Emerging Trends (AI, IoT, Cloud …)

What are emerging trends?

New technologies keep changing our lives — from paying by UPI to studying with AI tutors. Technologies that are new, growing fast and expected to have a big impact are called emerging trends. As an IP student you will work with data, so notice how almost every trend below depends on collecting and analysing data.

Artificial Intelligence

Artificial Intelligence (AI) is the ability of a computer or machine to imitate human thinking — to learn from experience, reason, understand language, recognise images and make decisions.

Machine learning – learning from data

Machine learning (ML) is a part of AI in which a computer finds patterns in past data and uses them to make predictions about new data — without being given every rule. The more good data it sees, the better its predictions become.

A very small idea of "learning" in Python — find the pattern between study hours and marks, then predict:

# A tiny "learning" example: predict marks from study hours
hours = [1, 2, 3, 4, 5]
marks = [35, 45, 55, 65, 75]
# find the pattern: marks increase by 10 per hour
rate = (marks[-1] - marks[0]) / (hours[-1] - hours[0])
base = marks[0] - rate * hours[0]
for h in (6, 7):
    print(h, 'hours -> predicted marks', base + rate * h)

Real ML (Netflix suggestions, spam filters, face unlock) uses millions of examples and complex mathematics, but the idea is the same.

NLP, immersive experiences and robotics

Big data and data analytics

Big data refers to data that is too large or complex for ordinary software. It is described by five Vs:

Data analytics is examining data to find trends and make decisions. Example: a city traffic department analyses camera and GPS data to time signals better; a supermarket studies bills to place items bought together side by side.

Internet of Things and smart cities

The Internet of Things (IoT) is a network of everyday objects with sensors and internet connection that collect and share data and can be controlled remotely. The Web of Things lets us control them through web pages and apps.

Sensors (temperature, humidity, light, motion, GPS, heartbeat) are the "senses" of IoT. A smart city uses IoT for traffic control, street lights that dim when roads are empty, waste-bin level alerts, air-quality monitors and water-leak detection.

Cloud computing

Cloud computing delivers computing services — storage, servers, databases, software — over the internet. You pay (or use free plans) only for what you use and can access it from anywhere.

Grid computing

In grid computing, many computers in different places are linked to work together on one big task that a single computer could not finish quickly — such as analysing data from telescopes or particle accelerators. Each computer works on a small piece and sends back the result.

Blockchain

A blockchain is a digital ledger copied on many computers. Each block holds records plus the hash of the previous block, forming a chain. Because every copy must agree, changing old records secretly is practically impossible.

Uses: cryptocurrency, digital certificates, supply-chain tracking of food and medicines, land records, voting.

Summary & practice

• AI imitates human intelligence; ML learns patterns from data.
• NLP handles language; AR adds to reality, VR replaces it; robots act in the physical world.
• Big data: 5 Vs; analytics turns it into decisions.
• IoT connects devices with sensors; cloud gives IaaS, PaaS, SaaS; grid shares computing power; blockchain is a shared, tamper-proof ledger.