Artificial Intelligence.pptx
- 2. Artificial Intelligence • Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing, speech recognition and machine vision.
- 4. How does AI work • As the hype around AI has accelerated, vendors have been scrambling to promote how their products and services use AI. Often what they refer to as AI is simply one component of AI, such as machine learning. AI requires a foundation of specialized hardware and software for writing and training machine learning algorithms. No one programming language is synonymous with AI, but a few, including Python, R and Java, are popular. • In general, AI systems work by ingesting large amounts of labeled training data, analyzing the data for correlations and patterns, and using these patterns to make predictions about future states. In this way, a chatbot that is fed examples of text chats can learn to produce lifelike exchanges with people, or an image recognition tool can learn to identify and describe objects in images by reviewing millions of examples.
- 5. Types of Artificial Intelligence • In 2020, we can classify artificial intelligence into 4 distinct types. The types are loosely similar to Maslov’s hierarchy of needs, where the simplest level only requires basic functioning and the most advanced level is the Mohammad, Buddha, Christian Saint, all-knowing, all-seeing, self-aware consciousness. • The four A.I. types are 1.Reactive Machines 2.Limited Memory 3.Theory of Mind 4.Self Aware
- 7. Reactive Machines • Reactive Machines perform basic operations. This level of A.I. is the simplest. These types react to some input with some output. There is no learning that occurs. This is the first stage to any A.I. system. A machine learning that takes a human face as input and outputs a box around the face to identify it as a face is a simple, reactive machine. The model stores no inputs, it performs no learning. • Static machine learning models are reactive machines. Their architecture is the simplest and they can be found on GitHub repos across the web. These models can be downloaded, traded, passed around and loaded into a developer’s toolkit with ease.
- 9. Limited memory • Limited memory types refer to an A.I.’s ability to store previous data and/or predictions, using that data to make better predictions. With Limited Memory, machine learning architecture becomes a little more complex. Every machine learning model requires limited memory to be created, but the model can get deployed as a reactive machine type.
- 11. Theory of mind • We have yet to reach Theory of Mind artificial intelligence types. These are only in their beginning phases and can be seen in things like self-driving cars. In this type of A.I., A.I. begins to interact with the thoughts and emotions of humans. • Presently, machine learning models do a lot for a person directed at achieving a task. Current models have a one-way relationship with A.I. Alexa and Siri bow to every command. If you angrily yell at Google Maps to take you another direction, it does not offer emotional support and say, “This is the fastest direction. Who may I call and inform you will be late?” Google Maps, instead, continues to return the same traffic reports and ETAs that it had already shown and has no concern for your distress.
- 12. Self aware • Finally, in some distant future, perhaps A.I. achieves nirvana. It becomes self-aware. This kind of A.I. exists only in story, and, as stories often do, instills both immense amounts of hope and fear into audiences. A self-aware intelligence beyond the human has an independent intelligence, and likely, people will have to negotiate terms with the entity it created. What happens, good or bad, is anyone’s guess.
- 14. How artificial intelligence will change the world • ROBOTS • 2022 is the year robot delivery ultimately takes off. Drones will be applications in towns handing over samples and reagents from quicker than automobiles could drive throughout town. Detecting and working in environments wherein people can’t survive, producing repetitively. •
- 16. AI at healthcare • At the 2018 World Medical Innovation Forum (WMIF) on artificial intelligence presented by Partners Healthcare, main researchers and clinical faculty participants showcased the twelve technologies and areas of the healthcare enterprise which might be maximum in all likelihood to look a major effect from artificial intelligence. AI has made specific contributions in anticancer drug improvement and remedy. It can offer critical insights and data that can’t be discovered through human identity and customize remedies for each cancer patient. It is assumed that AI could be an effective riding force for human most cancer studies and remedy in the future. We trust that AI will carry profound modifications to scientific technology in the future. AI can control the usage of chemotherapy drugs and expect the tolerance of chemotherapy drugs so that it will optimize the chemotherapy regimen. AI can assist medical doctors to make accurate remedy choices, lessen needless surgeries, and assist oncologists to enhance sufferers’ cancer remedy plans.
- 18. AI as workforce • The consensus amongst many specialists is that some of the professions might be definitely computerized. A group of senior-level tech executives who contain the Forbes Technology Council named 13, which include insurance underwriting, warehouse, and production jobs, consumer service, studies and information entry, long haul trucking, and a fairly disconcertingly wide class titled “Any Tasks That Can Be Learned.” Accountants, manufacturing unit employees, truckers, paralegals, and radiologists — simply to name a few. • Ex: Chatbots, AI-writers (such as Ryte), AI-Translators, AI-coders, etc.…
- 20. AI in education • The future of classrooms is virtual. Already, there are lots of courses on platforms that can be distinctly informative and can be accessed from anywhere, anytime. AI can automate the excursion of administrative responsibilities for instructors and educational institutions. • Educators spend a lot of time grading exams, assessing homework, and imparting important responses to their students. AI is permitting the automation of categories and processing of paperwork. The idea of schooling may be redefined from the comfort of the homes, customized in line with each students’