Archives

El PM2.5 es el gran éxito de la ciencia regulatoria del aire. La última Review de The Lancet sobre humo de incendios forestales muestra por qué ya no basta para contar toda la historia.

Cuando alguien critica a la IA por ser opaca, quizá olvida que Newton tampoco sabía por qué F = ma.

La ética de la IA en salud tiene un sesgo geográfico profundo. Europa y EE.UU. concentran más del 60% de los documentos de gobernanza. América Latina, África y Oceanía juntas no alcanzan el 4.5%.

A structural perspective on why AI fear has less to do with algorithms and more to do with power, ownership, and economic control.

A bilingual reflection based on Davide Castelvecchi’s 2016 Nature article, exploring the epistemological challenge of trusting machines we can’t fully understand.

From hyperplanes to neural networks, a reflection on why some of the most powerful AI models remain opaque to human comprehension.

A reflection on why the stochastic nature of LLMs does not make their output probabilistic — and why developers must learn to read, not just generate, code.

Why confusing AlphaFold with an LLM is misleading: it doesn’t predict text, it solves the 3D puzzle of biology

A real-world reflection on why AI struggles with messy business tasks like invoicing but succeeds in highly controlled environments such as robotic surgery

Reflections inspired by Jonathan Birch on the illusion of consciousness in AI, its social implications, and the real possibility of non-human consciousness.

7 core tasks that bioinformatics really performs in research centers like IFC-UNAM

Personal notes on how to get started with bioinformatics coding, including tools, learning resources, and practical entry points for genomic data analysis.

From the elegance of Crick’s Central Dogma to the digital revolution in biology, why information may be the final key to understanding life.

Exploring how physics and biology intertwine, inspired by the 2024 Nobel Prize in Physics.

Exploring the 5 key challenges of applying AI to the life sciences.

Behind Johns Hopkins' breakthrough surgical bot lies a brilliantly literal naming convention. Let's dissect why SRT-H isn't just random alphabet soup.

Johns Hopkins and Stanford just pulled off something remarkable: an AI-guided surgical robot that autonomously extracted bile ducts. Here's why this changes everything.

How we used Random Forest and permutation importance to increase business value in churn prediction

Development of a machine learning model to detect phishing websites using supervised classification techniques.

How Chile’s socialist government tried to reinvent economic planning using cybernetics—and why its legacy still matters.

AI-generated images flood our feeds, but they’re built on uncredited, uncompensated creative labor. Are artists being erased?

A post about the metaphorical and literal senses of distance.

A simple Python project for managing prioritized tasks.

A personal reflection on finishing Beazley’s advanced Python course — and how it changed the way I code and reason.

Bringing together coroutines, async logic, exceptions, and object-oriented design to solve a final puzzle from Beazley’s course.

From coroutines to communication — implementing a protocol for asynchronous message handling using asyncio.

How to compose coroutines using yield from and return values from generator pipelines.

How generators and coroutines enable lightweight, cooperative concurrency by yielding control in Python.

A closer look at how exceptions propagate through the call stack and how to read and use Python’s stack traces effectively.

How to craft your own exceptions and manage failure gracefully using Python's exception system.

Understanding how context managers work under the hood — and how to build your own using __enter__ and __exit__.

Reinventing the stack data structure in Python to understand object-oriented design and control flow.

A hands-on introduction to coroutines in Python using send(), yield, and the power of interactive pipelines.

Learn how to refactor procedural code into a clean, lazy-processing pipeline using Python generators.

From raw CSV files to structured reports — building a simple financial data pipeline using Python, inspired by David Beazley’s course.

Reflections on taking an advanced Python course with David Beazley — and how it reshaped my understanding of the language.

From understanding the CSV format to converting, reading, and downloading files using Python. A complete beginner-friendly guide.