Akin's Laws of Spacecraft Design

101 Things I Learned in Engineering School

In this unique primer, an experienced civil engineer and instructor presents the physics and fundamentals that underlie the many fields of engineering. Far from a dry, nuts-and-bolts exposition, however, 101 THINGS I LEARNED® IN ENGINEERING SCHOOL probes real-world examples to show how the engine...

The Winning Variant

A/B testing, algorithmic optimization, and the small act of ignoring both — and what it means to make something by hand when a number can tell you what would have worked better.

Logic for Programmers

Practical math for the working programmer.

Mathematical methods and human thought in the age of AI

Artificial intelligence (AI) is the name popularly given to a broad spectrum of computer tools designed to perform increasingly complex cognitive tasks, including many that used to solely be the...

Volume 384 Issue 2320 | Philosophical Transactions of the Royal Society A | The Royal Society

Influential themed journal issues across the physical mathematical and engineering sciences.

The case for a validity layer in life science research

When OpenAI recently announced that one of its models had disproved a long-standing conjecture in discrete geometry, the scientific community took notice...

The cost of opinion

It appears that I’ve been writing this essay since 2012, never quite finding the right framing. One of my brilliant colleagues asked me this question back then: “How do you evaluate whether a Javas…

Producing The Perfect Token

The unspoken inference quality gap and how numerics determine if the inference you're paying for is worth it.

The lost art of mathematical modelling

We provide a critique of mathematical biology in light of rapid developments in modern machine learning. We argue that out of the three modelling activities – (1) formulating models; (2) analysing models; and (3) fitting or comparing models to data – inherent to mathematical biology, researchers currently focus too much on activity (2) at the cost of (1). This trend, we propose, can be reversed by realising that any given biological phenomenon can be modelled in an infinite number of different ways, through the adoption of a pluralistic approach, where we view a system from multiple, different points of view. We explain this pluralistic approach using fish locomotion as a case study and illustrate some of the pitfalls – universalism, creating models of models, etc. – that hinder mathematical biology. We then ask how we might rediscover a lost art: that of creative mathematical modelling.

A result does not tell you how it was made - Sensemaker

A correct formula can have an unverified origin, and a successful AI answer can hide a forbidden route. Those claims need different evidence.

Donald MacKenzie · AI’s Scale

AI’s scale doesn’t matter just to specialists. The rest of us are being taken on a ride along the logarithmic curve...

Up and Down the Ladder of Abstraction

"In science, if you know what you are doing, you should not be doing it. In engineering, if you do not know what you are doing, you should not be doing it. Of course, you seldom, if ever, see either pure state."

Why Math is an Art, Not a Science

Mathematics is usually classed with the sciences, both in official catalogs and in the popular imagination. People who are good at science…

A quote by Edsger W. Dijkstra

The question of whether a computer can think is no more interesting than the question of whether a submarine can swim.

The End of Mathematics — Daniel Litt

I'm currently returning to Toronto from a summit on the future of mathematics, at OpenAI. Sebastian Bubeck asked me to talk a bit about the future we'd all like to avoid, where humans are mathematically disempowered. Jacob Tsimerman advised us to try to prioritize detail over correctness, and I have no doubt that I succeeded in deprioritizing correctness.