Excitement and existential dread defined my view of AI engineering—until this week. My dread has been replaced by a belief in our role as architects of the futu...

We establish a mathematical correspondence between state space models, a state-of-the-art architecture for capturing long-range dependencies in data, and an exa...

An assurance case is a structured argument document that justifies claims about a system's requirements or properties, which are supported by evidence. In regul...

Lateral predictive coding (LPC) is a simple theoretical framework to appreciate feature detection in biological neural circuits. Recent theoretical work [Huang ...

We study whether Large Language Models (LLMs) can perform feature model analysis operations (AOs) directly on semi-formal textual blueprints, i.e., concise cons...

Behaviour-Driven Development (BDD) suites accumulate step-text duplication whose maintenance cost is established in prior work. Existing detection techniques re...

Quality-Diversity (QD) algorithms excel at discovering diverse repertoires of skills, but are hindered by poor sample efficiency and often require tens of milli...

We extend our gauge-covariant stochastic neural-field framework by promoting architecture-level parameters to slow stochastic variables evolving in function spa...

TL;DR: Turn your ideas into full‑length, KDP‑ready books in minutes with Aivolut AI Book Creatorhttps://zdcs.link/z64N22?pageview_type=Standard&template=article...

!Pull Repohttps://media2.dev.to/dynamic/image/width=50,height=50,fit=cover,gravity=auto,format=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Fus...

High-capacity associative memories based on Kernel Logistic Regression (KLR) are known for their exceptional performance but are hindered by high computational ...

Chase Roossin, group engineering manager, and Steven Kulesza, staff software engineer, from Intuit join the podcast to chat about what might be the hardest prob...

The Synergistic Collapse occurs when scaling beyond 100 agents causes superlinear performance degradation that individual optimizations cannot prevent. We obser...

Introduction Comes to mind a meme with this expression, but I can’t find the related image. The Problem with Standard Benchmarks Whenever you build a system, p...

The rise of IoT devices and the uptake of cloud computing have informed a new era of data-driven intelligence. Traditional centralized machine learning models t...

Meta has found a new source of training data for its AI models: its own employees. The company plans to use data culled from the mouse movements and keystrokes...

Article URL: https://bsky.app/profile/edzitron.com/post/3mjzxwfx3qs2a Comments URL: https://news.ycombinator.com/item?id=47855565 Points: 106 Comments: 54...

TL;DR: If writing prompts slows you down, VibeFarm helps you build, save, and reusehttps://zdcs.link/922Wxe?pageview_type=Standard&template=article&module=conte...

Todos os dias surge uma IA nova, modelos novos, funcionalidades novas, um recorte de gastos daqui, menos tokens dali… e com isso, muita gente começa a se pergun...

Source - Tweet by Amol Avasarehttps://x.com/TheAmolAvasare/status/2046725498592722972 - XCancel linkhttps://xcancel.com/TheAmolAvasare/status/20467254985927229...

Multi‑agent systems are having a moment. Kimi K2.6 ships with Claw Groups supporting 300 parallel sub‑agents. Hermes Agent crossed 100 K GitHub stars in under t...

Funding round NeoCognition, a research‑focused startup developing self‑learning AI agents, has emerged from stealth with $40 million in seed funding. The round...

!https://9to5mac.com/wp-content/uploads/sites/6/2026/04/chatgpt-images-2-0.webp?w=1600 OpenAI announced its upgraded ChatGPT image generation model, ChatGPT Ima...

Ask Americans how they feel about AI and most say they have concerns. Communities have mounted resistance to data center projects, stalling them across the US....

The ChatGPT Images 2.0 model is here. Our testing shows it’s better at creating more detailed images and rendering text, but it still struggles with languages o...

The ChatGPT Images 2.0 model is here. Our testing shows it’s better at creating more detailed images and rendering text, but it still struggles with languages o...

An image generated by ChatGPT Images 2.0. | Image: OpenAI OpenAI is rolling out the latest version of its AI‑powered image generator with new “thinking capabili...

Overview OpenAI's new ChatGPT Images 2.0 model is now available. A little more than a year after OpenAI gave ChatGPT users the option to create images and desi...

April 21, 2026 A new era of image generation Try in ChatGPT opens in a new windowhttps://chatgpt.com/images/...

Recent advances in image generation and editing have opened new opportunities for virtual try-on. However, existing methods still struggle to meet complex real-...

Sparse-view 3D reconstruction is essential for modeling scenes from casual captures, but remain challenging for non-generative reconstruction. Existing diffusio...

We address the problem of generating a 3D-consistent, navigable environment that is spatially grounded: a simulation of a real location. Existing video generati...

Training modern neural networks often relies on large learning rates, operating at the edge of stability, where the optimization dynamics exhibit oscillatory an...

We establish central and non-central limit theorems for sequences of functionals of the Gaussian output of an infinitely-wide random neural network on the d-dim...

Reinforcement learning (RL) offers a compelling data-driven paradigm for synthesizing controllers for complex systems when accurate physical models are unavaila...

Conditional medical image generation plays an important role in many clinically relevant imaging tasks. However, existing methods still face a fundamental chall...

Scaling humanoid foundation models is bottlenecked by the scarcity of robotic data. While massive egocentric human data offers a scalable alternative, bridging ...

Some of the most performant reinforcement learning algorithms today can be prohibitively expensive as they use test-time scaling methods such as sampling multip...

Personalized Federated Learning (PFL) aims to learn multiple task-specific models rather than a single global model across heterogeneous data distributions. Exi...

We present VLA Foundry, an open-source framework that unifies LLM, VLM, and VLA training in a single codebase. Most open-source VLA efforts specialize on the ac...

Despite the remarkable success of Vision Transformers (ViTs) across a wide range of vision tasks, recent studies have revealed that they remain vulnerable to ad...

The discretization of continuous numerical attributes remains a persistent computational bottleneck in the induction of decision trees, particularly as dataset ...

Human video generation remains challenging due to the difficulty of jointly modeling human appearance, motion, and camera viewpoint under limited multi-view dat...

Large Language Models (LLMs) still struggle with multi-step logical reasoning. Existing approaches either purely refine the reasoning chain in natural language ...

Synopsis Meta is installing new tracking software on US‑based employees' computers to capture mouse movements, clicks, and keystrokes for use in training its a...

Distribution networks with high penetration of Distributed Energy Resources (DERs) increasingly rely on communication networks to coordinate grid-interactive co...

In [97,99,100], an fl-RDT framework is introduced to characterize statistical computational gaps (SCGs). Studying symmetric binary perceptrons (SBPs), [100] obt...

Vision-Language-Action (VLA) models offer a promising autonomous driving paradigm for leveraging world knowledge and reasoning capabilities, especially in long-...