bioAi is Biological Artificial intelligence. All kind of Artificial intelligence based on biology Found by Michael Weber
bioAi is a new science that combines Biology, Artificial intelligence, Computer science, Machine learning, Deep learning, Natural language processing, Robotics and Bioinformatics
Bioinformatics is an interdisciplinary field that develops methods and software tools for understanding biological data, in particular when the data sets are large and complex. Bioinformatics is a subdiscipline of biology and computer science concerned with the acquisition, storage, analysis, and dissemination of biological data. Next-generation sequencing data analysis, 3D genome, big data science including storage, analysis, modeling, visualization, and cloud are some of the applications of bioinformatics. Bioinformatics is also known as life science informatics and is a modern branch of biotechnology that gives biologists a vital tool for commercializing biotechnology. Bioinformatics is the application of computer technology to the understanding and effective use of biological and biomedical data. It is the discipline that focuses on the development of algorithms and software tools for the analysis of biological data. BMC Bioinformatics is an open access, peer-reviewed journal that considers articles describing novel computational algorithms and software, models, and tools for the understanding of biological systems.
Artificial intelligence (AI) is intelligence—perceiving, synthesizing, and inferring information—demonstrated by machines, as opposed to intelligence displayed by humans. At its simplest form, artificial intelligence is a field which combines computer science and robust datasets to enable problem-solving. It also encompasses sub-fields of machine learning and deep learning, which are frequently mentioned in conjunction with artificial intelligence. AI algorithms seek to create expert systems which make predictions or classifications based on input data. AI is used in a wide range of applications, such as natural language processing, robotics, and autonomous vehicles.
Computer Science is the study of computers and computational systems. Unlike electrical and computer engineers, computer scientists deal mostly with software and software systems; this includes their theory, design, development, application, algorithms, and performance of computer hardware and software. Principal areas of study within Computer Science include artificial intelligence, computer systems and networks, security, database systems, human computer interaction, vision and graphics, numerical analysis, programming languages, software engineering, bioinformatics and theory of computing.
Machine learning (ML) is a field of inquiry devoted to understanding and building methods that ‘learn’, that is, methods that leverage data to improve performance. It is a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn and make decisions. Google’s fast-paced, practical introduction to machine learning, featuring a series of lessons with video lectures, real-world case studies, and hands-on activities, is a great way to start learning about the topic. Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention. Machine learning is an application of AI that enables systems to learn and improve from experience without being explicitly programmed. Machine Learning is the field of study that gives computers the capability to learn without being explicitly programmed. ML is one of the core components of AI. In the first course of the Machine Learning Specialization, you will learn to build machine learning models in Python using popular machine learning libraries.
Deep learning is a machine learning technique that teaches computers to do what comes naturally to humans: learn by example. It is the key technology behind driverless cars, enabling them to recognize a stop sign, or to distinguish a pedestrian from a lamppost. It is also used in automated hearing and speech translation, and for automated detection of cancer cells. Deep learning algorithms attempt to draw similar representations from data that can be used in different tasks such as classification, recognition, prediction, and decision making. Deep learning models are trained by using a large set of labeled data and neural network architectures that contain many layers.
Natural language processing
Natural language processing (NLP) is an interdisciplinary subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language. It is used to develop computer systems that are able to understand, interpret and manipulate natural language. NLP enables computers to process and analyze large amounts of natural language data, such as text and speech. It also enables the development of applications such as chatbots, speech recognition and machine translation.
Robotics is an interdisciplinary branch of computer science and engineering. Robotics involves design, construction, operation, and use of robots. The objective of the robotics field is to create intelligent machines that can assist humans in a variety of ways. Robotics can take on a number of forms, including robotic process automation (RPA), which simulates how humans engage with software to perform repetitive, rules-based tasks. The International Federation of Robotics is a professional non-profit organization to promote, strengthen and protect the robotics industry worldwide. Robotics is also widely used in such industries as home electronics, computer science, artificial intelligence, data science, law enforcement and military, mechanical engineering, mechatronics, nanotechnology, bioengineering, healthcare, and aerospace. The latest developments in consumer robots, humanoids, drones, and automation are also rapidly advancing.
Michael Weber | bioAi