Search: “engineering”

arXiv:2605.17705v1 Announce Type: cross Abstract: Panel data, in which multiple units are repeatedly observed over time, arise throughout science and engineering. Quantifying predictive uncertainty in

arXiv:2602.21426v2 Announce Type: replace Abstract: We consider the problem of sampling from a posterior distribution arising in Bayesian inverse problems in science, engineering, and imaging. Our met

arXiv:2605.17169v1 Announce Type: new Abstract: Agentic AI is rapidly proliferating across diverse real-world domains such as software engineering, yet public trust has not kept pace. The central reas

arXiv:2605.17582v1 Announce Type: new Abstract: Many natural and engineered time series -- equity returns, climate anomalies, turbulent velocities, neural recordings, packet-level network traffic -- a

arXiv:2510.08702v2 Announce Type: replace Abstract: Code Large Language Models (LLMs) are revolutionizing software engineering. However, scaling laws that guide the efficient training are predominantl

Spotify's Chief Architect just showed how they ship 4,5K deployments /day with Claude at Anthropic stage 27-minutes. free. By #1 music app dev 'More than 99% of our engineers use AI coding tools. Adop

arXiv:2605.16610v1 Announce Type: new Abstract: High-dimensional data arise naturally in many areas of science and engineering, including machine learning, signal processing, computational physics, an

arXiv:2605.16428v1 Announce Type: cross Abstract: Search engines traditionally complement online content platforms by directing users seeking information to external websites. The emergence of generat

Behind the scenes of SmithDB with @ankush_gola11 ⤵️ We leveraged two amazing open source projects when building SmithDB. One is @ApacheDataFusio: an extensible Rust based query engine. We built custom

Every time I ask my 10-year-old to use coding agents, he gets extremely disappointed. It turns out that all he wants is to build his own rocket simulator. No amount of context engineering helps. No mo

arXiv:2605.15223v1 Announce Type: cross Abstract: This paper presents an LLM-empowered workflow for RISC-V supply chain analysis, integrating Vision-Language Models (VLMs) and Model-Driven Engineering

arXiv:2603.01290v3 Announce Type: replace Abstract: The 2026 Formula 1 technical regulations introduce a fundamental change to energy strategy: under a 50/50 internal combustion engine / battery power

arXiv:2605.15253v1 Announce Type: new Abstract: Machine learning research increasingly bifurcates into two disconnected modes: benchmark-driven engineering that prioritizes metrics over understanding,

Artificial intelligence agents have a memory problem and now Redis Inc., the database management startup, is trying to fix that with its new, real-time Context Engine. As the company explains, it’s al

Simulation is a core part of how we build and evaluate robots. I spoke about simulation, robotics, and the role of interactive worlds at AI Engineer Singapore this past weekend! Full talk : https://ww

arXiv:2605.15881v1 Announce Type: cross Abstract: The modeling and simulation of infinite-dimensional Hamiltonian systems are central problems in mathematical physics and engineering, however they pos

Witchcraft is a Rust reimplementation of Stanford's XTR-Warp semantic search engine that uses a single-file SQLite database for storage, enabling client-side deployment. The system operates completely

The aiDotEngineer Singapore conference, organized by speakers including Agrim Singh and Swyx, successfully concluded, marking the completion of the first edition of this AI engineering-focused event i

This post appears to be a congratulatory message acknowledging exceptional work or contributions from members of the AI engineering community (@aiDotEngineer, @agrimsingh, and @swyx), suggesting they

Test like you fly and test what you fly. Check out this video if you want to see (and hear) some progress updates on Starship. Our next generation v3 rocket is designed to be foundational for what com

This is one of the first real continual learning systems for agents in production. Not just monitoring. Actually getting better over time. LangSmith Engine is how we’re spinning the always-on, self-im

arXiv:2605.14211v1 Announce Type: new Abstract: Long-horizon embodied tasks remain a fundamental challenge in AI, as current methods rely on hand-engineered rewards or action-labeled demonstrations, n

arXiv:2605.14553v1 Announce Type: cross Abstract: Prompt engineering has become central to eliciting the capabilities of large language models (LLMs). At its core lies prompt selection -- efficiently

Google updated its spam policy to mark attempts to 'manipulate' its AI model in search results as spam, including results in AI Overview or AI Mode in Search, as Search Engine Land reports: 'In the co

arXiv:2605.13848v1 Announce Type: new Abstract: Agentic LLM frameworks that rely on prompted orchestration, where the model itself determines workflow transitions, often suffer from hallucinated routi

arXiv:2605.14561v1 Announce Type: new Abstract: Prompt engineering is crucial for effective interaction with generative artificial intelligence systems, yet existing optimisation methods often operate

arXiv:2605.14443v1 Announce Type: new Abstract: The shift toward interacting with frozen, 'black-box' Large Language Models (LLMs) has transformed prompt engineering from a heuristic exercise into a c

arXiv:2604.03551v2 Announce Type: replace-cross Abstract: Software Engineering 3.0 marks a paradigm shift in software development, in which AI coding agents are no longer just assistive tools but acti

arXiv:2605.12925v1 Announce Type: cross Abstract: Evaluation of software engineering (SWE) agents is dominated by a binary signal: whether the final patch passes the tests. This outcome-only view trea

arXiv:2605.13295v1 Announce Type: cross Abstract: LLM-based multi-agent systems have demonstrated strong performance across complex real-world tasks, such as software engineering, predictive modeling,

arXiv:2502.05157v3 Announce Type: replace Abstract: The perspective of developing trustworthy AI for critical applications in science and engineering requires machine learning techniques that are capa

In 2010, an engineer at a cloud-based business software company in India became enamored with an idea to build uncomplicated service software to deliver valuable customer and employee experiences and

arXiv:2605.12683v1 Announce Type: cross Abstract: Reconstructing nonlinear dynamical systems (DS) from data (DSR) is a fundamental challenge in science and engineering, but it inherently relies on seq

arXiv:2602.06104v2 Announce Type: replace Abstract: Many engineering and scientific workflows rely on expensive black-box evaluations, requiring sequential decisions that must both improve task perfor

arXiv:2605.12916v1 Announce Type: cross Abstract: Artificial intelligence is increasingly used to simplify complex tasks. In engineering applications of structural health monitoring (SHM), existing sp

🔴 We're LIVE from the SaaStr floor, Day 3! 🎙️🚀 Closing day. Joined this morning by: • Kathy Shin (Replit Support) • Jacob Eisner (Replit Field Engineering) • Samuel Spitz (Replit AI Products) Get in h

which was your favorite launch? SmithDB (database purpose built for agent trace data): https://www.langchain.com/blog/introducing-smithdb LangSmith Engine (agent for improving your agents based on tra

XANI (X-ray Analysis for Nanoscale Imaging) is an accelerated computing pipeline developed by NVIDIA engineers for rapid X-ray data analysis. NVIDIA's accelerated computing enables real-time experimen

This article likely discusses how advances in large language models, prompt engineering, and in-context learning are making traditional finetuning less necessary for many applications. It probably exp

arXiv:2605.11202v1 Announce Type: cross Abstract: LLM inference and serving systems have become security-critical infrastructure; however, many of their most concerning failures arise from the serving

Every day, thousands of hours of new video content sits waiting to be discovered. Most of it lives in long-form, horizontal formats, while audiences are scrolling through vertical feeds on their phone

How Arize uses Alyx to debug Alyx: searching dense traces, aggregating failures, triaging dogfooding issues, and closing the AI engineering feedback loop. The post How we use Alyx to build Alyx: How t

arXiv:2605.12449v1 Announce Type: new Abstract: While self-supervised pretraining has reduced vision systems' reliance on synthetic data, simulation remains an indispensable tool for closed-loop optim

Dutch artificial intelligence infrastructure giant Nebius Group N.V. said today it’s recruiting the core engineering team from AI orchestration software firm Clarifai Inc. in an effort to boost its ma

Reinforcement-learning agents — AI systems that learn by trial and error — can convert computation into new knowledge. That’s the focus of a new engineering-level collaboration between NVIDIA and Inef

Starship launch next week! Starship’s twelfth flight test will debut the next generation Starship and Super Heavy vehicles, powered by the next evolution of the Raptor engine and launching from a newl