Gephi Tutorial
A Gephi tutorial presented to students at Northeastern. To get all the data required to run along the tutorial, click here.
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The Future is Algorithmic Feeds on Bluesky
If the original sin of Web 1.0 was the pop-up ad, the original sin of web 2.0 was the move to algorithmic feeds. Opaque optimization strategies aimed at maximizing private revenue for the sake of what was otherwise externally billed as public goods became increasingly toxic, spawning discourse
How Much Data is Enough for Finetuning an LLM?
There's no shortage of analogies for explaining what an LLM is capable of - one of the best, though, is from this New Yorker article proclaiming it as a "blurry JPEG of the web". This metaphor is particularly useful for capturing many of the technical aspects
Using Synthetic Data Generators to Measure LSTM Lift
Long short-term memory models (LSTMs) are a family of neural networks that are predominantly used to predict the next value given a historical chain of previous values. These can be numerical predictions (i.e. where is the stock price going based on historical stock data) or categorical predictions (i.e.
Some supervision required: LLMs at scale in practice
Recently, I gave a talk at the PIE/Autodesk space to help contextualize some thoughts that have been percolating with regards to the nascent introduction of API-based, widely available LLMs like ChatGPT. In the hype cycle, I've observed some pretty broad claims about what's happening under