Physics and AI share a deep history, in some respects one could argue that 21st century machine learning scientists are arguably at the forefronts of science similiar to physicists in the early 20th century.

The works of Geoffry Hinton

1927 Solvay Conference

This is the first post. It’s here mostly to prove the pipeline works end to end: Markdown in, a properly typeset page out — LaTeX included.

Inline math

You can write inline math like $e^{i\pi} + 1 = 0$ right in a sentence, and it renders in place, at reading size, without breaking the line height.

Display math

For anything that deserves its own line, use display math:

\[\zeta(s) = \sum_{n=1}^{\infty} \frac{1}{n^s}, \qquad \operatorname{Re}(s) > 1\]

Multi-line derivations work too, using aligned:

\[\begin{aligned} \nabla \times \mathbf{E} &= -\frac{\partial \mathbf{B}}{\partial t} \\ \nabla \times \mathbf{B} &= \mu_0 \mathbf{J} + \mu_0 \varepsilon_0 \frac{\partial \mathbf{E}}{\partial t} \end{aligned}\]

Code, too

Since a lot of what’s worth writing down is code, not just math:

def zeta_partial(s, n_terms=10_000):
    return sum(1 / n**s for n in range(1, n_terms + 1))

A blockquote, for asides, caveats, or things I want to walk back later.

That’s the whole toolkit: headings, inline and display LaTeX, code blocks, and blockquotes. Delete this post once you’ve got a real first entry.