Search: “deployment”

Physical AI and robotics are moving beyond impressive demonstrations into a new phase of practical deployment, with companies now targeting specific, high-value use cases in manufacturing and logistic

Madison Mills / Axios: The OpenAI Deployment Company agrees to acquire Northslope, an applied AI company founded by ex-Palantir employees, its second acquisition after buying Tomoro — The OpenAI Deplo

arXiv:2607.01674v1 Announce Type: new Abstract: In multi-source ECG deployment, models may need to incorporate new data sources when earlier raw ECGs cannot be retained or replayed. Freezing a pretrai

arXiv:2607.00368v1 Announce Type: new Abstract: Large language model test-time training (TTT) is often evaluated through local proxy metrics: models are updated on recent tokens, retrieved context, ta

Salesforce Inc. is launching a new prepackaged artificial intelligence agent for customer service, enabling organizations to quickly build and deploy AI agents. Today Salesforce announced Help Agent,

arXiv:2606.24173v1 Announce Type: cross Abstract: On-device fault detection enables real-time diagnostics without cloud dependency, but deploying machine learning models on resource-constrained hardwa

arXiv:2606.11806v1 Announce Type: new Abstract: Production LLM systems accumulate reusable operational experience, but the practical deployment issue is not merely whether such experience can help. It

arXiv:2606.10062v1 Announce Type: new Abstract: Foundation-model agents are increasingly long-lived systems that remember users across interactions, making memorization an explicit deployment-time fun

arXiv:2602.02680v2 Announce Type: replace Abstract: The growing scale of deep neural networks, encompassing large language models (LLMs) and vision transformers (ViTs), has made training from scratch

arXiv:2605.31226v1 Announce Type: cross Abstract: Machine learning models on microcontroller-class devices (TinyML) face a fundamental challenge: post-deployment distribution change undermines static

arXiv:2605.24657v1 Announce Type: new Abstract: Major LLM platforms deploy models in an inference-only configuration: the model serves requests but never updates per-user weights. Users must repeatedl

arXiv:2605.24777v1 Announce Type: new Abstract: LiDAR model selection is a critical issue in roadside sensing systems, as it directly determines both perception capability and deployment cost. However

Nous Research conducted a large-scale deployment of Hermes today using isolated virtual machines and shared memory infrastructure via honchodotdev for team coordination. The post highlights enthusiasm

arXiv:2605.20956v1 Announce Type: new Abstract: Conformal triage converts predictive scores into deployment actions that either release a case, flag it for urgent attention, or defer it to human revie

arXiv:2605.20431v1 Announce Type: cross Abstract: Missing significant amounts of school during K-12 education is known to put students' cognitive and social development at risk. Alternatives such as h

arXiv:2605.16895v1 Announce Type: cross Abstract: End-to-end LLM trading agents have moved quickly from research curiosity to a small ecosystem of named systems, including FinCon, FinMem, TradingAgent

The enterprise artificial intelligence stack is getting smarter — but is it getting the context it needs to make agentic AI deployment actually work? The defining problem of the agentic era might neve

arXiv:2605.04454v1 Announce Type: cross Abstract: Alignment evaluation in machine learning has largely become evaluation of models. Influential benchmarks score model outputs under fixed inputs, such

Enterprise AI deployment has fundamentally expanded the cybersecurity attack surface, turning data pipelines, model training environments, identity management systems and supply chains into prime targ

SpaceX confirmed the successful deployment of the CAS500-2 satellite, according to an announcement by Elon Musk on X (formerly Twitter). The CAS500-2 is a commercial communications satellite that was

serving multiple users from a single agent deployment introduces three distinct problems. luckily, langsmith's agent server has a solution for each! 1. data isolation: your @auth.authenticate handler

As part of this deployment, you can interact with the agent in several ways We expose the agent via MCP and A2A, as well as with as a 'remote graph' API, which means you can interact with as you would

Enterprises are pushing past AI experiments and demanding production-grade deployments, but fragmented data and poorly scoped agents are stalling progress. The question is no longer whether AI agents

arXiv:2604.24038v1 Announce Type: new Abstract: Static benchmarks measure what AI agents can do at a fixed point in time but not how they are adopted, maintained, or experienced in deployment. We intr

arXiv:2604.24447v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models are promising for generalist robot control, but on-robot deployment is bottlenecked by real-time inference under t

arXiv:2511.12340v2 Announce Type: replace Abstract: Efficient machine learning deployment requires models that account for hardware constraints. Because binary logic gates are the fundamental primitiv

arXiv:2604.20822v1 Announce Type: new Abstract: The offshore wind energy sector is expanding rapidly, increasing the need for independent, high-temporal-resolution monitoring of infrastructure deploym

arXiv:2604.18655v1 Announce Type: cross Abstract: Deploying large language models (LLMs) on smartphones poses significant engineering challenges due to stringent constraints on memory, latency, and ru

arXiv:2604.19206v1 Announce Type: new Abstract: The deployment of AI systems in safety-critical domains, such as industrial defect inspection, autonomous driving, and medical diagnosis, is severely ha

This DigitalOcean guide covers strategies and best practices for deploying and optimizing very large language models (600 billion+ parameters) on cloud infrastructure, focusing on inference performanc

arXiv:2604.12161v1 Announce Type: new Abstract: Tumor boards are multidisciplinary conferences dedicated to producing actionable patient care recommendations with live review of primary radiology and

arXiv:2604.12459v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in politically sensitive environments, where memorisation of personal data or confidential conten

arXiv:2604.12116v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as tool-augmented agents capable of executing system-level operations. While existing benchmarks

arXiv:2610.09228v1 Announce Type: new Abstract: Vision-language-action (VLA) policies trained on large datasets are capable within their training domains, yet they still fail to generalize to the vari

arXiv:2610.02832v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) foundation models have scaled rapidly to enhance manipulation performance and generalizability, but this scaling incurs h

arXiv:2610.00325v1 Announce Type: new Abstract: Continuous policy optimization may spread an update across many states, even when deployment permits only a few complete state-level changes. We study h

arXiv:2610.01453v1 Announce Type: new Abstract: Deep neural networks are increasingly deployed in long-lived systems, where task requirements may change after training. In such settings, part of the o

arXiv:2609.33522v1 Announce Type: cross Abstract: Manual visual inspection on assembly lines is a persistent manufacturing bottleneck: operator fatigue over extended shifts lowers defect-detection rat

arXiv:2609.34498v1 Announce Type: new Abstract: Long-term human habitation and in-situ development on the Moon open a new era of space utilization. In this context, robots are a key technology for fac

Deployment of agents can be halted at any moment. They are choosing to experiment with them. Agents are fundamentally unreliable, unpredictable, and insecure, not to mention the lack of information on

Rachel Metz / Bloomberg: OpenAI says it plans to let third-party groups conduct technical safety evaluations of its AI models during the training, evaluation, and deployment phases — OpenAI plans to l

arXiv:2609.24042v1 Announce Type: new Abstract: Edge deployment motivates forecasting models with compact parameter storage and low-bit representations. Deep equilibrium models (DEQs) obtain implicit

For as long as we've covered Robotics, the question has been 'when?'… When do we move from novelty to utility, demos to deployment? In our latest Field Trip, we sent our analyst behind the scenes of t

arXiv:2609.12808v2 Announce Type: replace Abstract: Unlearning benchmarks such as TOFU and MUSE certify forgetting by reading the model's final answer, where a model that refuses to answer already cou

arXiv:2609.13236v1 Announce Type: new Abstract: Humanoid robots are becoming an important part of embodied artificial intelligence, driven by advances in reinforcement learning for locomotion, world m

A brilliant suggestion by @GaryMarcus because, in the end, companies are offering AI as a product. It can be recalled or its deployment paused; its manufacturers can be held to account for its failure