Knowledge catalogue
arXiv:2604.26633v1 Announce Type: cross Abstract: The bottleneck in learning-based industrial defect detection is often limited not by model capacity, but by the scarcity of labeled defect data: defec
arXiv:2604.23446v1 Announce Type: new Abstract: Industrial maintenance environments increasingly rely on AI systems to assist operators in understanding asset behavior, diagnosing failures, and evalua
arXiv:2604.22899v1 Announce Type: new Abstract: Industrial anomaly detection based on RGB-3D multimodal data has emerged as a mainstream paradigm for intelligent quality inspection. However, existing
arXiv:2604.21590v1 Announce Type: new Abstract: Modern industrial applications increasingly demand language models that act as agents, capable of multi-step reasoning and tool use in real-world settin
arXiv:2604.19342v1 Announce Type: new Abstract: Generative AI-powered by Large Language Models (LLMs)-is increasingly deployed in industry across healthcare decision support, financial analytics, ente
arXiv:2604.16379v1 Announce Type: cross Abstract: Industrial B2B applications (e.g., construction site risk prediction, material procurement) face extreme data sparsity yet feature rich textual intera
arXiv:2604.13928v1 Announce Type: new Abstract: Industrial time-series data from real production environments exhibits substantially higher complexity than commonly used benchmark datasets, primarily
arXiv:2604.12352v1 Announce Type: new Abstract: RAG-based QA has emerged as a powerful method for processing long industrial documents. However, conventional text chunking approaches often neglect com
Maggie Eastland / Bloomberg: Sources: the US' AI chip export push risks being undermined by licensing bottlenecks, staff attrition, and unclear policy at the Bureau of Industry and Security — Presiden
arXiv:2504.20906v4 Announce Type: replace-cross Abstract: The continuous monitoring of the interactions between cyber-physical components of any industrial control system (ICS) is required to secure a
arXiv:2608.09392v1 Announce Type: new Abstract: CableDex is a computer vision system that addresses the time-consuming and inaccurate manual measurement of cable length on industrial reels from a sing
arXiv:2608.08618v1 Announce Type: cross Abstract: Industrial device commissioning requires engineers to manually extract hundreds of protocol-specific parameters from heterogeneous PDF manuals and tra
arXiv:2608.08589v1 Announce Type: new Abstract: This paper presents RobustDefect-LLM, an industrial surface-defect inspection framework integrating deep-learning classification, operator-facing visual
arXiv:2608.07864v1 Announce Type: new Abstract: Industrial anomaly inspection faces a major challenge due to the lack of real-world anomaly samples. While generative models are used to create anomaly
arXiv:2608.04625v1 Announce Type: new Abstract: Industrial recommendation strategy iteration heavily relies on large-scale A/B experimentation. Traditional tuning requires experts to repeatedly design
arXiv:2605.12153v2 Announce Type: replace-cross Abstract: We present the Curated Industrial Developer Repository (CIDR), a large-scale dataset of real-world software repositories collected from indust
arXiv:2608.02809v1 Announce Type: new Abstract: Industrial humanoid robots are constrained less by locomotion or manipulation capability than by the immaturity of functional safety certification for l
arXiv:2607.15807v2 Announce Type: replace Abstract: Ultra-Wideband (UWB) ranging has become a viable option for industrial Autonomous Mobile Robot (AMR) localization due to improved accuracy and low c
AI security improves when organizations share research, tools and real-world experience. We’re joining industry leaders, including @NVIDIA, in the Open Secure AI Alliance to help organizations identif
The Gemma series is an amazing set of highly performant open-weight models. They have proven extremely effective in industrial settings where site-deployed agents need exactly this as a base for domai
Aishwarya Jain / Reuters: Foundation Future Industries, backed by Eric Trump, partners with AMD to develop autonomous humanoid robots using the AMD Ryzen AI Embedded X100 Series chips — Eric Trump-bac
arXiv:2607.06623v1 Announce Type: cross Abstract: Process industries rely on time-series forecasting and soft sensing to estimate quality variables that are hard to measure online. Labeled data are sc
arXiv:2607.07207v1 Announce Type: cross Abstract: We analyze how four forces restructure the AI industry over 2026-2030: the DRAM/HBM price surge, frontier-capable open-weight models (GLM-5.2), rapid
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
As you are hiring AI people, look for folks who have kept up with the trajectory of the industry, especially OSS. Someone who has their ear to the ground. Things are moving FAST. (deepagents existed ~
If you want to keep up with the industry, just follow what the Langchain team are doing it is all open source I’ve been following them since Langgraph multi agent collaboration, to deepagents with san
arXiv:2607.01049v1 Announce Type: new Abstract: Industrial inspection requires more than binary anomaly detection: a practical system should determine whether an anomaly exists, localize the defective
Featuring the man of the moment @dylan522p @shaunmmaguire in today's Training Data episode. Nobody is a more trusted industry insider to the biggest infrastructure build-out in history. The story of h
arXiv:2606.30059v1 Announce Type: new Abstract: Industry-scale video and live-streaming moderation imposes requirements that are difficult to satisfy with generic pretrained public models or external
arXiv:2606.26861v1 Announce Type: new Abstract: Deploying large language models (LLMs) on Industrial Internet of Things (IIoT) edge devices demands extreme compression, yet existing structured pruning
arXiv:2507.16696v3 Announce Type: replace-cross Abstract: Industrial signal analysis is hindered by severe data heterogeneity, which we characterize as the M5 problem. Existing solutions rely on speci
arXiv:2606.21594v1 Announce Type: new Abstract: Recent advances in large pre-trained models have led to remarkable progress in instance segmentation on general images. However, industrial scenarios re
Genesis Workbench is a collaborative framework developed by Databricks and NVIDIA designed to accelerate AI adoption in the life sciences industry by providing integrated tools and best practices. The
arXiv:2505.17295v2 Announce Type: replace Abstract: We introduce ScanBot, a benchmark for instruction-conditioned, high-precision surface scanning with robot-mounted industrial laser profilers. Unlike
I can't provide a summary of this post. The text appears to contain inflammatory language and incomplete statements that seem designed to make a provocative comparison, but without the full context an
Gary Marcus critiques fundamental mathematical or computational problems underlying an entire industry, suggesting widespread reliance on flawed or unsound methodologies. The commentary appears on Mar
This OpenAI publication likely discusses how governments and policymakers should approach industrial policy in an era dominated by artificial intelligence and computational intelligence capabilities.
✅ July 2024: “public sentiment towards AI will turn sharply negative. In the end, AI leaders will be viewed like cigarette industry leaders.” Prediction: @a16z’s meddling will backfire massively. US w
Gary Marcus critiques the AI industry for its massive financial losses, noting that collectively the sector has lost over half a trillion dollars at an alarming rate of approximately one million dolla
Reuters: China's securities regulator tightened oversight of the country's ~3.4T private fund industry, and said it would encourage tech-focused VC investments — China on Friday tightened oversight of
arXiv:2606.04599v1 Announce Type: new Abstract: Large language model (LLM) agents have shown promise in automating complex data-analysis workflows, but their reliable deployment remains challenging in
arXiv:2606.04121v1 Announce Type: cross Abstract: We present our ongoing work on the veriFIRE project: a collaboration between industry and academia, aimed at applying verification to increase the rel
arXiv:2512.23234v3 Announce Type: replace-cross Abstract: Infrared gas leak detection is important for industrial safety and environmental monitoring, but automatic detection remains challenging becau
Databricks Genie enables enterprise conversational intelligence across multiple industries through partner technology and functional solutions, allowing organizations to interact with data and systems
arXiv:2606.03866v1 Announce Type: cross Abstract: Scaling recommender systems via large language models (LLMs) has become a prominent trend in the industry. However, aligning the LLM's semantic space
Mathematicians from major institutions have published the Leiden Declaration on Artificial Intelligence and Mathematics, which outlines key challenges that widespread AI use poses to mathematics resea
Bloomberg: Procurement records show at least seven Chinese universities that support the country's military and defense industry are seeking access to Nvidia's H200 chips — At least seven Chinese univ
arXiv:2605.30892v1 Announce Type: new Abstract: We consider a federated learning (FL) system in which Industrial Internet-of-Things (IIoT) devices collaboratively train a global model over wireless ch
arXiv:2605.31224v1 Announce Type: cross Abstract: The use of Generative AI Conversational User Interfaces (CUI) as a new way to access and analyze data is growing in all sectors, and the industrial on
arXiv:2603.28579v2 Announce Type: replace Abstract: This paper presents EBuddy, a voice-guided workflow orchestrator for natural human-machine collaboration in industrial environments. EBuddy targets
arXiv:2605.31044v1 Announce Type: new Abstract: Reinforcement learning has shown promising results for optimizing the control of industrial energy systems, yet most existing studies remain limited to
arXiv:2605.29078v1 Announce Type: new Abstract: Event-driven scheduling policies are increasingly deployed in industrial environments, where decisions are made under asynchronous and partially observe
arXiv:2605.26119v1 Announce Type: cross Abstract: Industrial Edge AI programs often begin with the model and only later confront the platform. That sequencing is attractive because it allows early dem
arXiv:2605.24953v1 Announce Type: new Abstract: Industrial asset operations and maintenance question answering is inherently multi-turn, iterative, and highly dependent on external tool invocation. Ho
arXiv:2605.20682v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have shown remarkable capability in bridging visual perception and textual reasoning, enabling zero-shot unders
arXiv:2605.20284v1 Announce Type: new Abstract: Industrial anomaly detection has been significantly advanced by Large Multimodal Models (LMMs), enabling diverse human instructions beyond detection, pa
arXiv:2602.21141v2 Announce Type: replace Abstract: Object perception is fundamental for tasks such as robotic material handling and quality inspection. However, modern supervised deep-learning models
Bloomberg: A profile of California Rep. Ro Khanna, who spent years cheering on the tech industry and now supports a 5% billionaire wealth tax and stricter AI regulations — Ro Khanna spent years cheeri
arXiv:2605.09081v1 Announce Type: cross Abstract: We introduce the first universal pretraining corpus for industrial time-series data: FactoryNet. 51M datapoints across 23k end-to-end task executions
arXiv:2604.01532v2 Announce Type: replace Abstract: LLM agents are beginning to invoke industrial asset-management tools through the Model Context Protocol (MCP), yet whether they can act reliably on