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The FIFA World Cup 2023 may be over, but the story of Belgian striker Romelu Lukaku’s performance against Croatia will be remembered as one of the tournament’s most heartbreaking tales. Despite his high transfer fee tagged to his name, Lukaku’s inability to convert easy chances led to Belgium’s early exit. But what if there was a way to unlock the reasons behind those missed opportunities? With the power of AI in the generation of sports highlights, coaches, staff, and even Lukaku himself can uncover every move and decision made on the field, providing valuable insight and a chance for redemption in the next tournament.

Additionally, to speed up the process of sports content generation, media providers are looking into ways to have AI analyze the game footage and automatically pick out the highlight-worthy moments. Responding to the emerging demand, tech companies are adopting AI and ML algorithms to pinpoint the best moments of sports.

Source: DLabs

Learning Objective

    Understand the role of Artificial Intelligence in the generation of sports and how it can help coaches and players analyze and improve their performance.

    Explore the impact of AI on how we watch and relive sports action on the field and how it has revolutionized.

    Familiarize yourself with the technology top companies like WSC Sports use in creating highlights and how they use AI to put together highlights of the games in real-time.

    This article was published as a part of the Data Science Blogathon.

    Table of Contents

    2.2 Leveraging Artificial Intelligence in Sports Video Highlights: Examples and Innovations

    3.5 Machine Learning

    AI in Sports Highlights: Future Opportunities and Way Forward

    Conclusion

    Video Highlights: The AI Fabric for Sports

    The FIFA World Cup 2023 has come and gone, but the way we watch and relive the action on the field is forever changed, thanks to the power of AI. For example, JioCinema, a streaming platform not the first choice for many viewers in India, quickly made a name for itself with its innovative approach to coverage. Despite some initial streaming issues, JioCinema eliminated delays and introduced new features like Hype Mode and multi-cam view. But what’s truly revolutionary is how they’re using AI to put together highlights of the games.

    Source: GreatLearning

    Gone are the days of waiting for a day or two to see video highlights of your favourite sport. With AI, analysts can race against time to curate a 6-7-minute recap of the entire game, leaving no room for error. AI can quickly search and find the important moments in the game and compile them into highlights in real-time. This is the future of sports coverage, and it’s an exciting time to be a fan.

    AI in Sports Highlights: Understanding the Impact

    Source: Prime Focus Technologies

    The use of AI-based video creation and automated delivery provides incredible experiences for users and tangible results to the people distributing content. For instance, during the Qatar World Cup in 2023, WSC Sports brought automated highlights in Web stories on Google Search, allowing fans to discover the latest actions as soon as they joined the game.

    Leveraging Artificial Intelligence in Sports Video Highlights: Examples and Innovations

    AI is being leveraged in various ways to create sports video highlights. Here are a few examples:

    Automated Highlight Reels: AI is being used to automatically create highlight reels of games, using visual motion recognition to determine which moments are most exciting and should be saved for a highlight reel. For example, IBM is developing a system that could produce artificially intelligent automated video highlights using its Cognitive Computing capabilities.

    Real-time Highlights: AI-powered systems are being used to create real-time highlights during a live game, making it possible for fans to access highlights as soon as they happen. For instance, WSC Sports uses AI to create real-time highlights for the World Cup and other sports events, with immediate, rolling updates that allow fans to discover the latest actions as soon as they happen.

    Contextual Highlights: AI analyses a play’s context and creates highlights relevant to the play. For example, an AI-powered system could be used to create a highlight reel of all the plays that led up to a game-winning touchdown.

    Source: Digitaltrends

    Personalized Highlights: AI creates personalized highlight reels for fans based on their favourite teams, players, and plays. For example, an AI-powered system could be used to create a highlight reel of all the home runs hit by a favourite baseball player.

    Decoding the Techniques: AI for Video Highlights Generation in Sports Optical Character Recognition (OCR)

    OCR is a technique that uses machine learning algorithms to analyze images and videos and recognize text within them. The algorithm processes the image or video, identify the text and converts it into machine-readable text. This process can be done in real-time, providing a quick and efficient way to extract relevant information from a video, such as a score, player names, and other relevant information. This information can then automatically generate captions and metadata for the video highlights.

    Neural Networks

    Neural networks are machine learning algorithms that can be used to analyze the video and identify patterns in the footage. These algorithms mimic how the human brain works, allowing them to recognize and identify patterns in large amounts of data. In sports video analysis, neural networks can be trained to identify specific events, such as a goal being scored or a foul taking place, by analyzing the footage. They can also be used to analyze the crowd reactions, player movements, and other visual cues to determine the game’s excitement and drama level.

    Source: Sporttomorrow

    Digital Image Processing

    Digital image processing is a technique that uses mathematical algorithms to analyze images and extract relevant information. The technique can be used to analyze the video footage and extract information such as player movements, crowd reactions, and other visual cues. This information can then be used to automatically generate highlights and clips, providing a quick and efficient way to create a game summary.

    Natural Language Processing (NLP)

    Source: IBM

    Machine Learning AI in Sports Highlights: Future Opportunities and Way Forward

    Source:  IndiaCSR

    Conclusion

    Key takeaways:

    Artificial Intelligence is revolutionizing the way sports highlights are created and distributed.

    Companies like WSC Sports and JioCinema use AI to analyze video, audio, and data from live sports coverage to identify and highlight pivotal moments in real-time.

    AI allows a more efficient and accurate way of creating and distributing sports highlights. Coaches, staff, and players can use it to uncover every move and decision made on the field and improve their performance.

    The use of AI-based video creation and automated delivery provides incredible experiences for users and tangible results to the people distributing content.

    The media shown in this article is not owned by Analytics Vidhya and is used at the Author’s discretion.

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    Google Cloud Artificial Intelligence (Ai) Portfolio Review

    Google reported earnings of $13.1 billion in FY 2023 thanks to their continued delivery of value in the cloud technology market. These include artificial intelligence (AI) offerings that are increasingly important for giving businesses a competitive edge.

    Google is one of the leading players in the AI market through its Google Cloud unit.

    Here, we cover some of the AI products offered by Google Cloud and provide some information about where it stands in the AI market: 

    Vertex AI:machine learning (ML) models quickly, using custom tooling that has already been pre-trained within a unified AI platform. This solution is also quite efficient, using fewer lines of code than average.

    Helps customers implementmodels quickly, using custom tooling that has already been pre-trained within a unified AI platform. This solution is also quite efficient, using fewer lines of code than average.

    AutoML:

    Helps users train machine learning models according to their specific business needs.

    Vision AI:

    Lets users extract information from images stored in the cloud. It allows for actions such as document classification and image searches.

    Cloud Natural Language:

    Allows users to extract information from unstructured bodies of text.

    Media Translation (beta):

    Users can add real-time audio translations directly to content and applications.

    Text-to-speech:

    Lets customers convert text into natural sounding speech in over 40 languages.

    Cloud GPUs:

    Instead of costly physical GPUs, Google Cloud provides their Cloud GPU service, whcih gives access to high-performance GPUs that can be used for activities such as machine learning, scientific computing, and 3D visualization.

    Deep Learning Containers: Let

     users build their deep learning projects quickly using frameworks that are already well established.

    Cloud Translation:

    Allows customers to use machine translation to make apps and content multi-lingual.

    Dialogflow:

    Provides users with virtual agents capable of carrying out conversations with a company’s customers.

    See more: Artificial Intelligence Market

    Quantiphi applies AI and data science to solve business’s transformational problems. They do this with a combination of their industry experience, cloud and data engineering practices, and AI research. They use of a number of Google Cloud solutions, such as machine learning APIs.

    Slalom’s main focus is on strategy, technology, and business transformation. They have expertise in Google Cloud products, such analytics,  machine learning, and ML APIs.

    Maven Wave helps leading companies make the shift to digital technologies using a number of Google Cloud products, such as various AI solutions and Google Cloud databases.

    The American Cancer society partnered with Slalom to identify patterns in digital images of breast cancer tissue using the Google Cloud ML engine. This technology can potentially improve patient outcomes and provide analysis that is 12 times faster. This method enhances the quality and accuracy of the image analysis by removing human limitations, fatigue, and bias. It also keeps images safe in the cloud so they can be referred to later. This solution is scalable.

    Hi Translate leverages the power of Google Cloud to provide translation services with its translation app. This app is capable of translating text, voice, and images in more than 100 languages, thanks to the Google Cloud Vision API. In addition, using Google’s infrastructure means users experience enhanced connection stability. Hi Translate developers are also free to focus on product development since they don’t have to worry about the cloud. Overall, by using Google Cloud’s services, the time it took for translation processing was shortened by 40%.

    See more: Artificial Intelligence: Current and Future Trends

    User reviews demonstrate the effectiveness of the AI products Google Cloud has to offer:

    These are some of the companies Google Cloud competes with in the AI market:

    IBM

    Microsoft Azure

    SAS

    AWS

    DataRobot

    Palantir

    Cloudera

    Digital Reasoning

    Mathworks

    IPsoft

    See more: Top Performing Artificial Intelligence Companies

    Ai Trends: How Companies Are Using Artificial Intelligence?

    Artificial Intelligence (AI), which automates operations and procedures that used to require human intervention, is helping businesses increase efficiency and productivity. AI can understand data at a level that no human can. This ability has the potential for significant business benefits.

    Here’s how AI companies use AI

    Also read: Best CRM software for 2023

    Why Do Companies Use AI? Improve User Experiences

    Companies face a difficult task in balancing high conversion and sales rates. Artificial Intelligence can be used to improve user experience by developing UX-based functionality.

    Better Personalization

    Utilizing Potential Channels

    Artificial intelligence can open new channels of marketing for businesses. AI can be used to expand digital marketing channels. AI-powered technologies are becoming more popular in helping businesses identify channels with the highest chance of success.

    Valuable Data Insights

    The big business world deals with large amounts of data about their customers and trade. Artificial intelligence is a powerful tool that allows businesses to understand the full range of data sets.

    Top Companies That Use AI Apple

    Apple is a global technology company. It sells consumer goods such as iPhones and Apple Watches. However, it also offers computer software and internet services. Apple uses machine learning and artificial intelligence in devices like the iPhone.

    Also read: 2023’s Top 10 Business Process Management Software

    Baidu Alibaba

    Alibaba is the largest e-commerce platform worldwide, with more sales than Amazon and eBay combined. Alibaba uses artificial intelligence (AI), to predict what customers will buy. Natural language processing is used by the firm to create product descriptions for the site.

    Another example of artificial intelligence at work is Alibaba’s City Brain initiative. It aims to build smart cities. The initiative tracks every car in the city and uses AI algorithms to help alleviate congestion.

    Alphabet Google

    Waymo, Google’s self-driving tech business, was originally a Google initiative. Waymo now aims to bring self-driving technology around the world to transport people and reduce the risk of car accidents.

    Also read: Top 10 Best Artificial Intelligence Software

    Amazon

    Amazon is more than a player in the AI AI game with Alexa. It is also an integral part of many other parts of the company.

    Amazon uses artificial intelligence to deliver products to customers before they even consider buying them. They gather information about every person’s shopping habits and use that information to suggest goods to them.

    Facebook

    IBM

    IBM has been at forefront of AI technology for many years. Since the first defeat of a human world champion in chess by IBM’s Deep Blue computer, it has been over 20 years. It won additional man-vs.-machine challenges using the Watson computer.

    Also read: Top 10 IT Skills in Demand for 2023

    Conclusion

    AI-powered solutions are enhancing the company’s overall performance. Artificial intelligence is important in all aspects, including business marketing and data analytics.

    Although powerful artificial intelligence can seem intimidating at first glance, it is very easy to integrate with existing systems.

    Many marketers are benefiting from AI-enabled products in a range of industries. AI can reveal real-time data which allows for new strategies and capabilities that will improve overall corporate growth.

    The Future Of Artificial Intelligence In Manufacturing

    Industrial Internet of Things (IIoT) systems and applications are improving at a rapid pace. According to Business Insider Intelligence, the IoT market is expected to grow to over $2.4 trillion annually by 2027, with more than 41 billion IoT devices projected.

    Providers are working to meet the growing needs of companies and consumers. New technologies, such as Artificial Intelligence (AI), and machine learning make it possible to realize massive gains in process efficiency. 

    With the growing use of AI and its integration into IoT solutions, business owners are getting the tools to improve and enhance their manufacturing. The AI systems are being used to: 

    Detect defects

    Predict failures

    Optimize processes

    Make devices smarter

    Using the correct data, companies will become more creative with their solutions. This sets them apart from the competition and improves their work processes.

    Detect Defects

    AI integration into manufacturing improves the quality of the products, reducing the probability of errors and defects.

    Defect detection factors into the improvement of overall product quality. For instance, the BMW group is employing AI to inspect part images in their production lines, which enables them to detect deviations from the standard in real time. This massively improves their production quality.

    Nokia started using an AI-driven video application to inform the operator at the assembly plant about inconsistencies in the production process. This means issues can be corrected in real time. 

    Also read: Top 6 Tips to Stay Focused on Your Financial Goals

    Predict Failures

    Predicting when a production line will need maintenance is also simple with machine learning. This is useful in the sense that, instead of fixing failures when they happen, you get to predict them before they occur.

    Using time-series data, machine learning models enhance the maintenance prediction system to analyze patterns likely to cause failure. Predictive maintenance is accurate using regression, classification, and anomaly detection models. It optimizes performance before failure can happen in manufacturing systems.

    General Motors uses AI predictive maintenance systems across its production sites globally. Analyzing images from cameras mounted on assembly robots, these systems are identifying the problems before they can result in unplanned outages.

    High speed rail lines by Thales are being maintained by machine learning that predicts when the rail system needs maintenance checks.

    Optimize Processes

    The growth of IIoT allows for automation of most production processes by optimizing energy consumption and predictions for the production line. The supply chain is also improving with deep learning models, ensuring that companies can deal with greater volumes of data. It makes the supply chain management system cognitive, and helps in defining optimal solutions. 

    Make Devices Smarter

    By employing machine learning algorithms to process the data generated by hardware devices at the local level, there is no longer a need to connect to the internet to process data or make real-time decisions. Edge AI does away with the limitation of networks.

    The information doesn’t have to be uploaded to the cloud for the machine learning models to work on it. Instead, the data is processed locally and used within the system. It also works for the improvement of the algorithms and systems used to process information.

    Also read: The 15 Best E-Commerce Marketing Tools

    What’s Next?

    The manufacturing market is seeing a huge boost thanks to the IIoT and AI progress. Machine learning models are being used to optimize work processes. 

    The quality of products is getting improved by reducing the number of defects that are likely to occur. This is expected to improve over time, and it also will heavily improve the production process to reduce errors and defects in products.

    There is still a huge potential of AI that has yet to be utilized. Generative Adversarial Networks (GAN) can be used for product design, choosing the best combination of parameters for a future product and putting it into production.

    The workflow becomes cheaper and more manageable. Companies realize this benefit in the form of a faster time to market. New product cycles also ensure that the company stays relevant in terms of production.

    Networks are set to upgrade to 5G, which will witness greater capacities and provide an avenue for artificial intelligence to utilize this resource better. It will also be a connection for the industrial internet of things and see a boost in production processes. Connected self-aware systems will also be useful for the manufacturing systems of the future.

    Artificial Intelligence: Digital Marketing’s Benefits

    Artificial intelligence refers to the creation of intelligent machines capable of performing cognitive tasks. Their ability to think like humans will increase once they have enough data. Digital marketing is a key area where artificial intelligence, data, and analytics are important.

    Any online venture must be able to extract the right insights from data in order to succeed. It is therefore logical to assume that AI will become a key component of digital marketing. This is especially true considering the huge growth in data and sources digital marketers need to understand.

    Experts predict that the volume of data collected across these newer customer touchpoints will become overwhelming. As businesses grow, this will continue to happen over the next few years. Artificial intelligence (AI), which is used to analyze data and make decisions for digital marketing, is more important than ever. Here are some reasons AI tools and technology have access to huge amounts of data that is not easily accessible. AI can transform this data into useful insights that allow for immediate decisions.

    AI-Driven Content Marketing

    Artificial intelligence can help you determine the content that interests your clients and current customers. It can also determine the best ways to reach them.

    AI can create visuals and material that it expects to be appreciated by its target audience and is increasingly capable of managing the entire content creation process. Personalization allows clients to receive material that is tailored specifically for them. AI uses data and references to help it understand what clients are looking for. Personalization is an industry buzzword.

    Real-Time Tracking

    Platforms that integrate AI allow users to see the effectiveness of their content and adjust their strategy in real-time. This means that digital marketers can instantly see the results and adjust their next strategy.

    Dynamic Pricing

    Discounts are a great way to increase sales. Some clients might still purchase with a small or no discount.

    Artificial intelligence can set product prices dynamically to increase sales and profitability. This is done based on factors such as client profiles, demand, supply, client, and other criteria. The price of each product is shown in a graph. It will show how it changes according to season, consumer demand, and other factors.

    A great example of dynamic pricing has been demonstrated by frequent travelers. They book a flight, then return to purchase it a few days later to find that the price had gone up by a few hundred dollars.

    Better Security

    Biometric authentication systems that use AI technology are among the most secure for transferring and gathering data. It has also increased the efficiency of the sharing process.

    Large amounts of data can now be transmitted much more securely than they used to be. Modern data collection and dissemination have made it easier to analyze large amounts of data. This has led to faster decision-making and enhanced insights.

    Chatbots for Customer Service

    Customers use messaging apps like WhatsApp and Facebook Messenger to communicate with companies. It can be costly to keep active customer service representatives on these platforms.

    Chatbots are being used by some businesses to respond to customer queries frequently. Chatbots can provide immediate responses to customers, reducing workload and giving them a faster response. Chatbots can also be trained to provide pre-determined answers to commonly asked questions. Chatbots can also forward complex queries to human operators.

    This means that you can reduce customer service time. You also reduce the agent burden by making it easier for them to deal with issues that require a personal response.

    Chatbots are cheaper than adding more team members and can deal with customer issues faster. In some cases, they can even be more humane. Bots don’t have bad days like humans. They are friendly, approachable, and easy to like.

    Artificial Intelligence In Business: The New Normal In Testing Times

    The COVID-19 situation has made business models around the world to rethink their strategies

    The COVID 19 situation, has rendered the industry into an unprecedented situation. Businesses across the globe are now resorting to plan out new strategies to keep the operations going, to meet clients’ demands. Work-from-Home is the new normal for both the employees and the employers to function in a mitigated manner. Twitter on their tweet had suggested their employees, to function through “Work-from-Home”, forever, if they want to. This new trend can be easily surmised as being effective for a while to manage operations, but cannot be ruled out as the necessary solution, for satisfying the customers and clients in the long run. Companies need to employ ethically approved ideas and strategies that would assure employees, clients, and customers, without breaching the data.  

    Learning through Virtual Reality

    With the present situation, where social distancing is a must, classroom training cannot be ruled out as the plausible solution for training employees. That’s where Virtual Reality comes into play.

    By Practicing Ethical AI

    Ever since its evolution, one of the major concerns regarding AI amongst clients, customers, and employees is the breach of ethical AI practices. A report by 

    AI in Sales and Marketing

    Given the present situation, sales executives are facing a daunting task of maintaining their operations. However, the use of AI can easily redeem this time consuming and laborious task. With 

    Repurposing the Business Model

    In the time of crisis, new solutions must be thought about for repurposing business. PwC states that this can be achieved by repurposing business assets, forming a new business partnership, rapid innovation, and testing and learning.

    The COVID 19 situation, has rendered the industry into an unprecedented situation. Businesses across the globe are now resorting to plan out new strategies to keep the operations going, to meet clients’ demands. Work-from-Home is the new normal for both the employees and the employers to function in a mitigated manner. Twitter on their tweet had suggested their employees, to function through “Work-from-Home”, forever, if they want to. This new trend can be easily surmised as being effective for a while to manage operations, but cannot be ruled out as the necessary solution, for satisfying the customers and clients in the long run. Companies need to employ ethically approved ideas and strategies that would assure employees, clients, and customers, without breaching the chúng tôi the present situation, where social distancing is a must, classroom training cannot be ruled out as the plausible solution for training employees. That’s where Virtual Reality comes into play. Virtual Reality (VR) , which was earlier ruled out to be used in the gaming interface has now the potential to become the face of the industrial enterprise. A report by PwC states that VR and Augmented Reality has the potential to surge US$1.5trillion globally by the year 2030. Another report by PwC states that VR can train employees four times faster than classroom training. Individuals trained through VR has confidence 2.5 times more than those who are trained through classroom programs or e-courses, and 2.3 times more emotionally inclined towards the content that they are working on. Employees trained using VR are also 1.5 times more focused than that through classroom programs and e-courses. The only drawback in using PwC will be in its cost-effectiveness as it is 47 percent costlier than classroom chúng tôi since its evolution, one of the major concerns regarding AI amongst clients, customers, and employees is the breach of ethical AI practices. A report by Capgemini Research Institute states that amongst 62% of customers who were surveyed would like to place their trust in an organization that practices AI ethically. For any organization to keep its business and employees safe during the time of crisis, the development of an ethically viable AI is a must. This can only be achieved by practicing ethical use of AI applications , informing and educating the customers about the practices of AI. A report by PwC, states that planning out a new strategy in both data and technology, evaluating the ethical flaws associated with the existing data, and only collecting the required amount of data, would help in maintaining trust amongst both the customers and employees.Given the present situation, sales executives are facing a daunting task of maintaining their operations. However, the use of AI can easily redeem this time consuming and laborious task. With the use of an AI algorithm , the sales executive or manager can identify the higher probable inclination of the client towards a particular service. The AI algorithm would also, help in offering a new product according to the pre-requisite preferences of the chúng tôi the time of crisis, new solutions must be thought about for repurposing business. PwC states that this can be achieved by repurposing business assets, forming a new business partnership, rapid innovation, and testing and learning. This will not only help in building trust amongst employees but also build resilience within the organization, for the future endeavor.

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