Search: “deployment”

Safely run AI-generated code in Cloud Run sandboxes

model-releasesgoogle-cloud-ai

Here’s a question we hear often at Google Cloud: How do you safely run AI-generated code or untrusted binaries without putting your host application, data, and cloud credentials at risk? In other word

9 Jul 2026

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Where to Intervene? Benchmarking Fairness-Aware Learning on Differentially Private Synthetic Tabular Data

DGX agent

arXiv:2607.07471v1 Announce Type: cross Abstract: Machine learning models are increasingly deployed in high-stakes domains, raising concerns about both privacy and fairness. Differential Privacy (DP)

model-releasesarxiv-cs-ai

9 Jul 2026

AirflowAttack: Thermal-Airflow Adversarial Perturbations against Infrared Remote-Sensing Vision-Language Models

arXiv:2607.06485v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly deployed on infrared (IR) remote sensing imagery in security-critical settings, yet their adversarial r

Hardware

Announcing our $130M Series A to build the Open Superintelligence Stack Led by Radical Ventures, with NVIDIA, Intel Capital, Dell Capital, a…

Announcing our $130M Series A to build the Open Superintelligence Stack Led by Radical Ventures, with NVIDIA, Intel Capital, Dell Capital, and existing investors Train, deploy, and continuously improv

hardwareclem-delangue--x

Building and connecting a production-ready ecommerce MCP server using Amazon Bedrock AgentCore and Mistral AI Studio

model-releasesaws-ml-blog

In this post, you build and connect that server end to end. You will implement MCP tools, set up two-layer JSON Web Token (JWT) authentication, deploy with AWS Cloud Development Kit (AWS CDK), and con

Tools

Chat SDK now supports Vercel Connect

Vercel has announced support for Vercel Connect within its Chat SDK, enabling developers to integrate real-time chat functionality with Vercel's infrastructure and deployment services. This update lik

toolsvercel-blog

Drift Happens: An Empirical Study of Neural Architecture Robustness to Temporal Distribution Shift

arXiv:2607.05908v1 Announce Type: new Abstract: Real-world data distributions evolve over time, inducing temporal distribution shift that can substantially degrade the reliability of deployed machine

applicationsarxiv-cs-lg

Exogenous Dropout: A Simple, Strong Baseline for Corruption-Robust Time Series Forecasting with Covariates

model-releasesarxiv-cs-lg

arXiv:2607.05452v1 Announce Type: new Abstract: Time series forecasters that use exogenous covariates are fragile in deployment: when those covariates are noised, temporally misaligned, or missing, st

Is Your NPU Ready for LLMs? Dissecting the Hidden Efficiency Bottlenecks in Mobile LLM Inference

arXiv:2607.05475v1 Announce Type: cross Abstract: Deploying Large Language Models (LLMs) on mobile devices enhances privacy and reduces latency, but is severely bottlenecked by hardware inefficiency.

Local Ai

LLM-Guided Measurement Credibility Correction for Trustworthy Industrial Process Inference

arXiv:2607.06111v1 Announce Type: cross Abstract: Industrial prediction and soft sensing depend on credible input measurements. In field deployment, a predictor may receive biased, delayed, stale, or

local-aiarxiv-cs-ai

Medix: Out-of-Distribution Detection from Unlabeled Wild Data via Robust Gradient Statistics

arXiv:2510.06505v2 Announce Type: replace-cross Abstract: Out-of-distribution (OOD) detection plays a crucial role in ensuring the robustness of machine learning systems deployed in real-world applica

applicationsarxiv-cs-ai

MoWorld: A Flash World Model

arXiv:2607.06216v1 Announce Type: new Abstract: The future of World Models depends not only on scaling model capability, but also on scaling practicality and inference efficiency. High-frame-rate infe

agentsarxiv-cs-cv

Our approach to government and national security partnerships

OpenAI outlines its strategy for collaborating with government agencies and national security institutions, likely covering principles for responsible AI deployment in defense and security contexts. T

safetyopenai

Qdrant Beats Elastic’s DiskBBQ at 2x Throughput, Half the Latency, and 1/3 the Compute

TL;DR Elastic recently published a benchmark claiming that their proprietary, disk-based index (dubbed “DiskBBQ”) delivers up to 7x higher throughput than Qdrant when deployed on nodes with network-at

model-releasesqdrant

SEVRA-BENCH: Social Engineering of Vulnerabilities in Review Agents

arXiv:2606.13757v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly deployed in automated code-review systems, where their approvals can determine which code is mer

SpanUQ: Span-Level Uncertainty Quantification for Large Language Model Generation

model-releasesarxiv-cs-cl

arXiv:2607.05721v1 Announce Type: new Abstract: Uncertainty estimation is essential not only for the trustworthy deployment of large language models (LLMs) but also as a foundation for self-refinement

Industry

Try out Grok 4.5 in Vercel!

Elon Musk announced that Grok 4.5, an AI model developed by xAI, is now available for testing through Vercel, a popular platform for deploying web applications. This release likely allows developers t

industryelon-musk--x

Hardware

UBEP: Re-architecting Expert Parallelism Communication Library for Production Superpods

arXiv:2607.06202v1 Announce Type: cross Abstract: The deployment of Mixture-of-Experts (MoE) models on production high-bandwidth superpods, such as NVIDIA's NVL72/576 and Huawei's CloudMatrix384, intr

hardwarearxiv-cs-ai

VisCoP: Visual Probing for Video Domain Adaptation of Vision Language Models

model-releasesarxiv-cs-cv

arXiv:2510.13808v2 Announce Type: replace Abstract: Large Vision Language Models (VLMs) excel at general visual reasoning but experience significant performance degradation when deployed in novel doma

When Assisting One Disempowers Another

arXiv:2511.04177v2 Announce Type: replace Abstract: Personal AI agents are increasingly deployed in shared environments, where their actions affect not just the primary user they are assisting, but by

agentsarxiv-cs-ai

When Does Tool Use Increase the Expressive Power of Finite-Precision Recurrent Models?

arXiv:2607.06155v1 Announce Type: cross Abstract: Modern sequence models are increasingly deployed as agents that interleave token generation with calls to external tools. We give an exact, architectu

agentsarxiv-cs-cl

Hardware

AI Innovators Adopt NVIDIA Vera — Why Max Single-Threaded CPU at Scale Matters

Max single-threaded CPUs at scale are a new category of CPUs built for the agentic AI era. Across the creation and deployment of an agentic system, the CPU is on the critical path for reasoning, respo

hardwarenvidia-blog

Aligning Language Models with Selective Prediction

arXiv:2607.03528v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as critical decision-making components in high-stakes real-world AI systems, rendering LLM reli

safetyarxiv-cs-ai

Alleviating Sparse Rewards by Modeling Step-Wise and Long-Term Sampling Effects in Flow-Based GRPO

arXiv:2602.06422v2 Announce Type: replace Abstract: Deploying GRPO on Flow Matching models has proven effective for text-to-image generation. However, existing paradigms typically propagate an outcome

Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL

arXiv:2607.03833v1 Announce Type: cross Abstract: While Large Language Models (LLMs) have achieved remarkable success in Text-to-SQL tasks, their deployment in real-world environments is hindered by l

applicationsarxiv-cs-ai

CCFM: Collision-Constrained Flow Matching for Safety-Critical Scenario Generation

arXiv:2607.04451v1 Announce Type: new Abstract: Evaluation of autonomous vehicle (AV) planners in safety-critical closed-loop simulation is essential for real-world deployment. However, generating con

safetyarxiv-cs-cv

Consistent but Miscalibrated: Evaluating LLM Limitations for Risk Communication in Natural Language

arXiv:2607.03882v1 Announce Type: cross Abstract: LLMs are increasingly deployed as post-hoc explainers of AI-generated outputs, yet it remains unclear whether they can reliably communicate probabilis

researcharxiv-cs-ai

Denoised Conformal Alignment for Reliable Selection of Conditional Average Treatment Effect Predictions

arXiv:2607.03161v1 Announce Type: cross Abstract: In selective deployment, practitioners act only on a model-chosen subset of individuals based on predicted conditional average treatment effects, but

safetyarxiv-cs-lg

Distill Where the Student Goes: Teacher-Regularized RL for English-Evidence Cross-Lingual RAG

arXiv:2607.02966v1 Announce Type: new Abstract: Cross-lingual retrieval-augmented generation (RAG) is often deployed in an English-evidence regime, where users query in diverse languages but retrieved

safetyarxiv-cs-cl

EdgeBench: Unveiling Scaling Laws of Learning from Real-World Environments

arXiv:2607.05155v1 Announce Type: new Abstract: Pretraining scaling laws reveal that model capability improves predictably with data and compute. But learning from real world environments after deploy

agentsarxiv-cs-cl

Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing

arXiv:2607.04921v1 Announce Type: cross Abstract: Deep learning algorithms are notorious for their high carbon footprint and computational demands that limit their deployment on edge devices and raise

agentsarxiv-cs-ai

ExpoMotion: A Large-Scale Benchmark and A Householder Projection Network for Multi-Exposure Fusion

model-releasesarxiv-cs-cv

arXiv:2607.03110v1 Announce Type: new Abstract: Multi-Exposure Fusion (MEF) effectively extends dynamic range, but practical deployment is hindered by motion-induced ghosting and the scarcity of high-

From Arithmetic to Logic: The Resilience of Logic and Lookup-Based Neural Networks Under Parameter Bit-Flips

arXiv:2603.22770v2 Announce Type: replace-cross Abstract: The deployment of deep neural networks (DNNs) in safety-critical edge environments necessitates robustness against hardware-induced bit-flip e

GeoSAM-Lite: A Lightweight Foundation Model for Onboard Remote Sensing Segmentation

arXiv:2607.03760v1 Announce Type: new Abstract: The deployment of large-scale foundation models like Segment Anything Model (SAM) on resource-constrained Earth observation platforms is hindered by pro

Hope for the Best, Prepare for the Worst: Occlusion-Aware Contingency Planning for Autonomous Vehicles

arXiv:2607.03155v1 Announce Type: new Abstract: The deployment of autonomous vehicles in urban environments introduces significant safety challenges, particularly in scenarios with occlusions, where c

safetyarxiv-cs-ro

How many labels do you need? A decision framework for cross-habitat marine species recognition

model-releasesarxiv-cs-cv

arXiv:2607.02559v1 Announce Type: new Abstract: Automated image recognition is increasingly used to scale ecological monitoring beyond manual annotation, yet ecologists lack evidence-based guidance on

Hugging face goes agentic future ish and you can launch jobs to optimize kernels with AI agents https://huggingface.co/blog/revamped-kernels

Hugging Face has introduced agentic capabilities that allow users to deploy AI agents to automatically optimize computational kernels, representing a shift toward more autonomous AI-assisted developme

agentsclem-delangue--x

Industry

Hugging Face Jobs sounds like an incredible addition to LeRobot🤗 https://huggingface.co/docs/lerobot/v0.6.0/hardware_guide#hugging-face-job…

Hugging Face Jobs integration with LeRobot enables users to run robotics tasks and training jobs on Hugging Face's infrastructure, streamlining the deployment and execution of robot learning models. T

industryclem-delangue--x

Tools

Hugging Face Models on Foundry Managed Compute

This article describes how to use Hugging Face models with Microsoft's Foundry Managed Compute infrastructure, likely covering integration steps, deployment options, and the benefits of running open-s

toolshugging-face

Local Ai

Kairos: A Regret-Aware Native World-Action Model Stack for Physical AI

arXiv:2606.16533v3 Announce Type: replace Abstract: We introduce extbf{Kairos}, a regret-aware native world-action model stack for Physical AI. Kairos is motivated by the view that a physical world mo

local-aiarxiv-cs-ai

karl. -- A Research Vehicle for Automated and Connected Driving

arXiv:2602.08842v3 Announce Type: replace-cross Abstract: As highly automated driving is transitioning from single-vehicle closed-access testing to commercial deployments of public ride-hailing in sel

applicationsarxiv-cs-ro

Knowing When Not to Answer: Lightweight KB-Aligned OOD Detection for Safe RAG

arXiv:2508.02296v3 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) systems are increasingly deployed in high-stakes domains, where safety depends not only on how a system answers

safetyarxiv-cs-cl

Layout-independent actuation allocator for fin-actuated marine robots

arXiv:2607.03204v1 Announce Type: new Abstract: In this study, we propose a layout-independent control allocator capable of zero-shot deployment across diverse actuator configurations. The proposed me

applicationsarxiv-cs-ro

Leveraging Pathology Co-occurrence for Test-Time Adaptation in Chest X-Ray Diagnosis

arXiv:2607.03715v1 Announce Type: new Abstract: Medical imaging models often degrade when deployed at new clinical sites due to differences in imaging equipment, protocols, and patient populations. Te

LLM-Driven CI-CD Workflow Intelligence for Cyber Systems Engineering

arXiv:2607.04579v1 Announce Type: cross Abstract: CI/CD workflows have become executable operational policy: they decide what gets built, tested, released, and deployed, and they mediate how maintaine

MACS: Measurement-Aware Consistency Sampling for Inverse Problems

arXiv:2510.02208v3 Announce Type: replace-cross Abstract: Diffusion models have emerged as powerful generative priors for solving inverse imaging problems. However, their practical deployment is hinde

Medi-Gemma: A Hybrid Clinical Decision Support System Integrating Deterministic EMR Analytics and Retrieval-Augmented Generation

arXiv:2607.04907v1 Announce Type: new Abstract: Deploying Large Language Models (LLMs) in high-stakes clinical settings remains limited by structural hallucinations, weak deterministic reasoning over

Local Ai

Not Every Sync Is Safe: Calibrated DiLoCo Scheduling for Shared AI Infrastructure

arXiv:2607.02544v1 Announce Type: cross Abstract: DiLoCo-style training reduces communication by letting learner islands train locally before occasional outer synchronization, making it attractive for

local-aiarxiv-cs-ai