What are emerging technologies?
An emerging technology is a new technology that is still growing and will change life and work in the coming years. In this chapter we meet eleven of them. They often work together: sensors collect data, the cloud stores it, and AI learns from it.
Artificial Intelligence (AI)
Artificial Intelligence means making machines do tasks that need human-like thinking: seeing, understanding speech, deciding, and learning. The aim is a machine that can act sensibly in a new situation.
Examples of AI
- Face unlock on a phone.
- A map app finding the fastest route.
- Games where the computer player plans its moves.
- Voice assistants that answer questions.
Machine Learning (ML)
Machine learning is a part of AI. Instead of writing every rule by hand, we give the computer many examples (data). It finds the pattern on its own and builds a model. The model then makes predictions on new data it has never seen.
How ML works
- Training data: many examples, often with the right answer (label).
- Training: the algorithm finds the pattern.
- Testing: we check the model on new examples.
- Prediction: the model is used for real.
Uses: spam filters in email, movie suggestions, price prediction, medical image checks. More good data usually means better predictions.
Natural Language Processing (NLP)
NLP is the part of AI that helps computers understand, read, write and speak human languages like Hindi and English.
What NLP does
- Breaks a sentence into words (tokens).
- Works out the meaning and the intent.
- Produces a reply, a summary or a translation.
Uses: chatbots, voice assistants, auto-complete while typing, spell check, translation apps, and sorting reviews as happy or unhappy (sentiment analysis).
Augmented Reality (AR) and Virtual Reality (VR)
Augmented Reality
AR adds computer-made objects on top of the real world you can still see, usually through a phone camera or smart glasses. Examples: photo filters, apps that place a virtual sofa in your room, games where characters appear on the street.
Virtual Reality
VR creates a complete computer-made 3D world. You wear a headset that blocks the real world, and the view moves as you turn your head. Examples: flight training, virtual tours of monuments, practice for surgeons.
AR vs VR
| AR | VR |
|---|---|
| Real world + virtual objects | Only a virtual world |
| Phone or glasses are enough | Needs a headset |
| You stay aware of your surroundings | Real surroundings are hidden |
Mixed reality goes one step further: virtual objects can react to real ones.
Robotics
A robot is a machine that can do tasks on its own or with little help. Robotics is the field of designing, building and programming robots.
Parts of a robot
- Sensors to feel the world (camera, touch, distance).
- Processor (the brain) running a program, often with AI.
- Actuators / motors to move and act.
Examples: robot arms in car factories, robot vacuum cleaners, Mars rovers, drones, surgical robots. Robots do work that is repetitive, dangerous or needs great accuracy.
Big Data
Big data means data sets so large and fast-growing that normal software cannot store or handle them easily. Social media posts, online shopping clicks and sensor readings all create big data.
The 5 Vs of big data
- Volume: a huge amount of data.
- Velocity: it arrives very fast, often every second.
- Variety: many kinds: text, photos, videos, numbers.
- Veracity: how correct and trustworthy it is.
- Value: the useful knowledge we can get from it.
Data analytics is the process of studying big data to find patterns, for example which products sell more in winter.
Internet of Things (IoT) and sensors
The Internet of Things is a network of everyday objects (fans, bulbs, watches, meters, cars) that have sensors and software and are connected to the internet, so they can send and receive data without a person typing it.
Sensors
A sensor is a small device that measures something in the world and turns it into data: temperature, light, motion, sound, moisture, location (GPS). Your phone alone has an accelerometer, gyroscope, GPS and light sensor.
Web of Things
When IoT devices use normal web technology so that they can talk to each other and to web apps, it is called the Web of Things.
Examples: a smart bulb switched from an app, a soil-moisture sensor that starts a water pump, a fitness band sending your heart rate to your phone.
Smart cities
A smart city uses IoT sensors, networks and data analysis to run its services better and to save energy, water and time.
Examples
- Traffic lights that change timing based on live traffic.
- Street lights that dim when the road is empty.
- Dustbins that tell the office when they are full.
- Water pipes that report leaks.
- Apps that show when the next bus will come.
Challenges: privacy of people's data, cyber security, and the high cost of setting it up.
Cloud computing: SaaS, IaaS and PaaS
Cloud computing means using computing resources (servers, storage, software) over the internet, owned by a cloud provider, and paying only for what you use. You do not need to buy and look after the machines yourself.
The three service models
- IaaS (Infrastructure as a Service): you rent raw computing: virtual machines, storage and network. You install and manage everything else. Like renting an empty flat.
- PaaS (Platform as a Service): you get a ready platform (operating system, database, programming tools) to build and run your own apps. Like a flat with a ready kitchen: you just cook.
- SaaS (Software as a Service): you use a finished app through a browser. Web email, online word processors and video-call apps are SaaS. Like ordering ready food.
Benefits
Low starting cost, access from anywhere, easy to grow, automatic updates and backup. Risks: needs internet, and your data sits with someone else.
Grid computing
Grid computing joins many computers, often in different places and owned by different people, into one team. A huge job is split into small pieces, each computer works on a piece, and the results are combined.
It is used for heavy scientific work such as weather models, studying proteins, or searching radio signals from space. Volunteers can even donate their home computer's idle time.
Grid vs cloud
In the cloud, one provider offers services to many users. In a grid, many computers from many owners share their power to finish one big task.
Blockchain
Blockchain is a way of keeping records (like a digital register) that is shared among many computers instead of one central office.
How it works
- Records are grouped into blocks.
- Each block stores a hash (a short digital fingerprint) of the block before it, so the blocks form a chain.
- Every member (node) keeps a full copy of the chain. This is called a decentralised or distributed ledger.
- If someone changes an old block, its hash changes and the chain after it breaks. Other members' copies show the mismatch, so the change is rejected.
Uses: digital currencies, tracking food or medicine from farm to shop, land records, certificates, and secure voting trials. Benefit: transparent and very hard to tamper with. Limit: uses much energy and storage.
Try it: spot the tech at home
Walk around your home for 10 minutes. List every device and name its technology: smart TV (IoT + SaaS apps), phone keyboard suggestions (NLP + ML), photo filter (AR), map app (big data + AI). Then open the 3D free-play step and change block 2 of the blockchain: count how many links break.
Key formulas and definitions
- AI ⊃ Machine learning: ML is one way to build AI (learning from data).
- Robot = sensors (sense) + processor (think) + actuators (act).
- Big data 5 Vs = Volume, Velocity, Variety, Veracity, Value.
- Cloud models: IaaS (infrastructure) → PaaS (+ platform) → SaaS (+ ready software).
- Blockchain: each block stores the hash of the previous block; copies kept by all members.
Worked examples
1. A school uses an online word processor through a browser, without installing anything. Which cloud model is this?
SaaS (Software as a Service): the finished app is used over the internet; the provider handles servers, platform and updates.
2. A start-up rents virtual machines and storage and installs its own operating system and database on them. Which cloud model?
IaaS: they rent only the infrastructure (machines, storage, network) and manage everything above it themselves.
3. A shopping app shows 'people who bought this also bought…'. Name the technologies involved.
Big data (millions of purchases are recorded) and machine learning (a model learns which products are bought together and predicts what you may like).
4. Classify each as AR or VR: (a) a headset game inside a spaceship, (b) a ruler app that measures your table using the camera, (c) a virtual museum tour with a headset.
(a) VR, (b) AR, (c) VR. AR keeps the real world visible; VR replaces it completely.
5. A farmer's field has a soil-moisture sensor that switches on a pump by itself and sends a message to his phone. Which technologies are used?
IoT with sensors: the sensor measures moisture, the connected device acts (pump), and it sends data over the internet to the phone.
6. In a chain of 4 blocks, someone secretly edits block 2. Explain step by step why the change is caught.
Step 1: editing block 2 changes its data, so its hash changes. Step 2: block 3 stored the old hash of block 2, so the link 2→3 no longer matches. Step 3: this breaks every link after block 2. Step 4: all other members have the original copy, so the network sees the mismatch and rejects the edited chain.
Common mistakes
- Thinking AI and machine learning are the same. ML is only one part of AI: the part that learns from data.
- Mixing up AR and VR. AR adds to the real world; VR replaces it with a fully virtual one.
- Saying cloud and grid computing are the same. Cloud = services rented from a provider; grid = many computers sharing one big job.
- Believing blockchain data can never be read by anyone. It is usually visible to members; what makes it safe is that it is very hard to change secretly.