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Port Tanjung Pelepas turns to AI-powered management system

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The Port of Tanjung Pelepas (PTP) in Malaysia has entered into an agreement to deploy Innovez One's AI-powered Port Management Information System (PMIS) to improve efficiency and optimise its scheduling. Port information management systems provider Innovez One said it will supply its MarineM solution to PTP to aid the port in its journey towards digitalisation. The system's integration at the port is scheduled by the early third quarter of 2022. MarineM will provide an interface where agents can register their vessels and order services to support arrivals such as supplies, logistics and marine services. Using algorithms powered by artificial intelligence (AI) and machine learning, MarineM's planning module will automatically manage schedules and dispatch resources.


AI Makes Strides in Virtual Worlds More Like Our Own

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In 2009, a computer scientist then at Princeton University named Fei-Fei Li invented a data set that would change the history of artificial intelligence. Known as ImageNet, the data set included millions of labeled images that could train sophisticated machine-learning models to recognize something in a picture. The machines surpassed human recognition abilities in 2015. Soon after, Li began looking for what she called another of the "North Stars" that would give AI a different push toward true intelligence. She found inspiration by looking back in time over 530 million years to the Cambrian explosion, when numerous land-dwelling animal species appeared for the first time.


7 Lessons I've Learnt From Deploying Machine Learning Models Using ONNX

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In this post, we will outline key learnings from a real-world example of running inference on a sci-kit learn model using the ONNX Runtime API in an AWS Lambda function. This is not a tutorial but rather a guide focusing on useful tips, points to consider, and quirks that may save you some head-scratching! The Open Neural Network Exchange (ONNX) format is a bit like dipping your french fries into a milkshake; it shouldn't work but it just does. ONNX allows us to build a model using all the training frameworks we know and love like PyTorch and TensorFlow and package it up in a format supported by many hardware architectures and operating systems. The ONNX Runtime is a simple API that is cross-platform and provides optimal performance to run inference on an ONNX model exactly where you need them: the cloud, mobile, an IoT device, you name it!


可視化神經網路:Grad-CAM小簡介 -- 論文筆記(3)Grad-CAM的活用

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主要分為三個部分:診斷原有神經網路及資料集、圖片細部構造解讀,和物件捕捉/VQA任務。. “可視化神經網路:Grad-CAM小簡介 — 論文筆記(3)Grad-CAM的活用” is published by Martin Huang.


Deep Learning : Baby Steps

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This list goes on and on and never stops. This is what every single DL aspirant has heard in the past and marvelled at the complexity of it. I entered a DL workshop and the mentor asked, " Does anyone know what is a perceptron? I thought I had missed a character in the Transformers series.


Variational quantum evolution equation solver - Scientific Reports

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Variational quantum algorithms offer a promising new paradigm for solving partial differential equations on near-term quantum computers. Here, we propose a variational quantum algorithm for solving a general evolution equation through implicit time-stepping of the Laplacian operator. The use of encoded source states informed by preceding solution vectors results in faster convergence compared to random re-initialization. Through statevector simulations of the heat equation, we demonstrate how the time complexity of our algorithm scales with the Ansatz volume for gradient estimation and how the time-to-solution scales with the diffusion parameter. Our proposed algorithm extends economically to higher-order time-stepping schemes, such as the Crank–Nicolson method. We present a semi-implicit scheme for solving systems of evolution equations with non-linear terms, such as the reaction–diffusion and the incompressible Navier–Stokes equations, and demonstrate its validity by proof-of-concept results.


5 Top Trends in AI Robotics in 2022

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In the coming years, broad exploration will occur in the field of hybrid neurosymbolic approaches towards applications that are beyond the capabilities of any one approach on its own,


#selfdrivingcars_2022-06-22_05-29-21.xlsx

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The graph represents a network of 1,695 Twitter users whose tweets in the requested range contained "#selfdrivingcars", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 22 June 2022 at 12:38 UTC. The requested start date was Wednesday, 22 June 2022 at 00:01 UTC and the maximum number of tweets (going backward in time) was 7,500. The tweets in the network were tweeted over the 16-day, 17-hour, 23-minute period from Sunday, 05 June 2022 at 02:45 UTC to Tuesday, 21 June 2022 at 20:08 UTC. Additional tweets that were mentioned in this data set were also collected from prior time periods.


The Go-To-Market Strategy For Autonomous Vehicles: "Launch Somewhere"

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ENGLAND: Two autonomous, delivery robots pass on the pavement as they make home deliveries of ... [ ] groceries. Created by two of the co-founders of Skype in 2014, Starship has developed the self-driving pods for various, logistical tasks. Much more complicated than originally thought. Several manufacturers expected the first self-driving cars to hit the market 3-4 years ago. In fact, Johann Jungwirth of Volkswagen met with Focus Magazine in April of 2016 amongst beanbags, blue suede shoes and skateboards to report the first autonomous vehicles (AVs) will be on the market by 2019.


A Beginner's Guide to Basic Python

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Python programming language is a recommended language for beginners to learn. The reason is, this language has concise commands, so it is very easy to understand and write. You want to learn Python, but are confused about where to start? This time, we invite you to get to know what Python is, its functions and data types, to practice Python tutorials themselves. Python is one of the many examples of programming languages in the world.