Knowledge catalogue
arXiv:2608.12259v1 Announce Type: new Abstract: Financial forecasting models are typically developed in full precision, yet production deployment often requires low-precision inference to reduce memor
arXiv:2607.13172v1 Announce Type: new Abstract: We address the problem of safely training an agent policy and deploying a good and safe policy, in settings where the environment dynamics are unknown a
arXiv:2607.12755v1 Announce Type: cross Abstract: AI-enabled systems are seeing increasing deployment across numerous domains, with many being 'black boxes' with respect to core functions and capabili
Written by: Corné de Jong Introduction Mandiant security assessments frequently identify publicly exposed serverless applications that lack authentication, often as a result of specific business requi
Google Kubernetes Engine (GKE) managed DRANET supports both GPUs and TPUs. There are several configurations to use this implementation, including standard cluster (where you have full control) and aut
If you’re an IT leader, you might be getting a lot of questions about how to build and deploy agents. The pressure to move fast is intense, but the engineering reality is incredibly complex. Where do
arXiv:2607.02501v1 Announce Type: new Abstract: Embodied AI models now span vision-language-action (VLA) models and world-action models (WAMs), but practical deployment remains fragmented across model
arXiv:2606.22873v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly deployed in consumer, medical, financial, and enterprise applications. This broad deployment expands the
arXiv:2606.22338v1 Announce Type: cross Abstract: Robots deployed in realistic settings will accumulate experience across many sessions and tasks over their deployment. The robot's tasks may often req
You've got a working prototype in Google AI Studio. A React frontend, a Node.js backend, maybe a database. Now you want a live URL to share with your team, your users, or a friend who wants to try it.
arXiv:2605.21560v1 Announce Type: new Abstract: Deploying neural networks on microcontroller units (MCUs) is critical for edge intelligence but remains challenging due to tight memory, storage, and co
arXiv:2605.16882v1 Announce Type: new Abstract: Low-resource deployment constraints have made model quantization essential for deploying neural networks while preserving performance. Meanwhile, model
At Google Cloud Next ‘26, we unveiled the blueprint for the Agentic Enterprise, sharing our eighth-generation TPUs, Gemini Enterprise Agent Platform, a fully reimagined Agentic Data Cloud, Workspace I
arXiv:2605.16281v1 Announce Type: cross Abstract: Artificial intelligence systems are increasingly deployed in high-stakes domains, yet it remains unclear whether existing governance frameworks ensure
Executive Summary Since our February 2026 report on AI-related threat activity, Google Threat Intelligence Group (GTIG) has continued to track a maturing transition from nascent AI-enabled operations
Twintivo developed a system using three asynchronous deep agents with LangChain to reduce operational downtime in manufacturing facilities. The approach leverages asynchronous processing to enable mul
Deep Agents middleware is a great invention. You get a really strong default harness and a clean way to customize every part of it DeepAgents - it’s all you need - batteries included if you want, but
everyones gonna be here! I’ll be in San Francisco from May 9-16 for @LangChain Interrupt 🦜 If you’re around, DM me, I’d love to chat about applied AI, agents, and running agentic systems in production
arXiv:2604.20420v1 Announce Type: cross Abstract: AI research often emphasizes model design and algorithmic performance, while deployment and inference remain comparatively underexplored despite being
arXiv:2604.17650v1 Announce Type: new Abstract: LLMs are increasingly deployed in dynamic, real-world settings, where the distribution of user prompts can shift substantially over time as new tasks, p
This post discusses the integration of LangChain's Deep Agents framework into Toad, noting that the implementation functioned without requiring significant modifications or troubleshooting. The entry
New version of Toad has landed. Added @LangChain Deep agents and https://crow-ai.dev/ The diff view has some additional settings to play with. You can enable annotations and line wrapping if you don't
Harrison Chase demonstrates creating a custom CLI agent using LangChain's deep agent functionality, highlighting the ease and simplicity of building autonomous agents with modern frameworks. The post
Introduction Advances in AI model-powered exploitation have demonstrated that general-purpose AI models can excel at vulnerability discovery, even without being purpose-built for the task. Eventually,
Harrison Chase, co-founder of LangChain, discusses the concept of the agent 'harness' as the core architectural component where an agent's decision-making logic and identity reside. The post expresses
the team spent a lot of time totally revamping docs with care❤️ ofc for LangChain+deepagents DX but lots of ppl use them as general learning guides on patterns across Agents, Context Eng, Infra, Prod,
Agent-generated code enhances development speed but introduces new risks because agents lack awareness of a production environment's real-world constraints (e.g., traffic patterns, capacity, or fai...
A developer open-sourced an agent architecture specifically designed for long-horizon tasks, positioning it as addressing gaps in existing tools. Manus is a cloud-based autonomous AI agent built f...
Sub-agent Model Selection — Different Tasks, Different Models Your main agent runs Qwen3.6-Plus for quality. But not every subtask needs a flagship model. Now sub-agents can use a different model. Cre
arXiv:2610.19178v1 Announce Type: new Abstract: Before deploying clinical prediction models, their reliability must be assessed to ensure safe use. Errors may arise from distribution shifts between tr
arXiv:2610.07026v1 Announce Type: new Abstract: The Offline AI Modules workstream enables practical, low-power, and community-accessible deployment of voice-first AI systems that operate fully offline
arXiv:2610.03662v1 Announce Type: new Abstract: Deploying a new decision policy creates a cold-start problem for prediction models whose targets depend on the policy's actions: historical observations
Whether you’re launching microservices in response to sudden traffic spikes, deploying new software releases, or scaling up application replicas, pod startup time is critical to maintaining a fast, re
arXiv:2609.39537v1 Announce Type: cross Abstract: The EU AI Act (Art. 27) requires deployers of high-risk AI systems to conduct Fundamental Rights Impact Assessments (FRIAs) before deployment, yet the
arXiv:2609.39964v1 Announce Type: new Abstract: Multi-modal integrated sensing and communication (ISAC) enables environmental perception and reliable connectivity for intelligent wireless networks. Da
arXiv:2609.14274v1 Announce Type: new Abstract: Deploying deep neural networks in real-world settings requires models that are both compact and robust to common corruptions. However, at deployment-rel
Fascinating paper from Anthropic and colleagues. They study whether models can tell when they are being tested. It turns out that capable models can tell when they are being tested rather than deploye
Moving Large Language Models (LLMs) from experimental prototypes into enterprise production exposes a critical truth: your infrastructure dictates both your performance ceilings and your unit economic
arXiv:2609.01683v1 Announce Type: new Abstract: Vision models deployed on microcontrollers (MCUs) are quantized to integer-only arithmetic and run in inference-only runtimes that do not carry the mach
arXiv:2503.00287v3 Announce Type: replace Abstract: Reinforcement learning (RL) has achieved remarkable success in various robotic tasks; however, its deployment in real-world scenarios, particularly
arXiv:2608.30908v1 Announce Type: new Abstract: Fine-tuning Low-bit models aims to adapt a quantized model while keeping the final deployed checkpoint in the same low-bit form. This setting is practic
Presented by Tata Communications Enterprises are deploying AI agents, voice AI, and automation across messaging, voice, and digital channels faster than the architecture meant to support it. Most of t
arXiv:2602.14255v2 Announce Type: replace Abstract: Industrial robots are increasingly deployed in construction and manufacturing tasks, where the deployment of end-to-end visuomotor policies is chall
arXiv:2608.19425v1 Announce Type: cross Abstract: Reliable performance evaluation is a central bottleneck for deploying robot-learning policies in real-world conditions. Real-world testing is faithful
arXiv:2608.15591v1 Announce Type: new Abstract: Large Language Model (LLM) agents deployed in production environments face a fundamental tension: the agent's behavior is frozen at deployment time, whi
arXiv:2608.13076v1 Announce Type: new Abstract: Large Language Models (LLMs) have achieved remarkable success in natural language understanding and generation, but their deployment is constrained by h
For organizations deploying AI agents at scale, there’s often a critical divide between structured and unstructured data. While large language models (LLMs) excel at parsing text documents, emails, an
arXiv:2608.04706v1 Announce Type: new Abstract: Monitoring of offshore wind energy infrastructure life cycles, especially during the deployment phase, is an important contribution for stakeholders to
As a market leader in enterprise agentic automation and business orchestration, UiPath is helping to pioneer an industry shift toward agentic AI. With it, the company is deploying autonomous agents to
Startups are at the forefront of tackling some of the world’s most complex challenges, especially in cybersecurity, where new ideas and adaptability are always needed. These companies are embracing AI
arXiv:2607.00673v1 Announce Type: new Abstract: Robots deployed in unstructured outdoor environments often plan from scene reconstructions collected before deployment because operators cannot remap la
Anthropic's agentic coding tool Claude Code has worked with Google Cloud for a while now. An individual developer could easily point CLAUDE_CODE_USE_VERTEX=1 at a Google Cloud (GCP) project, grant the
arXiv:2605.27729v3 Announce Type: replace-cross Abstract: The 2024-2025 Nobel and Turing awards recognised AI and quantum science simultaneously. Yet no deployed system has brought these streams toget
The Federal Communications Commission (FCC) granted Amazon Leo a waiver of its July 2026 satellite deployment deadline, while retaining its July 30, 2029 final deployment deadline. Under the condition
arXiv:2606.07890v1 Announce Type: new Abstract: Performative prediction studies feedback loops that arise when predictive models are deployed in consequential domains. In these settings, deploying a m
arXiv:2606.04317v1 Announce Type: cross Abstract: Deep neural networks are increasingly deployed across heterogeneous and partially untrusted environments, where models are distributed through cloud s
arXiv:2605.31487v1 Announce Type: new Abstract: Deploying computer vision models in Warehouse Facilities traditionally requires extensive resources for camera mounting, image collection, annotation, t
Application owners and platform engineers have long faced a difficult choice: spend excessively by over-provisioning to guarantee quick startups, or minimize costs but endure slow cold starts. We are
arXiv:2605.20270v1 Announce Type: new Abstract: A local specialist LLM, fine-tuned with reinforcement learning from verifiable rewards (RLVR) on operator-local data, is installed in a regulated organi
arXiv:2605.16255v1 Announce Type: cross Abstract: Demand for AI accelerators is rapidly increasing rack power density, with projections approaching 1MW per deployment by 2027. This poses a major chall