The Archive

Release: micropython-wasm 0.1a1 Fixes for some limitations that emerged while I was trying to use this to build datasette-agent-micropython . Tags: python , sandboxing , webassembly

Uber's cutback has occurred after the company had reportedly encouraged staff to use AI as much as possible.

Microsoft on Tuesday took the wraps off Adaptive Spec-driven Scoring for Evaluation and Regression Testing, an open-source framework for spinning up AI evaluations.

AI agents are changing how you interact with your PC. Creators, developers, and AI enthusiasts are already using these agents extensively to assist with... AI agents are changing how you interact with your PC. Creators, developers, and AI enthusiasts are already using these…

President Donald Trump signed an executive order Tuesday creating a "voluntary framework" for AI companies to share their frontier models with the federal government before they're released "to promote secure innovation and strengthen the cybersecurity of critical…

International Mathematical Union endorses warning about tech industry influence.

California Brown Pelican, in Fort Mason, CA, US I'm at the Microsoft Build conference today, held at Fort Mason in San Francisco. There are California Brown Pelicans diving into the water directly behind venue! Tags: microsoft , ai , generative-ai , llms , llm-release

The caveat is that one of the world's most famous living directors is using the tech solely for storyboarding.

Microsoft announced a bunch of new in-house AI models at Build 2026, including a new "flagship" model: MAI-Thinking-1. It's an ambitious step into model development for Microsoft, which introduced its initial in-house models last year - before then, it had relied on OpenAI's…

Google's June Android feature drop includes more scam detection, more AirDrop, and yes, more AI.

The specification lets developer, compliance and security teams define their own policies for agents to follow in portable policy files.

Google is launching a new feature for its Phone app that aims to protect you from AI impersonation scams. Now, when you receive a call from a scammer that appears to be coming from the same number as one of your contacts, Phone by Google will flag the call as suspicious so you…

Much like Google, Microsoft is launching its own version of OpenClaw. Microsoft Scout is an always-on assistant that integrates into Microsoft 365 apps like Outlook, OneDrive, and Microsoft Teams, allowing businesses to assign a virtual assistant to employees to help with…

As people increasingly refuse to answer calls from unknown numbers, scammers are shifting their tactics by spoofing trusted phone numbers and using AI deepfake technology to sound like authority figures, family members, or employers.

We investigate whether neuron populations within neural networks evolve predictably with scale, extending scaling laws beyond macroscopic observables such as loss. To probe this question, we study Rosetta Neurons, a previously characterized class of neurons whose activation…

Vision language models (VLMs) excel at many tasks but still struggle with spatial reasoning when critical information is not directly observable. Many such problems require imaginative perception: inferring what would be seen from an unseen viewpoint, tracing paths through…

We introduce Humanoid-GPT, a GPT-style Transformer with causal attention trained on a billion-scale motion corpus for whole-body control. Unlike prior shallow MLP trackers constrained by scarce data and an agility-generalization trade-off, Humanoid-GPT is pre-trained on a…

Quantities with measurement units, such as 110 cm and 1.2 m, require language models (LMs) to combine a numeral with a symbolic unit scale. Here, we study how LMs compare such quantities in controlled settings spanning several unit systems. We find that accuracy degrades near…

Reward models (RMs) provide critical feedback signals for LLM post-training, notably in reinforced fine-tuning (RFT) and reinforcement learning (RL) pipelines. However, current reward evaluation relies on heterogeneous criteria such as rule-based verifiers, ground-truth…

The past few decades have witnessed significant advances in the design of machine learning algorithms, from early studies on task-specific shallow models to more general deep Large Language Models (LLMs). Despite showing promising results in tasks that require instant…

Representations of the world, arguably, contain information about features (e.g. something is blue, something is a circle) but also information about which features are part of the same object (e.g. the circle is blue), which we call binding information. Any system with the…

Reliable uncertainty communication is critical to the trustworthiness of LLMs, yet faithful calibration (FC)--the alignment between models' intrinsic and (linguistically) expressed confidence--is a persistent failure mode. This challenge is key for large reasoning models…

Rubric-based RL is a promising route for extending reinforcement learning beyond verifiable rewards, yet existing methods optimize rubrics while treating the query distribution as fixed. We identify a structural bottleneck: rubric quality is constrained by query structure…

We describe AlignAtt4LLM, an IWSLT 2026 simultaneous speech translation system for English to German, Italian, and Chinese. The system is a synchronous cascade: Qwen3-ASR with forced alignment produces an incrementally updated source transcript, and Gemma-4 E4B-it translates…

Large language models improve final-answer accuracy through extended chain-of-thought reasoning, but often spend tokens inefficiently and offer little inference-time control. Existing efficient reasoning methods control thinking length by shortening, early-stopping, or…

Deep reinforcement learning has shown strong potential for enabling autonomous robots to learn complex navigational tasks. However, its practical use still depends heavily on human designed reward functions and repeated manual fine tuning, which is time consuming and does not…

Classical reinforcement learning (RL) typically seeks a deterministic policy that maximizes the expected sum of a scalar reward. Yet, modern applications such as language model fine-tuning or scientific discovery demand diversity. Existing remedies such as entropy…

The class action lawsuit, filed in Seattle by Virginia resident Charles Sigwalt, claims that Ring's Familiar Faces feature stores images of passersby without consent.

Conversational ASR for lower-resource languages and niche domains is limited by the scarcity of domain-matched multi-speaker training data. We propose an augmentation pipeline that generates scenario-level dialogues with participant metadata, maps speaker attributes to TTS…

As AI systems increasingly assist humans in physical tasks, ensuring safety becomes paramount -- physical actions carry immediate and irreversible consequences that digital errors do not. We introduce the Vision-Language Embodied Safety Agent (VLESA), a framework that monitors…