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Also, the use of AR and VR in designing & assembling phase is benefitting automotive companies significantly. For example, designing and visualizing the vehicle in AR and VR technology assists designers in visualizing the body structure of a vehicle to improve efficiency, safety, and durability. Allied Market Research recently published a report, titled, "Automotive AR and VR Market by Type (Augmented Reality (AR) and Virtual Reality (VR)) and Application (Research & Development, Manufacturing & Supply, Marketing & sales, Aftersales, Support Functions, and Product): Global Opportunity Analysis and Industry Forecast, 2018 - 2025". According to the report, the global automotive AR and VR market was valued at $213.0 million in 2017 and is expected to reach $673.60 billion by 2025, growing at a CAGR of 175.7% during the forecast period.

Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! Gartner has released its latest Hype Cycle for emerging technologies, giving a glimpse at 25 embryonic and early-stage technological advances that can help enterprises differentiate and drive growth in the coming years. Modern organizations are racing to innovate to stay ahead of the competition and drive technology-enabled business transformation. They are watching market trends, but with hundreds of advances happening worldwide and the surrounding publicity, it becomes difficult to separate hype from reality.

I think your personal vision comes through. When I was a kid, I used to play video games that felt so real and watch movies that depicted machinery and technology coming to life as if they were living in the real world. I wondered if it would ever actually happen in reality or if it was simply the graphics I was seeing at the time, which he found to be incredible…But when that boy himself chose to be a part of this field, his questions were answered. Computer vision is a blend of magic and science to create illusions of reality. I believe that if a machine is capable of looking at the surroundings and understanding the situation, it can respond to it in the same way that a human can.

Recent years have seen a large interest in using the Simplified Molecular Input Line Entry System (SMILES) chemical language as input for deep learning architectures solving chemical tasks. Many successful applications have been demonstrated within de novo molecular design, quantitative structure-activity relationship modelling, forward reaction prediction and single-step retrosynthetic planning as examples. PySMILESUtils aims to enable these tasks by providing readyto- use and adaptable Python classes for tokenization, augmentation, dataset, and dataloader creation. Classes for handling datasets larger than memory and speeding up training by minimizing padding are also provided. The framework subclasses PyTorch dataset and dataloaders but should be adaptable for other deep learning frameworks.

Intended for researchers and practitioners alike, this book covers carefully selected yet broad topics in optimization, machine learning, and metaheuristics. Written by world-leading academic researchers who are extremely experienced in industrial applications, this self-contained book is the first of its kind that provides comprehensive background knowledge, particularly practical guidelines, and state-of-the-art techniques. New algorithms are carefully explained, further elaborated with pseudocode or flowcharts, and full working source code is made freely available.

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Hi everyone, and thanks for tuning in to our new post on exporting NIR regression models built in Python. One of the reader of this blog asked me this question: "How can we export a model that we just build, so that we can use it over and over again without having to fit the training data every time?" I must admit, I didn't have the answer straight away, it's a very good question. Once the training part is completed, it would be good to export the model to file, store it and retrieve it at a later time. If you'd like to get started with building your calibration models in Python, take a look at some of our previous posts.

Rammas, DEWA's virtual AI employee, is available on seven channels for customer service. These include DEWA's smart app (iOS and Android), DEWA's website and social media account on Facebook, Amazon's Alexa, and Google Assistant, robots, and WhatsApp Business. Rammas provides round-the-clock multiple services and answers enquiries in English and Arabic. DEWA employs AI to enhance customer and employee happiness as well as improve the performance of its systems through'Rammas for You' and'Rammas at Work' and'Powered by Rammas'. Rammas has answered more than 6.4 million enquiries since its inception in the first quarter of 2017 and until the end of June 2022.

Role requiring'No experience data provided' months of experience in Los Angeles Accentures SAP practice in the West, and we bring the New to life using design thinking, agile development methodologies, and the latest smart tech for SAP when it comes to automation and AI. We help out clients apply intelligence to set their business apart and make them more proactive, predictive and productive the power of the intelligent enterprise. We have also announced our partnership with SAP to develop SAPs new Responsible Production and Design solution, which will help companies consume fewer resources and build sustainability into their design processes. We believe sustainability is going to be the next digital, says Julie Sweet. Im hopeful that by 2025, well be able to say every business is a sustainable business.