Do you know machine learning? It has become an indispensable part of everyday life
According to the BBC, many people may not be sure exactly what machine learning is, and in fact it has become an indispensable part of our daily lives. As a form of artificial intelligence (AI), machine learning allows a computer to learn from an example without having to follow pre-defined instructions. The Royal Society believes that machine learning will have an ever-increasing impact on human life and calls for more research to ensure that people can make better use of it. Machine learning is changing our lives in eight seemingly ordinary ways: On the phone You can use verbal commands to ask your phone to perform tasks such as searching, calling, etc. These functions rely on machine learning technology support. Virtual personal assistants such as Siri, Alexa, Cortana, and Google Assistant are able to follow verbal instructions because they recognize speech. They can handle human natural language and match it to the desired instructions and responses in an increasingly natural way. These assistants can learn a lot of conversations in different ways. They can be asked for specific information, such as how to read your name, or to identify the owner of the sound in the room. The large number of conversations of the users used are their sample data, helping the assistant identify words with different pronunciations, or how to create natural discussions. 2. In the shopping basket Many of us are already familiar with shopping recommendations, such as supermarkets reminding you to add cheese to an online store, or Amazon recommending books you might like. Machine learning allows Amazon to offer referral services to individual shoppers, a technology that provides advice through a so-called recommendation system. By analyzing the user's previous shopping data and various preferences, the recommendation system can record the user purchasing history pattern. They use this model to predict what you might buy. 3. On TV A similar system is also used to recommend movies or TV shows to streaming services like Netflix. The recommendation system uses machine learning to analyze your viewing habits and build patterns from the movies or shows you watch. By knowing which users like which type of movie, such as the type of movie you most often watch, the recommendation system will determine your taste. They can also be used to recommend tracks for you on the streaming music service SpoTIfy, and to read articles for you on Facebook. 4. In the email Machine learning can also be used to distinguish between different categories of objects or items. Artificial intelligence is playing an important role in filtering spam. This technique is especially useful when you want to filter out messages you want to see from messages you don't want to see. The spam discovery system can use sample mail to filter spam and identify spam by finding specific words, specific sender names, or other characteristics. With this learning ability, these systems can directly link email to the correct folder. It can also tag emails like users or move between different folders. 5. On social media Everyone wants to know how Facebook knows who the people in the photo are and how to automatically tag your photos? The ability of image recognition systems used by Facebook and other social media to automatically tag photos is also derived from machine learning. When a user uploads a picture and tags family and friends, these image recognition systems can find duplicate pictures and classify them accordingly. 6. In the bank By analyzing a large number of data accounts, machine learning can help human analysts discover unusual patterns or activities that cannot be seen. The most common application of this ability is to crack down on credit card and debit card fraud. Machine learning systems can be trained to identify specific spending patterns and trading characteristics, such as location, quantity, and time, making fraud more difficult. When the transaction does not look normal, the system alerts and sends a message to the user. 7. In the hospital Doctors are just beginning to consider using machine learning to help make better diagnoses, such as diagnosing cancer and eye diseases. Patients in an eye hospital usually need to take a photo of the retina to find the problem, and by knowing the pictures marked by the doctor, the computer can analyze the patient's new retina picture, including skin spots or cell images under the microscope. They can find visual clues that show the patient's eye problems. Such image recognition systems are becoming more and more important in medical diagnosis. 8. In science Machine learning also provides scientists with new discoveries. In particle physics, it allows scientists to find specific patterns in the huge data generated by the Large Hadron Collider. This instrument helped to discover the Higgs Boson, which is now being used to help find "new physics" that no one can imagine. Similar ideas are being used to discover new drugs, such as finding new small molecules and antibodies against the disease. Future prospects The focus of the future will be on having the system perform special tasks on its own, so they can be considered the best “helpersâ€. At school, they track student performance and help develop individual study plans. By making better use of resources, they can help us reduce energy consumption; help improve older care by finding more meaningful time for human communication; in the transportation sector, machine learning is also supporting driverless car development. Many industries are using algorithms to increase productivity. Financial services may become more and more automated, and law firms may use machine learning for basic research, and daily tasks will be performed faster. In the next 10 years, machine learning technology will increasingly become an indispensable part of our lives and change our work and lifestyle. Semiconductor Moly Semiconductor Moly YANGZHOU POSITIONING TECH CO., LTD. , https://www.cnfudatech.com
