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Graph Data Prompt (GDP), which introduces specific prompts in graph data for efficiently adapting pre-trained GNNs, has become a mainstream approach to graph fine-tuning learning problem. However, existing GDPs have been respectively designed for distinct graph component (e.g., node features, edge features, edge weights) and thus operate within limited prompt spaces for graph data. To the best of our knowledge, it still lacks a unified prompter suitable for targeting all graph components simultaneously. To address this challenge, in […]

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Many companies are taking a slower, more controlled approach to autonomous systems as AI adoption grows. Rather than deploying systems that act on their own, they are focusing on tools that assist human decision-making and keep control over outputs. This approach is especially clear in sectors where errors carry real financial or legal risk. One example comes from S&P Global Market Intelligence, which builds AI tools into its Capital IQ Pro platform. The system is used by analysts […]

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Running containers on EC2 is not cloud-native. I’m sorry. Here’s what it actually means and the honest checklist to find out where your stack really stands. I’ve sat through a lot of conference talks where companies describe their “cloud-native journey.” The term has been so thoroughly diluted by marketing that it’s become nearly meaningless. Let me offer something more useful: a checklist. Run your stack against it. 1 Are your applications designed for ephemeral infrastructure? Cloud-native: your services […]

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In precision mold manufacturing, the machining of HRC52 hardened steel causes se-vere tool wear and high noise in multi source sensor signals, making accurate remain-ing useful life (RUL) prediction challenging. To address this, we propose a hybrid mod-el that integrates one dimensional deep convolution (DCNN), low resolution self attention (LRSA) with 1D 2D spatiotemporal reconstruction, and a multi channel bidirectional long short term memory network (McBiLSTM). A Gaussian smoothing filter is first applied to denoise the 50 kHz […]

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In precision mold manufacturing, the machining of HRC52 hardened steel causes se-vere tool wear and high noise in multi source sensor signals, making accurate remain-ing useful life (RUL) prediction challenging. To address this, we propose a hybrid mod-el that integrates one dimensional deep convolution (DCNN), low resolution self attention (LRSA) with 1D 2D spatiotemporal reconstruction, and a multi channel bidirectional long short term memory network (McBiLSTM). A Gaussian smoothing filter is first applied to denoise the 50 kHz […]

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Unmanned aerial vehicles (UAVs) have wide application prospects in disaster search and rescue, ecological monitoring and environmental inspection tasks, where target search is a key link to realize autonomous task execution. UAVs often face challenges related to limited onboard computational resources and inefficient environmental coverage when used for target search. To address these issues, this paper proposes an autonomous search method for UAVs based on combined lightweight target detection and coverage path planning. In this method, the target […]

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Unmanned aerial vehicles (UAVs) have wide application prospects in disaster search and rescue, ecological monitoring and environmental inspection tasks, where target search is a key link to realize autonomous task execution. UAVs often face challenges related to limited onboard computational resources and inefficient environmental coverage when used for target search. To address these issues, this paper proposes an autonomous search method for UAVs based on combined lightweight target detection and coverage path planning. In this method, the target […]

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Food and agricultural consumption are responsible for nearly a quarter of the world’s greenhouse gas (GHG) emissions, so eating is a critical element in slowing climate change. Accurate estimation of meals carbon price is necessary to promote sustainable food intakes, but current methods rely heavily on self-administered dietary questionnaires, nutrition databases, or manual input, which are time-consuming, subject to errors, and difficult to scale up. In response to these challenges, we provide a novel machine learning model that […]

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Food and agricultural consumption are responsible for nearly a quarter of the world’s greenhouse gas (GHG) emissions, so eating is a critical element in slowing climate change. Accurate estimation of meals carbon price is necessary to promote sustainable food intakes, but current methods rely heavily on self-administered dietary questionnaires, nutrition databases, or manual input, which are time-consuming, subject to errors, and difficult to scale up. In response to these challenges, we provide a novel machine learning model that […]

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I spent weeks debugging an agent that kept “forgetting” contexts mid-task. The agent had access to 1M context window, which should have been enough. But it wasn’t. It would repeat steps it had already completed, refetch data it had already seen, and occasionally ignore tool outputs that were technically still in the context. The logs looked fine. The context was huge. Nothing obvious was broken. The problem was not context window capacity. The problem was me treating the […]

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