." It’s a powerful, subtle commentary on our relationship with nature and the evolving definition of human labor, especially as artificial intelligence and machine learning increasingly shape our world.

How Generative AI is Changing Business and What's Coming Next

When most of us hear about artificial intelligence, our minds immediately jump to ChatGPT. It’s become the face of conversational AI, but the landscape of what is generative AI is far broader and more competitive than a single tool. Models are now being used across countless industries to boost productivity, cut costs, and totally reimagine the customer experience. But it's not just about the big names; emerging players like DeepSeek are proving that powerful AI doesn't have to come from the usual tech giants, offering a glimpse into a more accessible and diverse AI future.

How We See the World Shapes How We Build It

We all have mental models we use to make sense of the world, whether we realize it or not. These "logics" are the lenses through which we observe, reason, and make decisions. They’re incredibly powerful because they operate in the background, shaping our understanding of everything from personal relationships to global economies.

Why AI Demands a New Blueprint for Your Business

It’s no secret that artificial intelligence is changing the game. Whether it’s through automation that handles repetitive tasks or augmentation that gives human workers superpowers, AI is fundamentally lowering the cost of delivering better service on a massive scale. This means more people, everywhere, can get affordable access to innovative services. To really understand this shift, it's crucial to look at how different types of AI are being applied today. We’re seeing a surge in generative AI for business, with countless high-skill, high-paying jobs now focused on creating new AI use cases to drive a return on investment.

Why Marketers Struggle With AI (And a Simple Way to Understand It)

Just think about the names: Tesla, Spotify, Netflix, Slack. The pace of technology over the last 20 years has been staggering. Now, try to imagine that speed of change multiplied by ten, twenty, or even a hundred. That’s the challenge AI presents. It’s putting the velocity of change into hyperdrive.

The Hard Questions We're Not Asking About AI

When most of us try to answer the question, what is AI, we often picture the powerful tools we interact with daily. The conversation quickly turns to generative AI models that can write, create images, and analyze data at incredible speeds. But to truly understand what is generative AI, we have to look beyond the impressive capabilities and confront the serious ethical questions that come with it. As this technology becomes more woven into our lives, it’s creating complex challenges that we can’t afford to ignore.

Who's Responsible When an AI Gets It Wrong?

Artificial intelligence is no longer the stuff of science fiction; it’s quietly integrating into the fabric of our society. From the algorithms that suggest what to watch next to complex systems aiding in medical research, AI is reshaping our world. But this wave of innovation brings a critical question to the forefront: what happens when these systems make a mistake? The promise of a more efficient, data-driven future is shadowed by the risk of privacy invasion, baked-in bias, and ethical dilemmas we’re only just beginning to confront.