Search: “deployment”

The Illusion of Robustness: Aggregate Accuracy Hides Prediction Flips under Task-Irrelevant Context

model-releasesarxiv-cs-cl

arXiv:2607.12963v1 Announce Type: new Abstract: As large language models (LLMs) grow more capable, they are increasingly deployed in context-rich settings where task inputs are often accompanied by lo

15 Jul 2026

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Vision-Based Dribbling for Humanoid Soccer via Privileged Representation Learning

DGX agent

arXiv:2607.12702v1 Announce Type: new Abstract: Recent advances in humanoid robotics have highlighted the importance of deployable loco-manipulation skills. Dribbling a soccer ball while evading activ

safetyarxiv-cs-ro

15 Jul 2026

How Retail Finance teams are using Agentic AI to protect omni-channel margins

Retail Finance teams are increasingly deploying agentic AI to safeguard omni‑channel margins. These systems automatically monitor sales performance, forecast demand, and adjust pricing or inventory co

agentsdatabricks

14 Jul 2026

Tutorials

Scaling UX testing with Amazon Nova Act: A new approach to user flow analysis

Using generative AI enables parallel execution of comprehensive user flow testing at scale. This solution demonstrates how to build a cloud-deployed UX testing platform that automatically generates te

tutorialsaws-ml-blog

14 Jul 2026

Together AI positions open-weight AI models as the enterprise moat for cost, control and IP

Enterprises racing to deploy AI at scale are discovering that the biggest constraint isn’t model capability anymore — it’s control. As agentic AI moves from experimentation into core business processe

agentssiliconangle

14 Jul 2026

10 GWh of our industrial energy storage products are now operating across Australia! That's equivalent to 160,000 Model Ys. And we're just g…

Tesla has deployed 10 GWh of industrial energy storage products across Australia, a capacity equivalent to powering approximately 160,000 Tesla Model Y vehicles. This milestone reflects the growing ad

industryelon-musk--x

Safety

A Collaborative Reasoning Framework for Anomaly Diagnostics in Underwater Robotics

arXiv:2511.03075v2 Announce Type: replace Abstract: The safe deployment of autonomous systems in safety-critical settings requires a paradigm that combines human expertise with AI-driven analysis, esp

safetyarxiv-cs-ro

Adaptive Generation of Bias-Eliciting Questions for LLMs

arXiv:2510.12857v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are now widely deployed in user-facing applications, reaching hundreds of millions of users worldwide. Despite th

BiSCo-LLM: Lookup-Free Binary Spherical Coding for Extreme Low-Bit Large Language Model Compression

arXiv:2607.08643v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly constrained by memory capacity, weight bandwidth, and checkpoint storage during deployment. Existing low-b

local-aiarxiv-cs-lg

Closing the Null Space: Guidance-Aware Quantization for Classifier-Free Diffusion

model-releasesarxiv-cs-cv

arXiv:2607.08241v1 Announce Type: new Abstract: Deploying classifier-free guidance (CFG) diffusion models under real-world compute budgets requires quantization, yet existing post-training quantizatio

CoCo-Fed: A Unified Framework for Memory- and Communication-Efficient Federated Learning at the Wireless Edge

arXiv:2601.00549v2 Announce Type: replace-cross Abstract: The deployment of large-scale neural networks within the Open Radio Access Network (O-RAN) architecture is pivotal for enabling native edge in

local-aiarxiv-cs-ai

Data Alchemy: Mitigating Cross-Site Model Variability Through Test Time Data Calibration

arXiv:2407.13632v2 Announce Type: replace Abstract: Deploying deep learning-based imaging tools across various clinical sites poses significant challenges due to inherent domain shifts and regulatory

researcharxiv-cs-cv

Eigenvalue Calibration for Semantic Embeddings of Large Language Models

arXiv:2607.08377v1 Announce Type: new Abstract: Uncertainty quantification is central to the reliable deployment of large language models (LLMs), and eigenvalues of semantic embeddings have recently e

applicationsarxiv-cs-lg

FedOPAL: One-Shot Federated Learning via Analytic Visual Prompt Tuning

arXiv:2607.08368v1 Announce Type: new Abstract: With the widespread deployment of basic models in edge intelligence, communication bandwidth has become a core bottleneck restricting the scalability of

researcharxiv-cs-ai

Hugging Face’s CEO on why companies are done renting their AI https://techcrunch.com/2026/07/10/hugging-faces-ceo-on-why-companies-are-done-…

Hugging Face's CEO discusses why enterprises are moving away from renting AI models and services from cloud providers, likely advocating for open-source alternatives or on-premise deployment models. T

industryclem-delangue--x

On Exploring Input Resolution Scaling For Anytime LiDAR Object Detection

arXiv:2607.08391v1 Announce Type: cross Abstract: Making tradeoffs between execution latency and result utility (i.e., anytime computing) for adapting to dynamic operational requirements has been show

agentsarxiv-cs-lg

Overthinking: Amplifying Reasoning Weights to Extract Learned Secrets

arXiv:2607.08173v1 Announce Type: new Abstract: Black box auditing of language models is an essential pre-deployment tool, but it may miss subtle forms of misalignment and hidden information. To bette

researcharxiv-cs-ai

The Illusion of Equivalency: Statistical Characterization of Quantization Effects in LLMs

arXiv:2607.08734v1 Announce Type: new Abstract: Post-training quantization is widely used to deploy large language models in resource-constrained settings, yet its evaluation relies almost exclusively

applicationsarxiv-cs-ai

A Unified Detection Framework for AI-Related Content and Artifacts

arXiv:2607.07527v1 Announce Type: cross Abstract: Artificial intelligence (AI) is a double-edged sword: while it has achieved remarkable success across a wide range of domains, its deployment also cal

researcharxiv-cs-lg

Tutorials

An Adaptive Differentially Private Federated Learning Framework

arXiv:2602.06838v3 Announce Type: replace Abstract: Federated learning enables collaborative model training across distributed clients while preserving data privacy. However, in practical deployments,

tutorialsarxiv-cs-ai

Dual Path Attribution: Efficient Attribution for SwiGLU-Transformers through Layer-Wise Target Propagation

arXiv:2603.19742v2 Announce Type: replace-cross Abstract: Understanding the internal mechanisms of transformer-based large language models (LLMs) is crucial for their reliable deployment and effective

researcharxiv-cs-cl

Enhancing enterprise inference on Amazon SageMaker HyperPod with data capture, Hugging Face, NVMe, and Route 53 integration

In this post, we walk through five capabilities now available in SageMaker HyperPod inference: multi-tier data capture for auditing and model improvement, direct deployment from Hugging Face Hub, loca

local-aiaws-ml-blog

Future Confidence Distillation in Large Language Models

arXiv:2607.07626v1 Announce Type: cross Abstract: Reliable confidence estimation is essential for deploying large language models (LLMs) in confidence-aware systems, where downstream decisions such as

agentsarxiv-cs-ai

Tools

GPT 5.6 Sol, Luna, and Terra now available on AI Gateway

Vercel has made GPT 5.6 models (Sol, Luna, and Terra variants) available through its AI Gateway service, expanding the model options developers can access and deploy through the platform. This update

toolsvercel-blog

Grok is making progress

Elon Musk announced progress updates on Grok, his AI assistant developed by xAI, likely highlighting improvements in the model's capabilities, training, or deployment. The post suggests ongoing develo

industryelon-musk--x

https://ollama.com/blog/all-aboard-open-models

Ollama announced support for running multiple open-source language models locally, emphasizing accessibility and ease of deployment for users who want to use AI models without relying on cloud service

local-aiollama--x

Naming the Concepts Classifiers Rely On: Language-Anchored Decomposition for Faithful Explanation

arXiv:2607.07264v1 Announce Type: new Abstract: Deep neural networks are widely deployed in high-stakes visual applications where interpretability is critical, yet existing explanations face a trade-o

local-aiarxiv-cs-cv

Safety

Progressive Crystallization: Turning Agent Exploration into Deterministic, Lower-Cost Workflows in Production

arXiv:2607.07052v1 Announce Type: cross Abstract: AI agents deployed for IT operations are typically permanent cost centers because every execution requires full LLM inference, even for previously sol

safetyarxiv-cs-ai

Reason Less, Verify More: Deterministic Gates Recover a Silent Policy-Violation Failure Mode in Tool-Using LLM Agents

arXiv:2607.07405v1 Announce Type: new Abstract: Tool-using LLM agents can violate the very policies they are deployed to enforce while appearing to complete the task successfully. In policy-permissive

Robust Federated Learning Under Real-World Client Churn

arXiv:2607.06979v1 Announce Type: new Abstract: Federated Learning (FL) enables training shared models on private, on-device data, but production deployments remain constrained to slow, multi-day refr

local-aiarxiv-cs-lg

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

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

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)

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.

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

Safety

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

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