AI is not a new concept for people nowadays. The first time someone talked about AI was in 1950. But imagine someone talking about Artificial Intelligence in the 90s. People would have mocked the person, who would have thought about this. But what seemed to be just imagination became a reality.
Alan Turing, a British mathematician, was the first to come up with the idea of machines that had the thinking ability back in 1950. However, at that time, they ridiculed his ideas. But after Turing died in the mid-1950s, the term “Artificial Intelligence” gained popularity. Google Assistant, Amazon Alexa, and Apple Siri are all examples of Artificial Intelligence.
What are AI and ML
AI stands for “Artificial Intelligence”, whereas ML stands for “Machine Learning”. Natural beings such as animals and humans have innate intelligence, but machines manifest artificial intelligence since they are not natural beings.
Artificial Intelligence copies or mimics the functions associated with humans, such as learning and problem-solving. The main topics in AI programs consist of problem-solving, automatic programming, planning, machine learning, etc. Self-driven cars by Tesla, intelligent assistants such as Siri and Google Assistant, manufacturing robots, smartwatch keeping track of your health are all examples of AI programs.
Machine Learning is a branch of AI that can make software applications accurate at predicting outcomes without being programmed by a human. ML is the technology that is responsible for providing more precise and efficient results. Not only ML leads to additional efficiency, but it also reduces human error.
There are three types of ML:
- Supervised learning
- Unsupervised learning
- Reinforcement learning
Applications of AI and ML in India
Applications of AI
- Speech Recognition: Nowadays, tech companies use this technology for authorization and validation. This speech recognition is also used for content writing, voice-enabled or audio messages in Whatsapp, voice-controlled remote for an Android TV, and more.
- Natural Language Processing (NLP): NLP is the application used to understand the human text. Virtual assistants such as Google Assistant and Siri use this application to understand humans.
- Image Recognition: With the help of this application, users can animate their pictures. In addition, facial recognition and fingerprint ID features of mobile phones are examples of image recognition.
- Stock Trading: Certain AI Programs and platforms allow or can perform automated stock trading. AI can predict high-return stocks with more accuracy than humans.
- Robots: Lately, It is India has created seven humanoid robots that have been a success. Manav is India’s first 3D printed robot. capable of doing push-ups, headstands and can also play football. However, this humanoid is primarily meant for research purposes. The other robots are Mitra, Robocop, KEMPA, RADA, IRA, and INDRO.
- Agriculture: AI programs can also be used for farming and agricultural programs. It can predict the time a particular crop like potato will take to be ready for yield.
- Cyber security: Cyber security has become a significant issue nowadays. With the help of AI programs, attempts are being made to keep organizations’ confidential information secure.
Fields of Applications of ML in India
- Virtual Personal Assistants: Siri, Alexa, and Google are some famous examples of virtual personal assistants. Virtual assistants have made their way to various platforms, such as – smart speakers, smartphones, mobile apps, and more.
- Predictions while Commuting:
- Traffic Predictions: The primary job of ML over here is to find or estimate the regions where congestion can be seen daily. It helps in preventing traffic and does congestion analysis.
- Online Transportation Network: Booking an individual cab is priced higher than share cabs. Why does the price get reduced when you are going to a similar location? The answer is Machine Learning. ML is used to define price during surge hours by predicting the rider demand.
- Videos Surveillance: Video surveillance is an example of ML doing its job at the backend. Computers are trained to check people with mysterious or unusual behavior like standing motionless for a long time. The system alerts the human attendants, which can help in avoiding mishaps.
- Social Media Services: Ever wondered that when you want to buy something, and you happen to search for it on Google, your media accounts also start to show ads about the product from different companies. These ads show up due to the use of ML. Your news feed showing you the type of content you like is another example of ML. Here are a few examples that you happen to use in your daily life without even realizing that it is the application of ML.
- People you may know
- Face Recognition
- Similar Pins
- Product Recommendation: When you want to purchase something and start browsing through the pages of shopping apps like Flipkart and Snapdeal, you begin getting recommendations that match your taste. This magic that you get to experience is another example of Machine Learning. It works based on your past purchases, items added to the cart, products added to the wishlist, and brand preferences.
- Online Fraud Detection: With bank-to-bank UPI transactions gaining popularity in India, ML tries its best to make cyberspace a secure place. It is done by tracking monetary funds online. Paypal using ML for protection against money laundering is one example of ML. It compares millions of transactions and differentiates them between legitimate and illegitimate transactions taking place between buyer and seller.
- Network Protection: With the use of machine learning, it has become possible to activate highly sophisticated intrusion detection systems
- Suspect User Behaviour: Some ML applications can identify fraud by spiteful users at the time they occur.
These applications of AI and ML are not by means an exhaustive list. There are various applications, and they are also being applied to multiple new fields to utilize their full potential. As the scope widens, the demand for those with these skills also rises. Therefore, it would be beneficial to you if you upskill with AI and ML training. You can get a PG diploma in computer science distance learning and further your career in AI and ML.
The best part about distance learning is learning and earning a degree from your home without relocating yourself. You won’t need to pay the rent or buy essentials at a completely different place. This way, you will even save a lot by not traveling to a completely different city. You can earn and learn simultaneously by taking up a part-time job suitable for you. Also, distance learning is cheaper, as colleges charge lesser fees than traditional colleges without compromising on quality.
