digitado

We present a theoretical analysis and empirical evaluations of a novel set of techniques for computational cost reduction of test time operations of network classifiers based on extreme learning machine (ELM). By exploring some characteristics we derived from these models, we show that the classification at test time can be performed using solely integer operations without compromising the classification accuracy. Our contributions are as follows: (i) We show empirical evidence that the input weights values can be drawn […]

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Computing pairwise Wasserstein distances is a fundamental bottleneck in data analysis pipelines. Motivated by the classical Kuratowski embedding theorem, we propose two neural architectures for learning to approximate the Wasserstein-2 distance ($W_2$) from data. The first, DeepKENN, aggregates distances across all intermediate feature maps of a CNN using learnable positive weights. The second, ODE-KENN, replaces the discrete layer stack with a Neural ODE, embedding each input into the infinite-dimensional Banach space $C^1([0,1], mathbb{R}^d)$ and providing implicit regularization via […]

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Researchers and practitioners are increasingly considering reinforcement learning to optimize decisions in complex domains like robotics and healthcare. To date, these efforts have largely utilized expectation-based learning. However, relying on expectation-focused objectives may be insufficient for making consistent decisions in highly uncertain situations involving multiple heterogeneous groups. While distributional reinforcement learning algorithms have been introduced to model the full distributions of outcomes, they can yield large discrepancies in realized benefits among comparable agents. This challenge is particularly acute […]

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Release: datasette-ports 0.1 Another example of README-driven development, this time solving a problem that might be unique to me. I often find myself running a bunch of different Datasette instances with different databases and different in-development plugins, spreads across dozens of different terminal windows – enough that I frequently lose them! Now I can run this: datasette install datasette-ports datasette ports And get a list of every running instance that looks something like this: http://127.0.0.1:8333/ – v1.0a26 Databases: […]

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Eight years of wanting, three months of building with AI Lalit Maganti provides one of my favorite pieces of long-form writing on agentic engineering I’ve seen in ages. They spent eight years thinking about and then three months building syntaqlite, which they describe as “high-fidelity devtools that SQLite deserves“. The goal was to provide fast, robust and comprehensive linting and verifying tools for SQLite, suitable for use in language servers and other development tools – a parser, formatter, […]

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Learning from weak or proxy supervision is common when ground-truth labels are unavailable, yet robustness under distribution shift remains poorly understood, especially when the supervision mechanism itself changes. We formalize this as supervision drift, defined as changes in P(y | x, c) across contexts, and study it in CRISPR-Cas13d experiments where guide efficacy is inferred indirectly from RNA-seq responses. Using data from two human cell lines and multiple time points, we build a controlled non-IID benchmark with explicit […]

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There’s a particular kind of tedium that every AI engineer knows intimately: the prompt-tuning loop. You write a system prompt, run your agent against a benchmark, read the failure traces, tweak the prompt, add a tool, rerun. Repeat this a few dozen times and you might move the needle. It’s grunt work dressed up in Python files. Now, a new open-source library called AutoAgent, built by Kevin Gu at thirdlayer.inc, proposes an unsettling alternative — don’t do that […]

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In this tutorial, we build and run an advanced pipeline for Netflix’s VOID model. We set up the environment, install all required dependencies, clone the repository, download the official base model and VOID checkpoint, and prepare the sample inputs needed for video object removal. We also make the workflow more practical by allowing secure terminal-style secret input for tokens and optionally using an OpenAI model to generate a cleaner background prompt. As we move through the tutorial, we […]

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Most foundation models in biology have a fundamental blind spot: they see cells as frozen snapshots. Give a model a single-cell transcriptome — a readout of which genes are active in a cell at a given moment — and it can tell you a lot about what that cell is doing right now. What it can’t tell you is where that cell is headed. That limitation matters enormously when studying aging. Age-related diseases like heart disease, Alzheimer’s dementia, […]

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The best way to run AI and remain HIPAA compliant is to run it locally on your own hardware, instead of transferring protected health information (PHI) to a remote server by using a cloud-hosted service like ChatGPT or Claude. [1]. There are HIPAA-compliant cloud options, but they’re both restrictive and expensive. Even enterprise options are not “HIPAA compliant” out of the box. Instead, they are “HIPAA eligible” or that they “support HIPAA compliance,” because you still need the […]

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