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Technologies that rely on model- and algorithm-based machine learning and increasingly place a focus on perception,
              reasoning, and generalization have employed AI to assist in the sequencing of RNA for vaccines and mimic human
              speech. With advancements like these, AI has reclaimed the spotlight like never before, and it is not about to relinquish
              it any time soon.
              To learn more watch the video
              How Powerful Will AI Be In 2030? - https://www.youtube.com/watch?v=XKMvk5hWDfo
              Also, read the following article to see how AI is helping farmers improve crop yield in India:
              https://indiaai.gov.in/article/ai-for-the-farmer


                      Non-technical Explanation of Deep Learning


              Let us understand how deep learning works in a simple way. Suppose you order food from Swiggy. In such a case, the
              delivery man calculates the cost of petrol of best possible route. Whichever route uses up less fuel and saves time is the
              best route. Similarly, in deep learning, the weights of each hidden layer are adjusted to get optimum function.


                      Challenges Posed by AI

              Let us now see what challenges will be posed by AI:

              •  Bias: AI systems learn from data. If the data is biased, i.e., data favours a particular group/gender/class, the resulting
                  decisions made by the AI model are also biased.
              •  Unemployment: Due to automation, certain jobs will become obsolete. There will be some highly skilled jobs
                  created too, but some jobs will definitely get affected by AI.
              •  Disparate control over data: Data is AI fuel—the more data you have, the smarter are the AI machines. Tech
                  giants are investing heavily in data collection and AI projects. This gives them an unfair advantage over their smaller
                  competitors.
              •  Privacy: In this world of digital networks, privacy is becoming almost impossible. Many consumer products, from smart
                  appliances to computer applications, have characteristics that make them vulnerable to data exploitation by AI. AI can
                  be used to identify, track and monitor people on multiple devices, whether at work, at home, or in a public place. To
                  make matters worse, AI doesn't forget anything. Once the AI knows you, it remembers you forever!




                        At a Glance

                    •  Today, AI has become an integral part of human life and has penetrated areas as diverse as science, engineering,
                     business, medicine, video games, etc.
                    •  A chatbot is an AI application that can mimic a real conversation with a user in their natural language.
                    •  Chatbots allow communication through the text interface or audio on websites, messaging applications, or
                     smartphones.
                    •  There are two types of chatbot—Rule-based and AI-based Chatbot.
                    •  Rule-based chatbots map conversations as a flowchart.
                    •  AI-based chatbots use machine learning to understand the context and intent of a question before formulating
                     an answer.
                    •  Natural Language Processing, or NLP, is an area of artificial intelligence that employs natural language for
                     interaction between computers and humans.





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