artificial intelligence•
What 81,000 People Want from Artificial Intelligence
The largest qualitative study ever conducted: Anthropic interviews half the world to understand real hopes, fears, and expectations about AI.
AI Philosophy
Intelligence, creativity, agency, limits, and the human dimensions of artificial intelligence explored without hype.
25 Articles•Updated regularly
Server•
The Invisible Highways of AI
Why Data Centers are the True Strategic Infrastructure of the 21st Century
Design•
Goodbye to design: websites will become blank pages
Artificial intelligence is changing the way we search for information while eliminating the aesthetic experience of the web. For this reason, I believe we will unfortunately replace websites with empty text fields.
architecture•
Software Architectures for Artificial Intelligence Systems
Artificial intelligence approached with scientific rigor, engineering precision, and human depth.
AI•
2026: The Year of Artificial Intelligence Consolidation
The Global AI Report by NTT DATA reveals a clear picture: experimentation gives way to the creation of measurable value.
dead internet•
The dead internet is becoming a reality
If half of web traffic is generated by bots and content is produced en masse by AI, those working with artificial intelligence have only one path: to stand out from the noise.
local-ai•
Surviving an AI bubble burst: A developer’s Local AI survival kit
What happens when your favorite AI coding assistant disappears overnight?
AI•
AI and Digital Forensics
Digital forensics increasingly integrates artificial intelligence to automate the analysis of large volumes of data, enhancing the speed and effectiveness of investigations on texts, audio, images, videos, malware, and IoT devices.
2025•
Merry AI Christmas
2025, the year that redefined artificial intelligence.
AI•
Frozen in time
What if a superintelligent coding AI had emerged in 2012 and declared jQuery and PHP “good enough” for all time? In this alternate history, the web never evolves. No React, no component paradigms, no open-source renaissance: only a perfect stagnation masked by machine efficiency. This essay explores how AI, when trained only to imitate the past, can freeze the future. And it asks a chilling question: what if that future isn’t fiction, but our present unfolding in slow motion?
AI•
The Deception of "Necessary Fatigue"
Between ideological rejection and blind automation, the real distinction lies in directing technology instead of being replaced: history, method, and awareness in the use of artificial intelligence.
LLM•
Self-Attention: why the idea of "stochastic parrots" no longer holds up
A technical analysis of why the self-attention architecture makes modern LLMs much more than mere "stochastic parrots."
AI•
If Europe Does Not Develop AI: What Lies Behind Mario Draghi's Warning
Draghi's warning about European stagnation concerns not only the number of artificial intelligence models developed but also the very structure of the economy and how we use (or do not use) AI in production processes.
AI•
It's time to talk about non-linguistic AI models.
Why the real productive revolution does not come from LLMs.
LLM. AI•
The Unspoken Challenges of LLMs in Production
Why reliability, not capability, becomes the ultimate bottleneck when AI meets the real world.
AI•
Building Private AI Systems: Why On-Premise Solutions Matter
Exploring the critical importance of private AI infrastructure for organizations requiring absolute control, performance, and intellectual property ownership.
AI Agents•
Autonomous AI Agents: The Maestro Architecture Revolution
How orchestrated AI agents are transforming complex problem-solving through coordinated autonomy and specialized capabilities.
AI•
Training AI Without Data: Rethinking Supervision
Most organizations don't have labeled datasets. They have processes, constraints, and domain expertise. Here's how to build AI systems that learn from structure, not just examples.
AI Philosophy•
What Makes Intelligence Intelligent?
Beyond pattern matching and statistical correlation—exploring what distinguishes true intelligence from sophisticated computation, and why the question matters for how we build AI.
Education•
Teaching AI, Not Using It
Why my students implement backpropagation by hand, build neural networks from NumPy, and learn to architect systems instead of calling APIs.
Applied AI•
Edge AI in Industrial Automation: Bringing Intelligence to the Factory Floor
Why industrial automation demands AI that runs on-premise, operates without internet connectivity, and makes millisecond decisions in environments where downtime costs millions.
AI Architecture•
Model Collapse and the Problem of Forgetting
When AI systems trained on AI-generated content degrade over time, losing diversity and capability. Understanding the mechanics of model collapse and architectural solutions that preserve knowledge.
Private AI•
RAG Systems Beyond Vector Search
Building Retrieval-Augmented Generation systems that actually understand your organization's knowledge, not just find semantically similar text snippets.
AI Philosophy•
AI, Creativity, and the Role of Constraints
Creativity doesn't emerge from unlimited freedom—it emerges from intelligent navigation of constraints. What this means for building AI systems that generate novel solutions.
AI Architecture•
Optimization Landscapes and Why Neural Networks Train at All
The loss landscape of deep networks is high-dimensional, non-convex, and full of local minima. Yet gradient descent finds good solutions anyway. Understanding why reveals fundamental insights about deep learning.
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