Brief Summary
Alright ji, here's the gist of the AI basics video, একদম short and sweet:
- AI Basics: AI is all about making machines think and act like humans, learning from experience to solve problems.
- AI Roadmap: To become an AI engineer, you need a strong math and programming foundation, a relevant degree, and hands-on project experience.
- Types of AI: AI can be narrow (weak), general (strong), or super, and can function as reactive machines, with limited memory, theory of mind, or self-awareness.
- AI Applications: AI is used in social media, automobiles, agriculture, gaming, healthcare, robotics, banking, and daily life.
- Machine Learning: Machine learning is a subset of AI that enables systems to learn and improve from experience without explicit programming.
Introduction to Basics Of Artificial Intelligence
Hello and welcome to the video on artificial intelligence basics. AI is a broad term for intelligent agents that can perform tasks that typically require human intelligence. These agents can learn from experience and improve over time. AI has the capability to greatly enhance our daily lives. It is becoming increasingly important to have a deep understanding of AI and its application. Learning AI is an investment in your own future as well as in your future of your society as a whole. Simplilearn presents an AI boot camp that is designed to equip you with the knowledge and skills you need to thrive in this fast-paced and ever evolving field.
What is Artificial Intelligence?
John wondered how technology has made his life easy. He found out that Netflix, Siri, and Tesla are all using AI. AI or artificial intelligence is nothing but making computers based machines think and act like humans. John McCarthy coined the term artificial intelligence back in 1956. There are three types of AI: Artificial narrow intelligence, artificial general intelligence, and artificial super intelligence. Machine learning, deep learning, and natural language processing are all connected with artificial intelligence. AI is advancing in every crucial field like healthcare, education, robotics, banking, e-commerce, and the list goes on. The future of AI looks promising with the AI market expected to reach $190 billion by 2025.
AI Roadmap for 2023
This AI road map guides you in navigating the path towards building a successful career in artificial intelligence. The ultimate goal of artificial intelligence is to create intelligent missions that can perform complex task, exhibit humanlike intelligence and contribute positivity to society. AI presents exciting career opportunity in various industries and sectors. Roles like AI engineer, data scientist, NLP engineers, computer vision engineers, AI research scientist, robotic engineers and many more offer exciting prospects for working with cuttingedge technologies and making an impact through artificial intelligence innovation. The average reported salary of an AI engineer in the United States is around $15,000 per year. However, in India, it is 10 lakh peranom. Leading companies worldwide are fully aware of the immense value of AI and are actively pursuing skilled AI engineers to contribute to their research development and implementations of AI technology.
Types Of Artificial Intelligence
AI can be classified based on capabilities and functionalities. Under capabilities, there are three types of artificial intelligence: narrow AI, general AI, and super AI. Under functionalities, we have four types of artificial intelligence: reactive machine, limited memory, theory of mind, and self-awareness. Narrow AI, also known as weak AI, focuses on one narrow task and cannot perform beyond its limitations. General AI, also known as strong AI, has the ability to understand and learn any intellectual task that a human can. Super AI exceeds human intelligence and can perform any task better than a human. A reactive machine is the basic form of AI that does not store memories or use past experiences to determine future actions. Limited memory AI learns from past data to make decisions. Theory of mind represents a very advanced class of technology and exists as a concept. Self-awareness AI only exists hypothetically.
Top 10 AI Applications
AI can create social media post for you. It can draft and target social ads. It can also automate monitoring and it has powers that most of what you see in any given social network. The automotive value chain which includes manufacturing, design, supply, production, post-p production, driving assistance and driver risk assessment systems is successfully implementing artificial intelligence. Global spending on smart agriculture, including artificial intelligence and machine learning, is projected to triple to $15.3 million by 2025. The gaming industry is one another area where artificial intelligence technologies have gained popularity. Artificial intelligence in healthcare has the potential to help providers in many areas of patient care and operational procedures enabling them to build on current solutions and solve problems quickly. Another area where artificial intelligence is frequently applied is robotic. The use of advanced data analytics by artificial intelligence will transform banking in the future by reducing fraud enhancing compilence. Artificial intelligence is used in autonomous vehicle to teach computers to think and evolve like humans. The email that we regularly use features artificial intelligence that separates out junk emails and sends it to spam or trash folders, allowing us to see only the filtered material. Facial recognition algorithms are used by our favorite devices including phones, laptops, and personal computers to detect and identify users in order to grant safe access. Artificial intelligence can assist educators with non-educational task such as facilitating and automating personalized messages to students, back office duties such as grading paperwork, organizing and facilitating routine feedback, managing enrollment courses, etc. Artificial intelligence is most commonly used in the field of e-commerce.
What is Machine Learning?
Machine learning is the science of programming machines to think and act like humans without being specifically programmed to. Machine learning uses algorithms to learn tasks. These algorithms are fed with data from which they learn to perform these tasks. Machine learning is a subset of artificial intelligence which is a science concerned with imparting human-like intelligence onto machines and creating machines which can sense, reason, act and adapt. Deep learning is a subbranch of machine learning which is inspired by the working of the human brain. Machine learning is leading us to a future where machines can learn and think and has opened us a whole new plethora of job opportunities.
Types Of Machine Learning
Machine learning is primarily of three types: supervised machine learning, unsupervised learning, and reinforcement learning. In supervised learning, you have to supervise your machine learning while you train it to work on its own. It requires labeled training data. In unsupervised learning, there will be training data but it won't be labeled. In reinforcement learning, the system learns on its own. In supervised learning, you are training the model to do a certain kind of an operation on its own. This kind of a model is generally used into filtering spam mails from your email accounts as well. In unsupervised learning, you provide the data to the system and let the system do the rest of the work. This kind of a model is used by Flipkart to figure out the products that are well suited for you. In reinforcement learning, it learns from his mistakes and experiences. This model is used in games like Prince of Persia or Assassin's Creed or FIFA wherein the level of difficulty increases as you get better with the games.
Linear Regression Analysis
Linear regression is the statistical model used to predict the relationship between independent and dependent variables by examining two factors. The first important one is which variables in particular are significant predictors of the outcome variable. And the second one that we need to look at closely is how significant is the regression line to make predictions with the highest possible accuracy. The simplest form of a simple linear regression equation with one dependent and one independent variable is represented by y = m * x + c. M in this case is the slope of the line where M equals the difference in the Y2 - Y1 and X2 - X1. And finally, we have C, which is the coefficient of the line or where it happens to cross the zero axis. In multiple linear regression we have multiple variables coming in. So instead of having just x we have x1 x2 x3 and instead of having just one slope each variable has its own slope attached to it.
Classification In Machine Learning
Classification is used when the output you are looking for is a yes or a no or in the form A or B or true or false. The algorithms that fall under classification are decision tree, knife base, random forest, logistic regression and KNN. Regression is used when the predicted data is numerical in nature. Clustering is a kind of unsupervised learning. Again, it is used when the data needs to be organized. Most of the recommendation system used by Flipkart, Amazon, etc. make use of clustering. The four algorithms that we will try to understand are K nearest neighbor, linear regression, decision tree and KN base. K nearest neighbor is again a kind of a classification algorithm. Linear regression is again a type of supervised learning algorithm. This algorithm is used to establish linear relationship between variables, one of which would be dependent and the other one would be independent. This algorithm that is decision tree is a kind of an algorithm you can very strongly relate to. It uses a kind of a branching method to realize the problem and make decisions based on the conditions. Nightb algorithm is mostly used in cases where a prediction needs to be done on a very large data set. It makes use of conditional probability.
Top 10 AI Tools For 2023
Magic Eraser by Magic Studio removes unwanted images from your pictures. The Thing Translator allows users to point their camera at an object and hear the translation in a different language. Tab 9 analyzes and recommends your next blocks of code based on the context and syntax. Trevor AI is a daily planning program that leverages intelligent time blocking to connect your list of activities and calendar. Deep Nostalgia is an online tool developed by a company called My Heritage and can animate faces from old pictures. Durable helps create sample websites in under 30 seconds for people starting a new business or who are generally not well-versed in web development. Jasper AI, formerly known as Javis, is a lowcost service that generates original material such as blog entries for you. With Tetra, you don't have to note down your minutes of meeting every day. The latest groundbreaking texttop picture generator from OpenAI is called Dolly 2. OpenAI has unveiled Chat GPT, a powerful new chatbot that uses an improved version of its AI technology to converse in plain English.
Top 10 AI Robots In 2023
IBO is a charming little robot dog created by Sony. Spot is a four-legged robot produced by Boston Dynamics, an American robotics company. Serena 4 is a humanoid robot created by scientists at the University of Thran. Aquinaut is a shape-shifting underwater robot developed by Houston Meatronics Incorporated in Texas. Stantronics are simple animatronic stunt doubles. Flippy is an autonomous robotic kitchen assistant that can assist chefs in preparing freshlycooked burgers and fried foods such as crispy chicken tenders and teratons. Sophia is regarded to be the most intelligent humanoid robot. Atlas is a humanoid robot created by Boston Dynamics and renowned for its unmatched ability to jump over obstacles, do back flips, and dance. The Pepper robot is among business's most sophistically commercially available social robots today. Engineered Arts describes AMA as the world's most advanced human-shaped robot, reflecting the cutting edge of human robotics technology.
Top 10 Artificial Intelligence Project Ideas 2023
Face detection system is a form of biometric recognition. Chatbot is the best idea if you have chosen chatbot as your project topic. The rise of web services like Netflix, Amazon and YouTube has increased the use of recommended systems in our daily lives. As AI career aspirants, one will love to develop stock prediction applications as it is full of data. AI project can be created to detect heartbased diseases and also detect cancer. Search engines are utilized by all. We look for information on the greatest product to buy, a nice area to hang out or solutions to any questions we have. The challenge is to build a virtual assistant to assist user. Automated hate speech detection is a crucial weapon in the fight against hate speech propagation, especially on social media. You will need to estimate the sale price of a brand new home in any place for this assignment.
Career Opportunities In Artificial Intelligence 2023
An engineer in robotics create prototypes, constructs and test machines and updates the software that manages them. The role of a product manager is to recognize and express user requirements, market research and creating competitive evaluations and also creating a product's vision and putting emphasis on a product strengths and qualities. They mainly deal with lots of data. Extraction of knowledge from all collected data is the subject matter of a data science. Data mining, data cleaning, data interpretation are the three main task of an AI data analyst. A business intelligence developer's main duty is to take both business ends and AI into account. AI engineers are problem solvers who create, test and use various artificial intelligence models.
