digitado

arXiv:2605.10971v1 Announce Type: new Abstract: Discrete diffusion language models (DLMs) generate text by iteratively denoising all positions in parallel, offering an alternative to autoregressive models. Controlled generation methods for DLMs, imported from autoregressive models, apply uniform intervention at every denoising steps. We show this uniform schedule degrades quality, and the damage compounds when multiple attributes are steered jointly. To diagnose the failure, we train sparse autoencoders on four DLMs (124M-8B parameters) and find that different attributes commit on […]

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arXiv:2605.10966v1 Announce Type: new Abstract: Terminals provide a powerful interface for AI agents by exposing diverse tools for automating complex workflows, yet existing terminal-agent benchmarks largely focus on tasks grounded in text, code, and structured files. However, many real-world workflows require practitioners to work directly with audio and video files. Working with such multimedia files calls for terminal agents not only to understand multimedia content, but also to convert auditory and visual evidence across related files into appropriate […]

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arXiv:2605.10964v1 Announce Type: new Abstract: Embedding advertisements into large language model (LLM) outputs introduces a fundamental tension: revenue optimization can distort content and degrade user experience. Existing approaches largely ignore this trade-off, often forcing irrelevant ads into responses. We propose a quality-preserving auction framework that explicitly integrates content fidelity into the mechanism design. Built on retrieval-augmented generation (RAG), our approach treats organic content as a reference and derives an endogenous reserve price that screens out ads with non-positive […]

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arXiv:2605.10959v1 Announce Type: new Abstract: There is currently no unified metric for evaluating the efficiency of quantized neural networks. We propose QuIDE, built around the Intelligence Index I = (C x P)/log_2(T+1), which collapses the compression-accuracy-latency trade-off into a single score. Experiments across six settings — SimpleCNN (MNIST, CIFAR), ResNet-18 (ImageNet-1K), and Llama-3-8B — show a task-dependent Pareto Knee. 4-bit quantization is optimal for MNIST and large LLMs, while 8-bit is the sweet spot for complex CNN tasks […]

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arXiv:2605.10947v1 Announce Type: new Abstract: EEG microstate analysis segments continuous brain electrical activity into brief, quasi-stable topographic configurations that reflect discrete functional brain states. Conventional approaches such as Modified K-Means operate directly in electrode space with hard assignment, offering no learned latent representation, no generative decoder, and no mechanism to decode latent configurations into verifiable scalp topographies, limiting both model transparency and interpretability. To address this, we present a Convolutional Variational Deep Embedding (Conv-VaDE) model that jointly learns […]

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OpenAI details its response to the TanStack “Mini Shai-Hulud” supply chain attack, outlines protections taken to secure systems and signing certificates, and explains why macOS users must update OpenAI apps by June 12, 2026. Learn what happened, what was affected, and how OpenAI is strengthening defenses against evolving software supply chain threats.

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Release: datasette 1.0a29 New TokenRestrictions.abbreviated(datasette) utility method for creating “_r” dictionaries. #2695 Table headers and column options are now visible even if a table contains zero rows. #2701 Fixed bug with display of column actions dialog on Mobile Safari. #2708 Fixed bug where tests could crash with a segfault due to a race condition between Datasette.close() and Database.close(). #2709 That segfault bug was gnarly. I added a mechanism to Datasette recently that would automatically close connections at the […]

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Now, if your CEO has never heard the phrase Ralph Loop, oh man, you are less than 30 days away from your next promotion. I’m not even exaggerating. Walk into his office, close the door, and say, hey chief, been experimenting with something. It’s called Ralph Loops. And I think it could change literally everything. And he’s gonna say, what’s a Ralph loop? And you will say, give me $18,000 worth of API credits and I’ll show you. […]

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The thing about 90% of TDMs [Technical Decision Makers] is that they’re motivated primarily by NOT GETTING FIRED. These aren’t people who browser Lobsters or push to GH on the weekend. These are people that work 9 to 5, get paid, go home, and NEVER THINK ABOUT WORK AGAIN. So to achieve all that, they follow secular trends supported by analysts and broad public sentiment. Oh, Gartner said that “AI strategy” is most important? McKinsey said “context” needs […]

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In this tutorial, we begin by exploring the architecture behind a hybrid-memory autonomous agent. This system combines semantic vector search, keyword-based retrieval, and a modular tool-dispatching loop to create an agent capable of reasoning, remembering, and acting autonomously. We walk through each layer of the design from the ground up, starting with abstract interfaces that enforce clean separation of concerns, all the way to a live agent that manages its own long-term memory. Copy CodeCopiedUse a different Browser […]

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