Model releases, architecture work and prompting research on large language models — from frontier-lab announcements to the arXiv papers behind them.
Large language models are informing decisions with ever-higher stakes. As the consequences of their errors grow, a central question becomes harder to ignore: how much can we trust an individual answer...
Simon Willison comments on EmbeddingGemma 2, noting its Apache 2.0 license and expressing preference for open‑weight models over proprietary, hosted‑only options. He argues that embedding models are often used to generate and store large numbers of vectors, and a closed model could force costly re‑embedding if the vendor discontinues service. Willison prefers a hosted solution that allows him to switch to the open‑weight version if needed.
Mistral has released a preview of its new Mistral Large 4 model, a 1 trillion‑parameter, 49 billion‑active‑parameter language model trained on a cluster of 3,800 NVIDIA Grace‑Blackwell GPUs. The preview is available through their API, with two reasoning levels—"none" and "high"—and the company plans to release the open‑weights version by the end of the month. In preliminary tests, the model scores 38 on Artificial Analysis, outperforming last year’s Mistral Large 3 and approaching the performance of larger competitors.
Continuous cardiac monitoring outside clinical settings requires signals that are both informative and practical to collect during daily life. Electrocardiography (ECG) provides rich information about...
The article is a comment by Simon Willison on the Mistral Large 4 model, posted on Hacker News. He discusses the saturation of benchmarks and humorously references a benchmark involving an armadillo in fishnet tights jaywalking on Mars, comparing the performance of several large language models including Claude Opus, GPT, Gemini, and Mistral Large 4.
While vision-language-action (VLA) models have advanced rapidly, running them at every control step remains expensive. Prior work accelerates VLA inference using techniques like action chunking and vi...
Scientific research often begins by synthesizing ideas from a set of related papers to identify gaps and formulate new directions. However, training language models to perform this form of literature-...
Current video editors can insert objects but often struggle to make them participate in interactions such as being picked up or manipulated. We introduce ALIVE, a framework that makes inserted objects...
Interactive video world models need to generate each video chunk efficiently while responding faithfully to user controls. Many systems use chunk-wise autoregressive generation with few-step denoising...
A common approach to measuring bias in Large Language Models is to compare the log-likelihoods of two contrastive stereotype sentences. We argue that such single-pair comparisons are often unreliable:...
Generative retrieval trains a language model to generate the identifier of a relevant document. Recent work replaces the autoregressive decoder with diffusion, but changes identifiers, training recipe...
Large language model agents are accelerating scientific automation, yet verified executions rarely become persistent program-level improvements, and existing evaluations do not examine this process ac...
Contact with contaminated objects can spread hazards through a household robot's grippers, tools, and shared surfaces, while new contacts can make an existing plan unsafe. Existing benchmarks do not j...
Automatic Speech Recognition (ASR) systems often show uneven performance across demographic groups, and errors can be especially difficult to address for speakers belonging to multiple demographic gro...
Large language models (LLMs) are increasingly relied upon to support ambient documentation and clinical reasoning. Here we examine the impact of a failure mode shared between these two applications by...
While unlearning seeks to negate undesired capabilities acquired through learning, little research has examined how the way models learn shapes their subsequent unlearning. In this paper, we investiga...
Streaming video-language models must decide not only what to answer, but whether the evidence needed for the current question has arrived. Existing systems learn that decision as a separate trigger; w...
Simon Willison experimented with Claude Opus 5.5 to compose computer game music, specifically aiming for a style reminiscent of the original *Secret of Monkey Island*. He designed a simple text-based format for the music and built an artifact capable of playing it, including example tracks. The results were surprisingly good, prompting questions about whether this compositional ability is a new capability emerging in recent text models.
Long-context inference and Retrieval-Augmented Generation (RAG) handle evidence selection at vastly different scales, from a single long prompt to an entire corpus. We ask whether a single model-inter...
Multimodal large language models (MLLMs) have made significant progress in visual understanding, but precise 3D spatial reasoning integrated with physical environment remains difficult. Furniture asse...