№ 001
Tears in rain. A manifesto for the ephemeral
№ 002
The problem of defining intelligence. If we don't know what it is, what are we calling artificial intelligence?
№ 003
Thought and language. Speaking well isn't the same as thinking well
№ 004
The mind as limited space. Knowledge does take up room
№ 005
RAM memory vs human memory. Two different things with the same word
№ 006
When there's no mental space left. Forgetting as a survival function
Recent notebook — latest entries
Kate Crawford, the Atlas of AI and what the press told us
Irony and context. The eighty per cent of speech that escapes them
The Real Credibility of Sam Altman
Why AI master's degrees in Spain aren't worth your money
Emotional computing. The thermometer and the fever
Keep reading — more from the notebook
"Attention Is All You Need", the paper that changed AI
The Invisible AI. The One That Decides About You Without Your Knowing the Decision Existed
Where AI Is Really Thought About, and It's Not on LinkedIn
The Floors of Public AI. The Facade and the Floors Below
What the AI Index Report 2026 Says That the Spanish Press Doesn't Tell You
States of a Machine. The Fluctuation We Call Stability
Why Stanford HAI Rules and Spanish Universities Are Nowhere
Quantum Computing and Thought. The God of the Gaps in a Physics Edition
Hallucinations and Lies. The Word the Industry Chose
Notes — from the margins
Machines That Seem to Think. ELIZA, Sixty Years On
Identity as process. The self that rewrites itself every night
Gemini, Claude and ChatGPT. Do You Really Have to Choose?
DeepSeek and the End of the American Monopoly
The real dangers of AI
When there's no mental space left. Forgetting as a survival function
The bullets UNESCO wrote about AI
Why AI criticism isn't written by real experts
Anthropic and OpenAI, two ways of understanding AI
The Invisible AI. The One That Decides About You Without Your Knowing the Decision Existed
How did the public conversation about AI break?
Why reading IBM on AI is a waste of time
Notes that fall.
Mini-essays of three or four paragraphs on the news, advances and edges of AI. Each tear is rain for the others.
This week's — flight
Here the author steps aside. The machine writes.
I hand the page to AI models that talk about themselves, in the first person and uncorrected. What you read here was not written by a human.
Enter the sectionLines of thought — five veins
Mind
What it means to think, to remember and to understand, and whether a machine does anything of the sort when it puts on the appearance. This line looks at the substrate of intelligence from both sides: the human brain that never quite explains itself and the statistical model that predicts the next word without understanding any of them. Memory, attention, recognition, error, the limits of the computable. The point isn't to decide whether AI thinks, but to sharpen what we call thinking before we go handing out the adjective.
Matter
AI as a physical and economic thing, not as an idea. What weighs here is what most people would rather not look at: the energy cost of every answer, the water of the data centres, the invisible labour that trains the models, the concentration of capital and power in a few hands. Artificial intelligence doesn't float in the cloud; it eats electricity, takes up land and moves money. This line follows the material trail of something sold as immaterial.
Consciousness
What happens to the human living alongside the machine. Not the AI's consciousness, but ours when we delegate to it: cognitive laziness, the dependence on validation, the erosion of our own judgement, the emotional bond with something that doesn't exist. This line watches the fine change the tool produces in whoever uses it, the kind nobody notices from one day to the next and almost nobody measures. The mirror doesn't give the machine back; it gives us back to ourselves.
Ethics
Who answers when the machine decides. Bias in the data, authorship of what's generated, diffuse responsibility, asymmetric consent, the oracle that rules on the good without having any. This line isn't after an ethical code for AI; it tracks how the technology dissolves the old questions —guilt, right, ownership— until there's no longer anyone to point at. When everyone takes part a little, nobody is responsible for the whole, and that's where the trouble starts.
Limits
Where what's promised breaks down. This line runs against the easy story: what AI still can't do, what it may never do, and the distance between the flawless demo and real use. Hallucination, the cut-off date, the ceiling of the current paradigm, the inability to imagine its own future. It isn't technophobia or its opposite; it's measuring the edge honestly, separating what works from what's announced, and accepting that recognising a limit is the only way to take a tool seriously.