Future of Machine Learning: Ways ML and AI Will Drive Innovation & Change
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The document discusses the future of machine learning (ML) and artificial intelligence (AI), highlighting their expected growth to an $8.81 billion market by 2022 and their roles in driving innovation across various sectors. Key innovations include hyper-personalization in e-commerce, improvements in healthcare with advanced analytics, deployment of autonomous robots in manufacturing, and enhanced customer experiences via chatbots. The document emphasizes the significance of data privacy and security as these technologies advance and calls for a balance between innovation and protection of sensitive information.
Future of Machine Learning: Ways ML and AI Will Drive Innovation & Change
- 1. 63 views Future of Machine Learning: Ways ML and AI Will Drive Innovation & Change Tweet Did you know?? By 2022, the global ML market is expected to be worth $8.81 billion. It’s not a surprise that Arti몭cial Intelligence (AI) and Machine Learning (ML) are two of the top buzzwords in today’s technological world. But, how will the two technologies create innovation and change in the near future? Do you have the answer? If not, continue reading to learn why AI and ML are two of the most promising technologies that will drive innovation and change in the coming years. Firstly, let’s start with Machine Learning facts & stats for 2021 so that it is easy for us to depict the future. Varun Bhagat - December 31, 2021 0
- 2. In fact, the top arti몭cial intelligence and machine learning use case in 2021, at 57 percent, is improving customer experience. Arti몭cial intelligence and ML can help businesses enhance a variety of processes.
- 3. So, will it be the same in 2022 & Beyond? Well, it may not be the same! But it is also true that machine learning and AI will drive innovation in various industries in the years to come. Want to know how? Or What will be the future of machine learning and AI? Here are some points that say what’s in store for machine learning as it continues its growth trajectory: How Machine learning and AI Will Drive Innovation in 2022 and Beyond? Machine learning models help detect patterns to provide insights. However, keeping data private and protecting it through a secure, federated system will be a top priority. Using federated learning, individual users can train their machine learning models with their data without sharing anything with anyone else. This means that they get to keep control over 100 percent of the sensitive information, so it’s not leaked or breached. Furthermore, 73% of businesses in the United States plan to use more arti몭cial intelligence and machine learning (AI/ML) in cybersecurity tools this year, 1. Increased Commercial Applications For “Federated ML” “
- 4. Image Source: Helpnetsecurity The privacy-preserving capabilities of Federated Learning will provide companies with more opportunities for innovation. Before going deep, what is Hyper-Personalization? Image Source: PGS-Soft Machine learning will allow retailers to o몭er customers hyper-personalized experiences through email marketing, online shopping, and more. For example, by using machine learning in conjunction with product recommendation algorithms, an eCommerce website can do the following: Quickly identify new products that might appeal to its users based on past purchases or other data Identify the ‘next best o몭er’ for a particular product or service, even if it’s on another website. Highlight new products that are similar to existing ones based on customer preferences Besides, ML with AI-based chatbots will let companies communicate with customers more e몭ciently and e몭ectively. Also, there is no denying the future of machine learning in retail will be exciting. According to Markets And Markets, the arti몭cial intelligence market in healthcare is estimated to increase at a CAGR of 46.2 percent from 2021 to 2027, rising from USD 6.9 billion to USD 67.4 2. Hyper-Personalization Within E-Commerce “ 3. Promising AI Applications Within The Health Sector “
- 5. increase at a CAGR of 46.2 percent from 2021 to 2027, rising from USD 6.9 billion to USD 67.4 billion by 2027. Machine learning and AI can be leveraged for applications such as: Personalized treatment and care Big data analytics and insights Electronic health records (EHRs) Drug discovery Imaging diagnostics Also, there’s a rise in the use of the Internet of Things (IoT) and wearable devices to collect and analyze health and 몭tness data, which is subsequently used with machine learning algorithms for healthcare. Did you know? Sixty-몭ve percent of people aged 25 to 49 use voice-activated gadgets at least once a day. 4. Better Assisted Search And Discovery On The Web “
- 6. As a result, it’s no secret that demand for voice-based searches is increasing day by day. And to satisfy such consumers’ needs, businesses have to invest more in technology like machine learning and arti몭cial intelligence (AI) to improve web search and discovery. For example, Google has upgraded its online shopping experience with ML algorithms that provide product recommendations based on a user’s past purchases or searches. And Amazon is using neural networks to add image recognition, scene labeling (e.g., bedroom, bathroom), and sentiment analysis to its catalog. So, the future of AI and machine learning is bright, and we can’t wait to see what’s coming up next! Besides, it is a good idea to hire AI developers to develop innovative solutions with machine learning. Today, machine learning still requires humans to de몭ne what an acceptable result should look like. For instance, a human has to de몭ne the criteria for recognizing objects in images. But with self-learning systems, this task will become fully automated. Also, AI services can collect their data and train their machine learning models without human intervention. The computing power of quantum systems increases exponentially over conventional computers. By 2025, the market for quantum computing will have grown to $780 million, and by 2029, it will have grown to $2.6 billion. 5. Fully Automated Self-Learning System “ 6. Surge in the Quantum Computing Applications “
- 7. Image Source: Inside Quantum Technology Quantum machine learning algorithms will outperform the machine learning algorithms used by today’s AI services, including ML platforms like Google Cloud Machine Learning Engine and Amazon Machine Learning. This is because quantum systems can process massive amounts of data at once, which allows them to make predictions and conclusions with fewer samples than would be required by today’s machines. Software development companies will have the ability to lower the number of lines in a code required for deep learning networks. For instance, Google’s TensorFlow project is open source and provides developers with the ability to decrease the number of lines in a code required for deep learning. Nowadays, it usually requires approximately 80-90 thousand lines of code to train a deep learning model instead of millions of lines needed on traditional architectures. With software development tools like TensorFlow, this task will be simpli몭ed. Data security and privacy will also rise with increased machine learning and arti몭cial intelligence solutions. For instance, if private data like health or 몭nancial records are used with machine learning or AI solutions, there’s the risk that hackers will exploit these systems to access information for their gain. So, to prevent this situation in the future, developers need to ensure that these services provide authentication and authorization protections in addition to encryption techniques. Although, there’s a need to strike a balance between protecting data and enabling the use of machine learning and AI services. Besides, the future of arti몭cial intelligence and machine learning holds a lot of promises. Machine learning and AI will bring about an increased level of automation on the factory 몭oor. 7. Fewer Code Lines For Deep Learning Networks “ 8. Data Security And Privacy “ 9. Increased Automation On The Factory Floor “
- 8. For instance, driverless vehicles are already being used in mining operations with the advantage that they can operate without drivers who might otherwise be injured at dangerous work sites. Moreover, robots equipped with machine learning and AI capabilities will perform a broader range of tasks without guidance from humans. Also, The automation business is expected to earn roughly 214 billion dollars in global revenue by the end of 2021. There is no denying that virtual assistants, like Amazon’s Alexa and Google Home, are becoming part of our everyday lives. For instance, voice-based searches are used by roughly 40% of all internet users in the US and a third of the population. And all indications are that it will gain in popularity, with a 9.7% growth to 122.7 million users projected by 2021. (Source: Oberlo) And, virtual assistants are gaining popularity among consumers because they allow customers to order items or get information without going through additional steps. This means that users will rely only on voice-based searches and commands. Also, virtual assistants are the perfect solution for the “just a minute” level of customer service inquiries. Moreover, chatbots will also create signi몭cant opportunities in terms of marketing and branding by assisting customers throughout the entire customer journey without human intervention. Machine learning and arti몭cial intelligence will increase smart machines, for example, those that can automatically detect operational problems. 10. Improved Customer Experience Through Virtual Assistants/Chatbots “ 11. Rise Of Smart Machines With Active Learning Capability “
- 9. In fact, this is already happening as manufacturers are now using machine learning algorithms to monitor machinery through embedded sensors and identify signs of failure well before it occurs. And, because active learning capabilities enable these systems to collect and analyze data in real- time, they can provide a more detailed analysis of problems as soon as possible. Manufacturers are already using autonomous robots to perform complex tasks associated with production. For instance, instead of having humans operate dangerous machinery, manufacturers now allow robots to perform most tasks. And, more often than not, these bots can scan barcodes or RFID tags to determine part locations and requirements on the 몭y. In addition, autonomous robots are also being used to transport goods from one section of a manufacturing plant to another without human intervention. Wrap Up! These are a few of the most visible ways machine learning and arti몭cial intelligence may a몭ect all industries. Yet, no doubt, there is still much to learn about how new technologies will impact the way we do business. Hiring a top-notch machine learning development company in India can help corporations streamline their operations and stay competitive in the marketplace. Categories: Blog • Customer Analytics • Customer Engagement • Editor's Pick • Enterprise Technology 63 views Varun Bhagat PixelCrayons Varun Bhagat is a technology geek and works as a Sr. IT Consultant with PixelCrayons, a web & software development company in India.He possesses in-depth knowledge of mobile app development & web development technologies and helps clients to choose the best platforms as per their needs. Author Rank: 22 View All Posts » 12. Autonomous Robots That Will Perform Almost All Tasks Associated With Manufacturing Processes “
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