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How science startups actually work

It’s tough being an academic these days. Between the tiny number of permanent positions and the systemic exploitation of cheap labour, people are looking for a way out. Students, postdocs, and even PIs are asking themselves: should I join a startup? Should I make my own startup? It sounds seductive—change the world! Make money! Keep […]

Large language models will change science

It takes dedication to keep up with the scientific literature. 2344 papers were accepted at last year’s NeurIPS conference. Who has time to read all of that? It’s difficult to see the forest from the trees as ever more research is published. What if every single one of us had infinite access to world experts […]

What’s the endgame of neuroAI?

This blog post was adapted into an article for a16z’s Future. It’s been 60 years since Hubel and Wiesel first started unlocking the mysteries of the visual system. Proceeding one neuron at a time, they discovered the fundamental building blocks of vision, the simple and complex cells. Yet for a long time, neurons in high-level […]

Unsupervised models of the brain

We’re in a golden age of merging AI and neuroscience. No longer tied to conventional publication venues with year-long turnaround times, our field is moving at record speed. 2021 saw a Cambrian explosion of research into unsupervised learning to explain brain representations, which is teaching us about how the brain might have evolved for sensing. […]

The Good Research Code Handbook

When I was in grad school, I wrote a lot of code which ended up biting me later. It wasn’t until I got a job as a software engineer at Google that I discovered better ways of organizing code. Writing reusable, easy-to-read code is a core skill to have when you’re spending half of your […]

Dimensionality reduction in neural data analysis

It’s become commonplace to record from hundreds of neurons simultaneously. If past trends extrapolate, we might commonly record 10k neurons by 2030. What are we going to do with all this data? To deal with a 14-dimensional space, visualize a 3D space and say fourteen to yourself very loudly. Everyone does it. Geoffrey Hinton Neural […]

My stack for research ML projects

For the past few months, I’ve been working on a machine learning research project, which I just submitted to NeurIPS [update: it was accepted as a spotlight! Preprint here]. The scale is, all things considered, fairly small: the output limited to one paper and a handful of figures. Yet, I still needed to distribute the […]

Dynamic scientific visualizations in the browser for Python users

Updated September 8th, 2022 with info about gradio, Idyll, pyscript As a scientist, interacting with data allows you to gain new insight into the phenomena you’re studying. If you read the New York Times, the D3 docs or you browse distill, you’ll see impressive browser-based visualizations – interactive storytelling that not only accurately represent data […]

Accelerating progress in brain recording tech

In Stevenson and Kording (2011), the authors estimated that every 7.4 years, the number of neurons we can record with doubles. Think of it as Moore’s law for brain recordings. Since then, Stevenson has updated the estimate, which now stands at 6 years. Could it be that progress itself is accelerating? Matteo Carandini raised a […]

Is early vision like a convolutional neural net?

Early convolutional neural net (CNNs) architectures like the Neocognitron, LeNet and HMAX were inspired by the brain. But how much like the brain are modern CNNs? I made a pretty strong claim on Twitter a few weeks ago that the early visual processing is nothing like a CNN: In typical Twitter fashion, my statement was […]

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