adaptive machine learning

In-Depth Analysis: Core Definitions and Underlying Differences Between Sports AI and AI Agents

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In-Depth Analysis: Core Definitions and Underlying Differences Between Sports AI and AI Agents

Sports AI and Sports AI Agents are not two separate concepts, but rather“basic applications” and“advanced forms” that are interrelated—— Sports AI Agents are an integrated and upgraded version of Sports AI with core differences focused on“autonomy” and“systemic synergy”, which will be visually presented through“definitions+ core dimension comparisons+ evolutionary logic” to illustrate the connections and differences … Read more

From 2% to Continuous Evolution: Unveiling the Four-Stage Leap of Customer Service AI Agents

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From 2% to Continuous Evolution: Unveiling the Four-Stage Leap of Customer Service AI Agents

If we were to list the department most often overlooked by enterprises, yet most capable of reflecting customer experience, it would undoubtedly be the customer service center. In industries such as telecommunications, banking, and the internet, customer service centers often play the role of “gatekeepers of customer experience.” They must address questions from all directions … Read more

TaiLing Microelectronics RF SoC Chips Empower Machine Learning and Artificial Intelligence, TL721X and TL751X Usher in a New Era of AI Applications

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TaiLing Microelectronics RF SoC Chips Empower Machine Learning and Artificial Intelligence, TL721X and TL751X Usher in a New Era of AI Applications

Driven by the continuous wave of technological advancement, TaiLing Microelectronics has achieved new breakthroughs in chip technology with the recent launch of the TL721X and TL751X. These chips are equipped with highly integrated self-developed IP that enhances edge computing capabilities and leads the industry with their ultra-low power chip design. Both chips support Machine Learning … Read more

Facebook Open Sources Chatbot Blender, Enhanced with 9.4 Billion Parameters for More ‘Human-Like’ Interaction

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Facebook Open Sources Chatbot Blender, Enhanced with 9.4 Billion Parameters for More 'Human-Like' Interaction

作者 | Kyle Wiggers 编译 | Sambodhi 策划 & 编辑 | 刘燕 不久前，Facebook 开源了号称是全球最强大的聊天机器人 Blender，它标志着 Facebook 在 AI 领域的新进展：新的聊天机器人不仅解决了此前聊天机器人的固有缺点，更是拥有史无前例的 94 亿个参数。 Recently, Facebook open-sourced what it claims to be the world’s most powerful chatbot, Blender, marking a new advancement for Facebook in the field of AI. This new chatbot not only addresses the inherent shortcomings … Read more

2020 ARM CMSIS Roadmap: Release of Machine Learning Library, Enhanced DSP Library, Support for M55, and Launch of CMSIS-TFM and CMSIS-Build

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2020 ARM CMSIS Roadmap: Release of Machine Learning Library, Enhanced DSP Library, Support for M55, and Launch of CMSIS-TFM and CMSIS-Build

The CMSIS software package is primarily used for Cortex-M and Cortex-A5/A7/A9. Over the past two years, CMSIS has made significant progress, especially with CMSIS-RTOS, CMSIS-Driver, and CMSIS-DSP, which have become quite impressive. This year, we will continue to advance the CMSIS ecosystem, particularly in the areas of secure IoT, signal processing, and machine learning. 2020 … Read more

From Dataset to Inference on Board: How a Complete eIQ NPU Project Runs

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From Dataset to Inference on Board: How a Complete eIQ NPU Project Runs

This project implements a small yet practical AI demo on the NXP MCX-N947: enabling the MCU to recognize “shoes” or “hats”. Leveraging the training process of the eIQ Portal along with the acceleration capabilities of the NPU, the entire model construction, quantization, and execution process is very smooth. The project itself is not complex but … Read more

What is Edge Artificial Intelligence

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What is Edge Artificial Intelligence

Gongbang·New Ecology of Industrial Interconnection Gongxun 01 Introduction Edge Artificial Intelligence (Edge AI) refers to the development and deployment of artificial intelligence (AI) algorithms and programs on edge devices. It is a form of edge computing characterized by analyzing and processing data near the location where it is generated or collected. In contrast to Edge … Read more

Paper Sharing: Scikit-learn: Machine Learning in Python

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Paper Sharing: Scikit-learn: Machine Learning in Python

Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., … & Duchesnay, É. (2011). Scikit-learn: Machine learning in Python. the Journal of machine Learning research, 12, 2825-2830. Abstract Scikit-learn is a Python module that integrates a variety of advanced machine learning algorithms for medium-scale supervised and unsupervised learning problems. The toolkit aims … Read more

SSNet: A Spectral Unmixing Framework for Enhancing the Qualitative Sensitivity of SERS to Trace Targets in Complex Mixtures

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SSNet: A Spectral Unmixing Framework for Enhancing the Qualitative Sensitivity of SERS to Trace Targets in Complex Mixtures

1 Research Overview 01 Surface-enhanced Raman spectroscopy (SERS) is a powerful spectroscopic-structural correlation technique widely used in fields such as chemistry, biology, and environmental analysis. However, in complex systems, co-adsorption and competitive adsorption of non-target molecules often lead to signal overlap, limiting the accuracy of SERS in the qualitative and quantitative analysis of trace target … Read more

Energy | Empowering Lithium Battery SOC Precision Assessment with EIS Data

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Energy | Empowering Lithium Battery SOC Precision Assessment with EIS Data

Paper S N ◀ Recommended Paper ▶ Equivalent Circuit Models Assist Machine Learning: A New Method for Battery SOC Estimation Based on EIS Data 01 Abstract This paper focuses on the estimation of the state of charge (SOC) of batteries, proposing a lightweight SOC estimation method that combines machine learning with equivalent circuit models, based … Read more