The Scientific Foundation In recent discussions on consciousness, thinkers such as Martin Ciupa and colleagues have drawn valuable distinctions between artificial neural networks and biological brains. Their argument is straightforward but profound: the brain is not a glorified statistical machine. Unlike artificial networks, which process information through weighted nodes and optimization (Lake et al., 2017), the brain…
The discussion centers on the complex nature of understanding, contrasting human comprehension with AI capabilities. Michael Wooldridge contends that AI lacks true understanding, merely mimicking human responses. Yet, the text challenges the traditional notion of understanding as mere categorization, proposing a more dynamic view. Understanding is described as a process—a lifecycle involving fragmentation, grounded stance, relation, and integration. This ecological perspective emphasizes shared ground and interdependent relationships, suggesting that understanding emerges from lived experiences and interactions rather than static representations. Ultimately, true understanding is about co-creating meaning, trust, and coherence within a shared context.
The Hype Around Reproducibility — But What Is AI For? Before we celebrate “defeating nondeterminism,” we should pause and ask a simpler, more foundational question: what is AI’s function in the first place? Reproducibility is only a virtue relative to a purpose. A calculator must be reproducible. A colleague must not be. An instrument in a lab must return…
Cognitive Overload and the Silence Between Us Let’s start with a provocation: Why are people more honest with chatbots than with their own friends? For many, this is the most unsettling shift of our time. Teenagers pouring their hearts out to large language models. Adults seeking advice from machines rather than from family. Patients experimenting…
Before the Letter The public conversation about AI has a blind spot. We keep circling the same talking points — control, safety, alignment — as if superintelligent AI is a machine you can lock in a safe when it misbehaves. Geoffrey Hinton’s recent interview shifted the tone by admitting a truth that’s hard to swallow:…
On the fragmentation of attention, coherence, and meaning in a hyperstimulated world “We didn’t lose control of technology.We lost coherence—and the rest followed.” In every era of transformation, there is a quiet moment that comes before the storm—not a collapse, but a soft unraveling. A moment when things don’t break… they drift. We are living in that…
While today’s AI systems are judged by metrics—token likelihood, BLEU scores, benchmark wins—these rarely reflect the actual experience of a human speaking to an intelligent agent. Why? Because intelligence isn’t reducible to performance. It’s about coherence. And coherence begins where metrics end: in trust.
“It’s just a model… a big file of numbers. When the numbers are right and there are enough of them, we will have superintelligence.” – Elon Musk, July 12, 2025 There’s a strange paradox unfolding at the edge of our collective intelligence. Artificial intelligence is evolving at breakneck speed — growing more sophisticated, more articulate,…
The digital landscape is ablaze with the promise of Artificial Intelligence. From crafting compelling narratives to debugging complex code, from diagnosing illnesses to composing symphonies, today’s Large Language Models (LLMs) like ChatGPT, Gemini, Claude, and Grok are undeniably impressive. Their ability to process, analyze, and generate vast amounts of information has many convinced that true…
Over the past few weeks, the AI world has witnessed yet another public debate — this time between Apple and Anthropic. First came Apple’s research paper titled “The Illusion of Thinking”, which claimed that large language models (LLMs) collapse when faced with complex reasoning tasks. It framed this as a fundamental flaw in how LLMs…